From aa89fa1f4c05d16cdd85aef9135948d0885252fe Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Thu, 4 Mar 2021 19:51:30 +0100
Subject: [PATCH 01/87] Refactor profilers

---
 pytorch_lightning/callbacks/progress.py       |   3 +-
 pytorch_lightning/profiler/profilers.py       | 148 ++++++-------
 pytorch_lightning/profiler/pytorch.py         | 196 ++++++++----------
 .../trainer/connectors/profiler_connector.py  |   5 +-
 pytorch_lightning/trainer/training_loop.py    |   2 +-
 tests/deprecated_api/test_remove_1-5.py       |   6 +
 tests/test_profiler.py                        | 162 ++++++++++++++-
 tests/trainer/test_trainer.py                 | 109 ----------
 8 files changed, 322 insertions(+), 309 deletions(-)

diff --git a/pytorch_lightning/callbacks/progress.py b/pytorch_lightning/callbacks/progress.py
index 2f133eaccf512..9b960d2553390 100644
--- a/pytorch_lightning/callbacks/progress.py
+++ b/pytorch_lightning/callbacks/progress.py
@@ -39,8 +39,7 @@
 
 class tqdm(_tqdm):
     """
-    Custom tqdm progressbar where we append 0 to floating points/strings to
-    prevent the progress bar from flickering
+    Custom tqdm progressbar where we append 0 to floating points/strings to prevent the progress bar from flickering
     """
 
     @staticmethod
diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index 75bcda09e1af7..644aa0e6f6255 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -12,7 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 """Profiler to check if there are any bottlenecks in your code."""
-
 import cProfile
 import io
 import logging
@@ -22,7 +21,7 @@
 from abc import ABC, abstractmethod
 from collections import defaultdict
 from contextlib import contextmanager
-from typing import Optional, Union
+from typing import Optional
 
 import numpy as np
 
@@ -31,22 +30,8 @@
 log = logging.getLogger(__name__)
 
 
-class BaseProfiler(ABC):
-    """
-    If you wish to write a custom profiler, you should inhereit from this class.
-    """
-
-    def __init__(self, output_streams: Optional[Union[list, tuple]] = None):
-        """
-        Args:
-            output_streams: callable
-        """
-        if output_streams:
-            if not isinstance(output_streams, (list, tuple)):
-                output_streams = [output_streams]
-        else:
-            output_streams = []
-        self.write_streams = output_streams
+class AbstractProfiler(ABC):
+    """Specification of a profiler."""
 
     @abstractmethod
     def start(self, action_name: str) -> None:
@@ -56,6 +41,38 @@ def start(self, action_name: str) -> None:
     def stop(self, action_name: str) -> None:
         """Defines how to record the duration once an action is complete."""
 
+    @abstractmethod
+    def summary(self) -> str:
+        """Create profiler summary in text format."""
+
+
+class BaseProfiler(AbstractProfiler, ABC):
+    """
+    If you wish to write a custom profiler, you should inherit from this class.
+    """
+
+    def __init__(self, local_rank: Optional[int] = None, log_dir: Optional[str] = None) -> None:
+        self.output_fname = getattr(self, "output_fname", None)
+        # the profiler can be used outside of lightning
+        # that's why we call `on_train_start` manually
+        self.on_train_start(local_rank=local_rank, log_dir=log_dir)
+
+    def on_train_start(self, local_rank: Optional[int] = None, log_dir: Optional[str] = None):
+        """
+        This function is used by the Trainer to inject local_rank with `DDP`
+        and `TensorBoardLogger` log_dir in the profiler.
+        """
+        self.local_rank = local_rank
+        self.log_dir = log_dir
+        self.prepare_file()
+
+    def prepare_file(self) -> None:
+        self.output_file = None
+        if self.output_fname:
+            fs = get_filesystem(self.output_fname)
+            self.output_file = fs.open(self.output_fname, "w")
+        self.write_streams = [self.output_file.write] if self.output_file else [log.info]
+
     @contextmanager
     def profile(self, action_name: str) -> None:
         """
@@ -91,13 +108,23 @@ def describe(self) -> None:
         """Logs a profile report after the conclusion of the training run."""
         for write in self.write_streams:
             write(self.summary())
+        if self.output_file:
+            self.output_file.flush()
 
-    @abstractmethod
-    def summary(self) -> str:
-        """Create profiler summary in text format."""
-
-    def on_train_start(self, local_rank: Optional[int] = None):
-        self.local_rank = local_rank
+    def stats_to_str(self, stats: dict) -> str:
+        output = ["Profiler Report"]
+        for action, value in stats.items():
+            header = f"Profile stats for: {action}"
+            if getattr(self, "local_rank", None) is not None:
+                header += f" rank: {self.local_rank}"
+            output.append(header)
+            output.append(value)
+        return os.linesep.join(output)
+
+    def __del__(self) -> None:
+        """Close profiler's stream."""
+        if self.output_file:
+            self.output_file.close()
 
 
 class PassThroughProfiler(BaseProfiler):
@@ -125,7 +152,7 @@ class SimpleProfiler(BaseProfiler):
     the mean duration of each action and the total time spent over the entire training run.
     """
 
-    def __init__(self, output_filename: Optional[str] = None, extended=True):
+    def __init__(self, output_filename: Optional[str] = None, extended: bool = True):
         """
         Args:
             output_filename: optionally save profile results to file instead of printing
@@ -136,19 +163,12 @@ def __init__(self, output_filename: Optional[str] = None, extended=True):
                 If you attempt to start an action which has already started, or
                 if you attempt to stop recording an action which was never started.
         """
+        self.output_fname = output_filename
         self.current_actions = {}
         self.recorded_durations = defaultdict(list)
         self.extended = extended
-
-        self.output_fname = output_filename
-        self.output_file = None
-        if self.output_fname:
-            fs = get_filesystem(self.output_fname)
-            self.output_file = fs.open(self.output_fname, "w")
-
-        streaming_out = [self.output_file.write] if self.output_file else [log.info]
+        super().__init__()
         self.start_time = time.monotonic()
-        super().__init__(output_streams=streaming_out)
 
     def start(self, action_name: str) -> None:
         if action_name in self.current_actions:
@@ -170,7 +190,8 @@ def make_report(self):
         return report, total_duration
 
     def summary(self) -> str:
-        output_string = "\n\nProfiler Report\n"
+        sep = os.linesep
+        output_string = f"Profiler Report{sep}"
 
         if self.extended:
 
@@ -178,16 +199,16 @@ def summary(self) -> str:
                 max_key = np.max([len(k) for k in self.recorded_durations.keys()])
 
                 def log_row(action, mean, num_calls, total, per):
-                    row = f"{os.linesep}{action:<{max_key}s}\t|  {mean:<15}\t|"
+                    row = f"{sep}{action:<{max_key}s}\t|  {mean:<15}\t|"
                     row += f"{num_calls:<15}\t|  {total:<15}\t|  {per:<15}\t|"
                     return row
 
                 output_string += log_row("Action", "Mean duration (s)", "Num calls", "Total time (s)", "Percentage %")
                 output_string_len = len(output_string)
-                output_string += f"{os.linesep}{'-' * output_string_len}"
+                output_string += f"{sep}{'-' * output_string_len}"
                 report, total_duration = self.make_report()
                 output_string += log_row("Total", "-", "_", f"{total_duration:.5}", "100 %")
-                output_string += f"{os.linesep}{'-' * output_string_len}"
+                output_string += f"{sep}{'-' * output_string_len}"
                 for action, durations, duration_per in report:
                     output_string += log_row(
                         action,
@@ -199,27 +220,16 @@ def log_row(action, mean, num_calls, total, per):
         else:
 
             def log_row(action, mean, total):
-                return f"{os.linesep}{action:<20s}\t|  {mean:<15}\t|  {total:<15}"
+                return f"{sep}{action:<20s}\t|  {mean:<15}\t|  {total:<15}"
 
             output_string += log_row("Action", "Mean duration (s)", "Total time (s)")
-            output_string += f"{os.linesep}{'-' * 65}"
+            output_string += f"{sep}{'-' * 65}"
 
             for action, durations in self.recorded_durations.items():
                 output_string += log_row(action, f"{np.mean(durations):.5}", f"{np.sum(durations):.5}")
-        output_string += os.linesep
+        output_string += sep
         return output_string
 
-    def describe(self):
-        """Logs a profile report after the conclusion of the training run."""
-        super().describe()
-        if self.output_file:
-            self.output_file.flush()
-
-    def __del__(self):
-        """Close profiler's stream."""
-        if self.output_file:
-            self.output_file.close()
-
 
 class AdvancedProfiler(BaseProfiler):
     """
@@ -241,17 +251,10 @@ def __init__(self, output_filename: Optional[str] = None, line_count_restriction
             ValueError:
                 If you attempt to stop recording an action which was never started.
         """
+        self.output_fname = output_filename
         self.profiled_actions = {}
         self.line_count_restriction = line_count_restriction
-
-        self.output_fname = output_filename
-        self.output_file = None
-        if self.output_fname:
-            fs = get_filesystem(self.output_fname)
-            self.output_file = fs.open(self.output_fname, "w")
-
-        streaming_out = [self.output_file.write] if self.output_file else [log.info]
-        super().__init__(output_streams=streaming_out)
+        super().__init__()
 
     def start(self, action_name: str) -> None:
         if action_name not in self.profiled_actions:
@@ -261,9 +264,7 @@ def start(self, action_name: str) -> None:
     def stop(self, action_name: str) -> None:
         pr = self.profiled_actions.get(action_name)
         if pr is None:
-            raise ValueError(  # pragma: no-cover
-                f"Attempting to stop recording an action ({action_name}) which was never started."
-            )
+            raise ValueError(f"Attempting to stop recording an action ({action_name}) which was never started.")
         pr.disable()
 
     def summary(self) -> str:
@@ -273,21 +274,4 @@ def summary(self) -> str:
             ps = pstats.Stats(pr, stream=s).strip_dirs().sort_stats('cumulative')
             ps.print_stats(self.line_count_restriction)
             recorded_stats[action_name] = s.getvalue()
-
-        # log to standard out
-        output_string = f"{os.linesep}Profiler Report{os.linesep}"
-        for action, stats in recorded_stats.items():
-            output_string += f"{os.linesep}Profile stats for: {action}{os.linesep}{stats}"
-
-        return output_string
-
-    def describe(self):
-        """Logs a profile report after the conclusion of the training run."""
-        super().describe()
-        if self.output_file:
-            self.output_file.flush()
-
-    def __del__(self):
-        """Close profiler's stream."""
-        if self.output_file:
-            self.output_file.close()
+        return self.stats_to_str(recorded_stats)
diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index 4ccb88883260e..ed973501b3247 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -12,17 +12,16 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 """Profiler to check if there are any bottlenecks in your code."""
-
 import inspect
 import logging
 import os
-from typing import List, Optional
+from typing import Dict, List, Optional, Union
 
 import torch
+from torch.autograd.profiler import EventList, FunctionEvent
 
 from pytorch_lightning.profiler.profilers import BaseProfiler
 from pytorch_lightning.utilities import rank_zero_only
-from pytorch_lightning.utilities.cloud_io import get_filesystem
 from pytorch_lightning.utilities.distributed import rank_zero_warn
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 
@@ -31,7 +30,7 @@
 
 class PyTorchProfiler(BaseProfiler):
 
-    PROFILED_FUNCTIONS = ("training_step_and_backward", "validation_step", "test_step")
+    RECORD_FUNCTIONS = ("training_step_and_backward", "training_step", "backward", "validation_step", "test_step")
     AVAILABLE_SORT_KEYS = (
         "cpu_time",
         "cuda_time",
@@ -48,27 +47,26 @@ def __init__(
         self,
         output_filename: Optional[str] = None,
         enabled: bool = True,
+        use_cpu: bool = True,
         use_cuda: bool = False,
         record_shapes: bool = False,
         profile_memory: bool = False,
         group_by_input_shapes: bool = False,
         with_stack: bool = False,
-        use_kineto: bool = False,
-        use_cpu: bool = True,
         emit_nvtx: bool = False,
         export_to_chrome: bool = False,
-        path_to_export_trace: str = None,
+        path_to_export_trace: Optional[str] = None,
         row_limit: int = 20,
         sort_by_key: Optional[str] = None,
-        profiled_functions: Optional[List] = None,
+        record_functions: Optional[List[str]] = None,
         local_rank: Optional[int] = None,
-    ):
+        profiled_functions: Optional[List[str]] = None,
+    ) -> None:
         """
         This profiler uses PyTorch's Autograd Profiler and lets you inspect the cost of
         different operators inside your model - both on the CPU and GPU
 
         Args:
-
             output_filename: optionally save profile results to file instead of printing
                 to std out when training is finished. When using ``ddp``,
                 each rank will stream the profiled operation to their own file
@@ -76,21 +74,18 @@ def __init__(
 
             enabled: Setting this to False makes this context manager a no-op.
 
+            use_cpu: record events on the CPU
+
             use_cuda: Enables timing of CUDA events as well using the cudaEvent API.
                 Adds approximately 4us of overhead to each tensor operation.
 
             record_shapes: If shapes recording is set, information about input dimensions will be collected.
 
-            profile_memory: Whether to report memory usage, default: True (Introduced in PyTorch 1.6.0)
+            profile_memory: Whether to report memory usage
 
             group_by_input_shapes: Include operator input shapes and group calls by shape.
 
-            with_stack: record source information (file and line number) for the ops (Introduced in PyTorch 1.7.0)
-
-            use_kineto: experimental support for Kineto profiler (Introduced in PyTorch 1.8.0)
-
-            use_cpu: use_kineto=True and can be used to lower the overhead
-                for GPU-only profiling (Introduced in PyTorch 1.8.0)
+            with_stack: record source information (file and line number) for the ops
 
             emit_nvtx: Context manager that makes every autograd operation emit an NVTX range
                 Run::
@@ -102,18 +97,18 @@ def __init__(
                     nvvp trace_name.prof
                     torch.autograd.profiler.load_nvprof(path)
 
-            export_to_chrome: Wether to export the sequence of profiled operators for Chrome.
+            export_to_chrome: Whether to export the sequence of profiled operators for Chrome.
                 It will generate a ``.json`` file which can be read by Chrome.
 
             path_to_export_trace: Directory path to export ``.json`` traces when using ``export_to_chrome=True``.
                 By default, it will be save where the file being is being run.
 
-            row_limit: Limit the number of rows in a table, `0` is a special value that
+            row_limit: Limit the number of rows in a table, ``0`` is a special value that
                 removes the limit completely.
 
-            sort_by_key: Keys to sort out profiled table
+            sort_by_key: Keys to sort out profiled table.
 
-            profiled_functions: list of profiled functions which will create a context manager on.
+            record_functions: list of profiled functions which will create a context manager on.
                 Any other will be pass through.
 
             local_rank: When running in distributed setting, local_rank is used for each process
@@ -126,91 +121,99 @@ def __init__(
             ValueError:
                 If you attempt to stop recording an action which was never started.
         """
+        if output_filename is not None and not output_filename.endswith(".txt"):
+            raise MisconfigurationException("`output_filename` should be a `.txt` file.")
+
+        record_functions = self.__deprecation_check(profiled_functions, record_functions)
 
-        self.profiled_actions = {}
+        self.output_fname = output_filename
         self.enabled = enabled
-        self.profiled_functions = profiled_functions or self.PROFILED_FUNCTIONS
+        self.record_functions = record_functions or self.RECORD_FUNCTIONS
+        self.use_cpu = use_cpu
         self.use_cuda = use_cuda
         self.record_shapes = record_shapes
         self.profile_memory = profile_memory
         self.sort_by_key = sort_by_key or ("cuda_time_total" if self.use_cuda else "cpu_time_total")
         self.with_stack = with_stack
         self.group_by_input_shapes = group_by_input_shapes and record_shapes
-        self.use_kineto = use_kineto
-        self.use_cpu = use_cpu
         self.row_limit = row_limit
         self.emit_nvtx = emit_nvtx
         self.export_to_chrome = export_to_chrome
         self.path_to_export_trace = path_to_export_trace
 
-        if export_to_chrome and path_to_export_trace is None:
+        if self.export_to_chrome and self.path_to_export_trace is None:
             rank_zero_warn(
-                "The exported trace would be save locally as `path_to_export_trace` is empty."
+                "The exported trace would be saved locally as `path_to_export_trace` is None."
                 " Note: Each functions will generate its own traced file."
             )
 
         if self.sort_by_key not in self.AVAILABLE_SORT_KEYS:
             raise MisconfigurationException(
-                f"Found sort_by_key: {sort_by_key}. Should be within {self.AVAILABLE_SORT_KEYS}. "
+                f"Found sort_by_key: {self.sort_by_key}. Should be within {self.AVAILABLE_SORT_KEYS}. "
             )
 
-        self.profiled_actions = {}
+        self.profiled_actions: Dict[str, Union[FunctionEvent, EventList]] = {}
         self.context_names = {}
         self.running_stack = []
         self.profiler = None
 
-        self.output_fname = output_filename
-        self.output_file = None
-        if local_rank is not None:
-            self.on_train_start(local_rank=local_rank)
-            self.on_train_start = super().on_train_start
-
-    def on_train_start(self, local_rank: Optional[str] = None):
-        self.local_rank = local_rank
-
-        # when logging to `log.info`, only perform profiling on rank 0
-        if local_rank != 0 and self.output_fname is None:
-            self.wrap_functions_into_rank_zero_only()
+        super().__init__(local_rank=local_rank)
 
-        if self.output_fname:
-            if local_rank is not None:
-                if '.txt' not in self.output_fname:
-                    raise MisconfigurationException("Log file should be .txt file.")
+    def __deprecation_check(self, profiled_functions: Optional[List[str]],
+                            record_functions: Optional[List[str]]) -> Optional[List[str]]:
+        if profiled_functions is not None:
+            rank_zero_warn(
+                "`PyTorchProfiler.profiled_functions` has been renamed to"
+                " `record_functions` in v1.3 and will be removed in v1.5", DeprecationWarning
+            )
+            if record_functions is None:
+                record_functions = profiled_functions
+            else:
+                raise MisconfigurationException(
+                    "You set `PytorchProfiler.profiled_functions` and `PyTorchProfiler.record_functions`."
+                    "  Please use only the later."
+                )
+        return record_functions
 
-                self.output_fname = self.output_fname.replace(".txt", f"_{self.local_rank}.txt")
+    def on_train_start(self, local_rank: Optional[int] = None, log_dir: Optional[str] = None) -> None:
+        super().on_train_start(local_rank=local_rank, log_dir=log_dir)
 
-            fs = get_filesystem(self.output_fname)
-            self.output_file = fs.open(self.output_fname, "w")
+        # if the user didn't `path_to_export_trace`,
+        # set it as TensorBoardLogger log_dir if exists
+        if self.path_to_export_trace is None:
+            self.path_to_export_trace = log_dir
 
-        streaming_out = [self.output_file.write] if self.output_file else [log.info]
-        super().__init__(output_streams=streaming_out)
+        # when logging to `log.info`, only perform profiling on rank 0
+        if local_rank is not None and local_rank > 0 and self.output_fname is None:
+            self._rank_zero_only_wrap()
 
-    def wrap_functions_into_rank_zero_only(self):
+    def _rank_zero_only_wrap(self) -> None:
         self.start = rank_zero_only(self.start)
         self.stop = rank_zero_only(self.stop)
         self.summary = rank_zero_only(self.summary)
         self.describe = rank_zero_only(self.describe)
 
     def start(self, action_name: str) -> None:
-        if action_name not in self.profiled_functions:
+        if action_name not in self.record_functions:
             return
 
         if len(self.running_stack) > 0:
-            self._stop(self.running_stack[-1])
+            self._stop()
+
         self.running_stack.append(action_name)
 
         self.context_names[action_name] = "/".join(self.running_stack)
 
-        self._start(action_name)
+        self._start()
 
-    def _start(self, action_name: str) -> None:
+    def _start(self) -> None:
         if self.emit_nvtx:
-            self._create_profiler(action_name, torch.cuda.profiler.profile, enter=False)
-            self._create_profiler(action_name, torch.autograd.profiler.emit_nvtx)
+            self._create_profiler(torch.cuda.profiler.profile, enter=False)
+            self._create_profiler(torch.autograd.profiler.emit_nvtx)
         else:
-            self._create_profiler(action_name, torch.autograd.profiler.profile)
+            self._create_profiler(torch.autograd.profiler.profile)
 
-    def _create_profiler(self, action_name, profiler, enter=True):
+    def _create_profiler(self, profiler, enter=True) -> None:
         init_args = inspect.signature(profiler.__init__).parameters
         profiler_args = {k: v for k, v in vars(self).items() if k in init_args}
         pr = profiler(**profiler_args)
@@ -218,42 +221,41 @@ def _create_profiler(self, action_name, profiler, enter=True):
             pr = pr.__enter__()
         self.profiler = pr
 
-    def _stop(self, action_name: str) -> None:
+    def _stop(self) -> None:
         if self.profiler is None:
             return
 
-        self.profiler.__exit__(exc_type=None, exc_val=None, exc_tb=None)
+        self.profiler.__exit__(None, None, None)
 
-        function_events = self.profiler.function_events
-        self.profiler = None
-        for name in self.running_stack:
-            if name not in self.profiled_actions:
-                self.profiled_actions[name] = function_events
-            else:
-                self.profiled_actions[name] += function_events
+        events: EventList = self.profiler.function_events
+        if events is not None:
+            for name in self.running_stack:
+                if name not in self.profiled_actions:
+                    self.profiled_actions[name] = events
+                else:
+                    self.profiled_actions[name] += events
 
     def stop(self, action_name: str) -> None:
-        if action_name not in self.profiled_functions:
+        if action_name not in self.record_functions:
             return
 
         if len(self.running_stack) == 0 or self.running_stack[-1] != action_name:
-            raise ValueError(  # pragma: no-cover
-                f"Attempting to stop recording an action ({action_name}) which was never started."
-            )
-        self._stop(action_name)
+            raise ValueError(f"Attempting to stop recording an action ({action_name}) which was never started.")
+
+        self._stop()
+
+        self.profiler = None
         self.running_stack.pop()
         # restore running profiler
         if len(self.running_stack) > 0:
-            self._start(self.running_stack[-1])
+            self._start()
 
     def summary(self) -> str:
-        recorded_stats = {}
-        output_string = ''
-        local_rank = '0' if self.local_rank is None else self.local_rank
-
-        if not self.enabled:
-            return output_string
+        if not self.enabled or self.emit_nvtx:
+            return ""
 
+        local_rank = 0 if self.local_rank is None else self.local_rank
+        recorded_stats = {}
         for action_name, function_events in self.profiled_actions.items():
 
             # next line is a workaround for a pytorch issue (fixed on master, still present
@@ -263,32 +265,14 @@ def summary(self) -> str:
 
             if self.export_to_chrome:
                 filename = f"{action_name}_{local_rank}_trace.json"
-                path_to_trace = filename if self.path_to_export_trace is None \
-                    else os.path.join(self.path_to_export_trace, filename)
+                path_to_trace = (
+                    filename
+                    if self.path_to_export_trace is None else os.path.join(self.path_to_export_trace, filename)
+                )
                 function_events.export_chrome_trace(path_to_trace)
 
-            if self.emit_nvtx:
-                return output_string
+            data = function_events.key_averages(group_by_input_shapes=self.group_by_input_shapes)
+            table = data.table(sort_by=self.sort_by_key, row_limit=self.row_limit)
+            recorded_stats[action_name] = table
 
-            else:
-                data = function_events.key_averages(group_by_input_shapes=self.group_by_input_shapes)
-                table = data.table(sort_by=self.sort_by_key, row_limit=self.row_limit)
-                recorded_stats[action_name] = table
-
-        # log to standard out
-        output_string = f"{os.linesep}Profiler Report{os.linesep}"
-        for action, stats in recorded_stats.items():
-            output_string += (f"{os.linesep}Profile stats for: {action} rank: {local_rank} {os.linesep}{stats}")
-
-        return output_string
-
-    def describe(self):
-        """Logs a profile report after the conclusion of the training run."""
-        super().describe()
-        if self.output_file:
-            self.output_file.flush()
-
-    def __del__(self):
-        """Close profiler's stream."""
-        if self.output_file:
-            self.output_file.close()
+        return self.stats_to_str(recorded_stats)
diff --git a/pytorch_lightning/trainer/connectors/profiler_connector.py b/pytorch_lightning/trainer/connectors/profiler_connector.py
index 98d65c1285ff7..7639926424090 100644
--- a/pytorch_lightning/trainer/connectors/profiler_connector.py
+++ b/pytorch_lightning/trainer/connectors/profiler_connector.py
@@ -55,5 +55,6 @@ def on_trainer_init(self, profiler: Union[BaseProfiler, str]):
         self.trainer.profiler = profiler or PassThroughProfiler()
 
     def on_train_start(self, trainer):
-        local_rank = trainer.local_rank if trainer.world_size > 1 else None
-        self.trainer.profiler.on_train_start(local_rank)
+        if not isinstance(trainer.profiler, PassThroughProfiler):
+            local_rank = trainer.local_rank if trainer.world_size > 1 else None
+            self.trainer.profiler.on_train_start(local_rank=local_rank, log_dir=self.trainer.log_dir)
diff --git a/pytorch_lightning/trainer/training_loop.py b/pytorch_lightning/trainer/training_loop.py
index 97814bb912fbe..39548b5ed64c5 100644
--- a/pytorch_lightning/trainer/training_loop.py
+++ b/pytorch_lightning/trainer/training_loop.py
@@ -749,7 +749,7 @@ def training_step_and_backward(self, split_batch, batch_idx, opt_idx, optimizer,
 
                 # backward pass
                 if result is not None:
-                    with self.trainer.profiler.profile("model_backward"):
+                    with self.trainer.profiler.profile("backward"):
                         self.backward(result, optimizer, opt_idx)
 
                     # hook - call this hook only
diff --git a/tests/deprecated_api/test_remove_1-5.py b/tests/deprecated_api/test_remove_1-5.py
index cb1d461414603..479db3a4ec6f9 100644
--- a/tests/deprecated_api/test_remove_1-5.py
+++ b/tests/deprecated_api/test_remove_1-5.py
@@ -19,6 +19,7 @@
 
 from pytorch_lightning import Callback, Trainer
 from pytorch_lightning.loggers import WandbLogger
+from pytorch_lightning.profiler import PyTorchProfiler
 from tests.helpers import BoringModel
 from tests.helpers.utils import no_warning_call
 
@@ -68,3 +69,8 @@ def on_save_checkpoint(self, *args):
     trainer.callbacks = [NewSignature(), ValidSignature1(), ValidSignature2()]
     with no_warning_call(DeprecationWarning):
         trainer.save_checkpoint(filepath)
+
+
+def test_v1_5_0_legacy_profiler_argument():
+    with pytest.deprecated_call(match="renamed to `record_functions` in v1.3"):
+        PyTorchProfiler(profiled_functions=[])
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 667e153a9edd4..976d3ba9dafcc 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -14,12 +14,19 @@
 import logging
 import os
 import time
+from distutils.version import LooseVersion
 from pathlib import Path
 
 import numpy as np
 import pytest
+import torch
 
-from pytorch_lightning.profiler import AdvancedProfiler, SimpleProfiler
+from pytorch_lightning import Trainer
+from pytorch_lightning.loggers import TensorBoardLogger
+from pytorch_lightning.profiler import AdvancedProfiler, PyTorchProfiler, SimpleProfiler
+from pytorch_lightning.utilities.exceptions import MisconfigurationException
+from tests.helpers import BoringModel
+from tests.helpers.runif import RunIf
 
 PROFILER_OVERHEAD_MAX_TOLERANCE = 0.0005
 
@@ -44,12 +51,6 @@ def simple_profiler():
     return profiler
 
 
-@pytest.fixture
-def advanced_profiler(tmpdir):
-    profiler = AdvancedProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"))
-    return profiler
-
-
 @pytest.mark.parametrize(["action", "expected"], [
     pytest.param("a", [3, 1]),
     pytest.param("b", [2]),
@@ -116,6 +117,12 @@ def test_simple_profiler_value_errors(simple_profiler):
     simple_profiler.stop(action)
 
 
+@pytest.fixture
+def advanced_profiler(tmpdir):
+    profiler = AdvancedProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"))
+    return profiler
+
+
 @pytest.mark.parametrize(["action", "expected"], [
     pytest.param("a", [3, 1]),
     pytest.param("b", [2]),
@@ -187,3 +194,144 @@ def test_advanced_profiler_value_errors(advanced_profiler):
 
     advanced_profiler.start(action)
     advanced_profiler.stop(action)
+
+
+@pytest.fixture
+def pytorch_profiler(tmpdir):
+    profiler = PyTorchProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"), local_rank=0)
+    return profiler
+
+
+def test_pytorch_profiler_describe(pytorch_profiler):
+    """Ensure the profiler won't fail when reporting the summary."""
+    with pytorch_profiler.profile("test_step"):
+        pass
+
+    # log to stdout and print to file
+    pytorch_profiler.describe()
+    data = Path(pytorch_profiler.output_fname).read_text()
+    assert len(data) > 0
+
+
+def test_pytorch_profiler_value_errors(pytorch_profiler):
+    """Ensure errors are raised where expected."""
+
+    action = "test_step"
+    with pytest.raises(ValueError):
+        pytorch_profiler.stop(action)
+
+    pytorch_profiler.start(action)
+    pytorch_profiler.stop(action)
+
+    with pytest.raises(MisconfigurationException, match="profiled_functions` and `PyTorchProfiler.record"):
+        PyTorchProfiler(profiled_functions=[], record_functions=[])
+
+
+@RunIf(min_gpus=2, special=True)
+def test_pytorch_profiler_trainer_ddp(tmpdir):
+    """Ensure that the profiler can be given to the training and default step are properly recorded. """
+
+    output_filename = os.path.join(tmpdir, "profiler.txt")
+
+    profiler = PyTorchProfiler(output_filename=output_filename)
+
+    model = BoringModel()
+    trainer = Trainer(
+        max_epochs=1,
+        default_root_dir=tmpdir,
+        limit_train_batches=6,
+        limit_val_batches=6,
+        profiler=profiler,
+        accelerator="ddp",
+        gpus=2,
+        logger=TensorBoardLogger(tmpdir)
+    )
+    trainer.fit(model)
+
+    assert len(profiler.summary()) > 0
+    profiler.describe()
+    data = Path(profiler.output_fname).read_text()
+    assert len(data) > 0
+
+
+@pytest.mark.parametrize("use_output_filename", [True])
+def test_pytorch_profiler_trainer(tmpdir, use_output_filename):
+    """Ensure that the profiler can be given to the training and default step are properly recorded. """
+
+    if use_output_filename:
+        output_filename = os.path.join(tmpdir, "profiler.txt")
+    else:
+        output_filename = None
+
+    profiler = PyTorchProfiler(output_filename=output_filename)
+
+    model = BoringModel()
+    trainer = Trainer(
+        default_root_dir=tmpdir,
+        max_epochs=1,
+        limit_train_batches=1,
+        limit_val_batches=1,
+        profiler=profiler,
+    )
+    trainer.fit(model)
+
+    enabled = use_output_filename or not use_output_filename and profiler.local_rank == 0
+
+    if enabled:
+        assert len(profiler.summary()) > 0
+        expected = {'validation_step', 'training_step_and_backward', 'training_step', 'backward'}
+        assert set(profiler.profiled_actions.keys()) == expected
+    else:
+        assert profiler.summary() is None
+        assert set(profiler.profiled_actions.keys()) == set()
+
+    if use_output_filename:
+        profiler.describe()
+        data = Path(profiler.output_fname).read_text()
+        assert len(data) > 0
+
+
+def test_pytorch_profiler_nested(tmpdir):
+    """Ensure that the profiler handles nested context"""
+
+    pytorch_profiler = PyTorchProfiler(
+        record_functions=["a", "b", "c"],
+        use_cuda=torch.cuda.is_available(),
+        output_filename=os.path.join(tmpdir, "profiler.txt")
+    )
+
+    with pytorch_profiler.profile("a"):
+        a = torch.ones(42)
+        with pytorch_profiler.profile("b"):
+            b = torch.zeros(42)
+        with pytorch_profiler.profile("c"):
+            _ = a + b
+
+    pa = pytorch_profiler.profiled_actions
+
+    # From PyTorch 1.8.0, less operation are being traced.
+    if LooseVersion(torch.__version__) >= LooseVersion("1.8.0"):
+        expected_ = {
+            'a': ['ones', 'empty', 'fill_', 'zeros', 'empty', 'zero_', 'add'],
+            'b': ['zeros', 'empty', 'zero_'],
+            'c': ['add'],
+        }
+    # From PyTorch 1.6.0, more operation are being traced.
+    elif LooseVersion(torch.__version__) >= LooseVersion("1.6.0"):
+        expected_ = {
+            'a': ['ones', 'empty', 'fill_', 'zeros', 'empty', 'zero_', 'fill_', 'add', 'empty'],
+            'b': ['zeros', 'empty', 'zero_', 'fill_'],
+            'c': ['add', 'empty'],
+        }
+    else:
+        expected_ = {
+            'a': ['add'],
+            'b': [],
+            'c': ['add'],
+        }
+
+    for n in ('a', 'b', 'c'):
+        pa[n] = [e.name for e in pa[n]]
+        if LooseVersion(torch.__version__) >= LooseVersion("1.7.1"):
+            pa[n] = [e.replace("aten::", "") for e in pa[n]]
+        assert pa[n] == expected_[n]
diff --git a/tests/trainer/test_trainer.py b/tests/trainer/test_trainer.py
index 867afc5eab886..63143cbacb455 100644
--- a/tests/trainer/test_trainer.py
+++ b/tests/trainer/test_trainer.py
@@ -17,7 +17,6 @@
 import sys
 from argparse import Namespace
 from copy import deepcopy
-from distutils.version import LooseVersion
 from pathlib import Path
 from unittest.mock import ANY, call, patch
 
@@ -43,12 +42,6 @@
 from tests.helpers.runif import RunIf
 
 
-@pytest.fixture
-def pytorch_profiler(tmpdir):
-    profiler = PyTorchProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"), local_rank=0)
-    return profiler
-
-
 @pytest.mark.parametrize("url_ckpt", [True, False])
 def test_no_val_module(monkeypatch, tmpdir, tmpdir_server, url_ckpt):
     """Tests use case where trainer saves the model, and user loads it from tags independently."""
@@ -1448,108 +1441,6 @@ def test_trainer_predict_ddp_cpu(tmpdir):
     predict(tmpdir, "ddp_cpu", 0, 2)
 
 
-def test_pytorch_profiler_describe(pytorch_profiler):
-    """Ensure the profiler won't fail when reporting the summary."""
-    with pytorch_profiler.profile("test_step"):
-        pass
-
-    # log to stdout and print to file
-    pytorch_profiler.describe()
-    data = Path(pytorch_profiler.output_fname).read_text()
-    assert len(data) > 0
-
-
-def test_pytorch_profiler_value_errors(pytorch_profiler):
-    """Ensure errors are raised where expected."""
-
-    action = "test_step"
-    with pytest.raises(ValueError):
-        pytorch_profiler.stop(action)
-
-    pytorch_profiler.start(action)
-    pytorch_profiler.stop(action)
-
-
-@RunIf(min_gpus=2, special=True)
-@pytest.mark.parametrize("use_output_filename", [False, True])
-def test_pytorch_profiler_trainer_ddp(tmpdir, use_output_filename):
-    """Ensure that the profiler can be given to the training and default step are properly recorded. """
-
-    if use_output_filename:
-        output_filename = os.path.join(tmpdir, "profiler.txt")
-    else:
-        output_filename = None
-
-    profiler = PyTorchProfiler(output_filename=output_filename)
-
-    model = BoringModel()
-    trainer = Trainer(
-        fast_dev_run=True,
-        profiler=profiler,
-        accelerator="ddp",
-        gpus=2,
-    )
-    trainer.fit(model)
-
-    enabled = use_output_filename or not use_output_filename and profiler.local_rank == 0
-
-    if enabled:
-        assert len(profiler.summary()) > 0
-        assert set(profiler.profiled_actions.keys()) == {'training_step_and_backward', 'validation_step'}
-    else:
-        assert profiler.summary() is None
-        assert set(profiler.profiled_actions.keys()) == set()
-
-    if use_output_filename:
-        profiler.describe()
-        data = Path(profiler.output_fname).read_text()
-        assert len(data) > 0
-
-
-def test_pytorch_profiler_nested(tmpdir):
-    """Ensure that the profiler handles nested context"""
-
-    pytorch_profiler = PyTorchProfiler(
-        profiled_functions=["a", "b", "c"], use_cuda=False, output_filename=os.path.join(tmpdir, "profiler.txt")
-    )
-
-    with pytorch_profiler.profile("a"):
-        a = torch.ones(42)
-        with pytorch_profiler.profile("b"):
-            b = torch.zeros(42)
-        with pytorch_profiler.profile("c"):
-            _ = a + b
-
-    pa = pytorch_profiler.profiled_actions
-
-    # From PyTorch 1.8.0, less operation are being traced.
-    if LooseVersion(torch.__version__) >= LooseVersion("1.8.0"):
-        expected_ = {
-            'a': ['ones', 'empty', 'fill_', 'zeros', 'empty', 'zero_', 'add'],
-            'b': ['zeros', 'empty', 'zero_'],
-            'c': ['add'],
-        }
-    # From PyTorch 1.6.0, more operation are being traced.
-    elif LooseVersion(torch.__version__) >= LooseVersion("1.6.0"):
-        expected_ = {
-            'a': ['ones', 'empty', 'fill_', 'zeros', 'empty', 'zero_', 'fill_', 'add', 'empty'],
-            'b': ['zeros', 'empty', 'zero_', 'fill_'],
-            'c': ['add', 'empty'],
-        }
-    else:
-        expected_ = {
-            'a': ['add'],
-            'b': [],
-            'c': ['add'],
-        }
-
-    for n in ('a', 'b', 'c'):
-        pa[n] = [e.name for e in pa[n]]
-        if LooseVersion(torch.__version__) >= LooseVersion("1.7.1"):
-            pa[n] = [e.replace("aten::", "") for e in pa[n]]
-        assert pa[n] == expected_[n]
-
-
 @pytest.mark.parametrize(
     ["limit_train_batches", "global_step", "num_training_batches", "current_epoch", "should_train"],
     [(0.2, 0, 0, 0, False), (0.5, 10, 2, 4, True)],

From b66f1f64a25b3e17f258097d004205329573b5fc Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Fri, 5 Mar 2021 19:35:45 +0100
Subject: [PATCH 02/87] Update PassThrough

---
 pytorch_lightning/profiler/profilers.py | 4 ----
 1 file changed, 4 deletions(-)

diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index 644aa0e6f6255..fd4bcf8732932 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -132,10 +132,6 @@ class PassThroughProfiler(BaseProfiler):
     This class should be used when you don't want the (small) overhead of profiling.
     The Trainer uses this class by default.
     """
-
-    def __init__(self):
-        super().__init__(output_streams=None)
-
     def start(self, action_name: str) -> None:
         pass
 

From d388d80941eb4ebe65f694bf7aab60a58b47a95b Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Sat, 6 Mar 2021 14:42:05 +0100
Subject: [PATCH 03/87] WIP - This is broken and will change

---
 pytorch_lightning/profiler/pytorch.py | 190 +++++++++++++-------------
 tests/test_profiler.py                |  16 +--
 2 files changed, 105 insertions(+), 101 deletions(-)

diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index ed973501b3247..98ab37e02f915 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -15,10 +15,10 @@
 import inspect
 import logging
 import os
-from typing import Dict, List, Optional, Union
+from typing import List, Optional, Union, Type, Any, Tuple, Dict
 
 import torch
-from torch.autograd.profiler import EventList, FunctionEvent
+from torch.autograd.profiler import record_function, EventList, parse_event_records
 
 from pytorch_lightning.profiler.profilers import BaseProfiler
 from pytorch_lightning.utilities import rank_zero_only
@@ -27,6 +27,8 @@
 
 log = logging.getLogger(__name__)
 
+_PROFILER = Union[torch.autograd.profiler.profile, torch.cuda.profiler.profile, torch.autograd.profiler.emit_nvtx]
+
 
 class PyTorchProfiler(BaseProfiler):
 
@@ -46,13 +48,7 @@ class PyTorchProfiler(BaseProfiler):
     def __init__(
         self,
         output_filename: Optional[str] = None,
-        enabled: bool = True,
-        use_cpu: bool = True,
-        use_cuda: bool = False,
-        record_shapes: bool = False,
-        profile_memory: bool = False,
         group_by_input_shapes: bool = False,
-        with_stack: bool = False,
         emit_nvtx: bool = False,
         export_to_chrome: bool = False,
         path_to_export_trace: Optional[str] = None,
@@ -61,6 +57,7 @@ def __init__(
         record_functions: Optional[List[str]] = None,
         local_rank: Optional[int] = None,
         profiled_functions: Optional[List[str]] = None,
+        **profiler_kwargs: Any,
     ) -> None:
         """
         This profiler uses PyTorch's Autograd Profiler and lets you inspect the cost of
@@ -72,21 +69,8 @@ def __init__(
                 each rank will stream the profiled operation to their own file
                 with the extension ``_{rank}.txt``
 
-            enabled: Setting this to False makes this context manager a no-op.
-
-            use_cpu: record events on the CPU
-
-            use_cuda: Enables timing of CUDA events as well using the cudaEvent API.
-                Adds approximately 4us of overhead to each tensor operation.
-
-            record_shapes: If shapes recording is set, information about input dimensions will be collected.
-
-            profile_memory: Whether to report memory usage
-
             group_by_input_shapes: Include operator input shapes and group calls by shape.
 
-            with_stack: record source information (file and line number) for the ops
-
             emit_nvtx: Context manager that makes every autograd operation emit an NVTX range
                 Run::
 
@@ -106,7 +90,11 @@ def __init__(
             row_limit: Limit the number of rows in a table, ``0`` is a special value that
                 removes the limit completely.
 
-            sort_by_key: Keys to sort out profiled table.
+            sort_by_key: Attribute used to sort entries. By default
+                they are printed in the same order as they were registered.
+                Valid keys include: ``cpu_time``, ``cuda_time``, ``cpu_time_total``,
+                ``cuda_time_total``, ``cpu_memory_usage``, ``cuda_memory_usage``,
+                ``self_cpu_memory_usage``, ``self_cuda_memory_usage``, ``count``.
 
             record_functions: list of profiled functions which will create a context manager on.
                 Any other will be pass through.
@@ -114,6 +102,8 @@ def __init__(
             local_rank: When running in distributed setting, local_rank is used for each process
                 to write to their own file if `output_fname` is provided.
 
+            profiler_kwargs: Keyword arguments for the PyTorch profiler. This depends on your PyTorch version
+
         Raises:
             MisconfigurationException:
                 If arg ``sort_by_key`` is not present in ``AVAILABLE_SORT_KEYS``, or
@@ -127,19 +117,14 @@ def __init__(
         record_functions = self.__deprecation_check(profiled_functions, record_functions)
 
         self.output_fname = output_filename
-        self.enabled = enabled
         self.record_functions = record_functions or self.RECORD_FUNCTIONS
-        self.use_cpu = use_cpu
-        self.use_cuda = use_cuda
-        self.record_shapes = record_shapes
-        self.profile_memory = profile_memory
-        self.sort_by_key = sort_by_key or ("cuda_time_total" if self.use_cuda else "cpu_time_total")
-        self.with_stack = with_stack
-        self.group_by_input_shapes = group_by_input_shapes and record_shapes
+        self.sort_by_key = sort_by_key or f"{'cuda' if profiler_kwargs.get('use_cuda', False) else 'cpu'}_time_total"
+        self.group_by_input_shapes = group_by_input_shapes and profiler_kwargs.get("record_shapes", False)
         self.row_limit = row_limit
         self.emit_nvtx = emit_nvtx
         self.export_to_chrome = export_to_chrome
         self.path_to_export_trace = path_to_export_trace
+        self.profiler_kwargs = profiler_kwargs
 
         if self.export_to_chrome and self.path_to_export_trace is None:
             rank_zero_warn(
@@ -152,15 +137,17 @@ def __init__(
                 f"Found sort_by_key: {self.sort_by_key}. Should be within {self.AVAILABLE_SORT_KEYS}. "
             )
 
-        self.profiled_actions: Dict[str, Union[FunctionEvent, EventList]] = {}
-        self.context_names = {}
-        self.running_stack = []
-        self.profiler = None
+        self.stack: List[Tuple[str, record_function]] = []
+        self.profiler: Optional[_PROFILER] = None
+        self.function_events: Dict[str, EventList] = {}
 
         super().__init__(local_rank=local_rank)
 
-    def __deprecation_check(self, profiled_functions: Optional[List[str]],
-                            record_functions: Optional[List[str]]) -> Optional[List[str]]:
+    def __deprecation_check(
+        self,
+        profiled_functions: Optional[List[str]],
+        record_functions: Optional[List[str]]
+    ) -> Optional[List[str]]:
         if profiled_functions is not None:
             rank_zero_warn(
                 "`PyTorchProfiler.profiled_functions` has been renamed to"
@@ -197,82 +184,101 @@ def start(self, action_name: str) -> None:
         if action_name not in self.record_functions:
             return
 
-        if len(self.running_stack) > 0:
-            self._stop()
-
-        self.running_stack.append(action_name)
+        if self.profiler is None:
+            self._create_profilers()
 
-        self.context_names[action_name] = "/".join(self.running_stack)
+            self.profiler.__enter__()
+            if self._parent_profiler is not None:
+                self._parent_profiler.__enter__()
 
-        self._start()
+        recording = record_function(action_name)
+        self.stack.append((action_name, recording))
+        recording.__enter__()
 
-    def _start(self) -> None:
+    def _create_profilers(self) -> None:
         if self.emit_nvtx:
-            self._create_profiler(torch.cuda.profiler.profile, enter=False)
-            self._create_profiler(torch.autograd.profiler.emit_nvtx)
+            self._parent_profiler = self._create_profiler(torch.cuda.profiler.profile)
+            self.profiler = self._create_profiler(torch.autograd.profiler.emit_nvtx)
         else:
-            self._create_profiler(torch.autograd.profiler.profile)
+            self._parent_profiler = None
+            self.profiler = self._create_profiler(torch.autograd.profiler.profile)
 
-    def _create_profiler(self, profiler, enter=True) -> None:
-        init_args = inspect.signature(profiler.__init__).parameters
-        profiler_args = {k: v for k, v in vars(self).items() if k in init_args}
-        pr = profiler(**profiler_args)
-        if enter:
-            pr = pr.__enter__()
-        self.profiler = pr
+    def _create_profiler(self, profiler: Type[_PROFILER]) -> _PROFILER:
+        init_parameters = inspect.signature(profiler.__init__).parameters
+        kwargs = {k: v for k, v in self.profiler_kwargs.items() if k in init_parameters}
+        return profiler(**kwargs)
 
-    def _stop(self) -> None:
-        if self.profiler is None:
+    def stop(self, action_name: str) -> None:
+        if self.profiler is None or action_name not in self.record_functions:
             return
 
-        self.profiler.__exit__(None, None, None)
+        if not self.stack or self.stack[-1][0] != action_name:
+            raise ValueError(f"Attempting to stop recording an action ({action_name}) which was never started.")
 
-        events: EventList = self.profiler.function_events
-        if events is not None:
-            for name in self.running_stack:
-                if name not in self.profiled_actions:
-                    self.profiled_actions[name] = events
-                else:
-                    self.profiled_actions[name] += events
+        action_name, recording = self.stack.pop()
+        recording.__exit__(None, None, None)
 
-    def stop(self, action_name: str) -> None:
-        if action_name not in self.record_functions:
-            return
+        self.function_events[action_name] = self.thing()
+        self.profiler.function_events = None
 
-        if len(self.running_stack) == 0 or self.running_stack[-1] != action_name:
-            raise ValueError(f"Attempting to stop recording an action ({action_name}) which was never started.")
+        if not self.stack:
+            self.profiler.__exit__(None, None, None)
+            if self._parent_profiler is not None:
+                self._parent_profiler.__exit__(None, None, None)
+
+    def thing(self):
+        """TODO: Adapted from ..."""
+        profiler = self.profiler
+        kind = torch.autograd.ProfilerState.CUDA if profiler.use_cuda else torch.autograd.ProfilerState.CPU
+        config = torch.autograd.ProfilerConfig(
+            kind,
+            profiler.record_shapes,
+            profiler.profile_memory,
+            profiler.with_stack
+        )
 
-        self._stop()
+        records = torch.autograd._disable_profiler()
 
-        self.profiler = None
-        self.running_stack.pop()
-        # restore running profiler
-        if len(self.running_stack) > 0:
-            self._start()
+        function_events = EventList(
+            parse_event_records(records),
+            use_cuda=profiler.use_cuda,
+            profile_memory=profiler.profile_memory
+        )
+        if profiler.with_stack:
+            function_events.set_backward_stacktraces()
+
+        torch.autograd._enable_profiler(config)
+
+        return function_events
 
     def summary(self) -> str:
-        if not self.enabled or self.emit_nvtx:
+        if not self.profiler_kwargs.get("enabled", True) or self.emit_nvtx:
             return ""
 
         local_rank = 0 if self.local_rank is None else self.local_rank
         recorded_stats = {}
-        for action_name, function_events in self.profiled_actions.items():
-
-            # next line is a workaround for a pytorch issue (fixed on master, still present
-            # on 1.7). Without it the code fails with `AssertionError: There is already a CPU
-            # parent event for detach`
-            function_events.populate_cpu_children = lambda: None
-
-            if self.export_to_chrome:
-                filename = f"{action_name}_{local_rank}_trace.json"
-                path_to_trace = (
-                    filename
-                    if self.path_to_export_trace is None else os.path.join(self.path_to_export_trace, filename)
-                )
-                function_events.export_chrome_trace(path_to_trace)
+        function_events = self.profiler.function_events
+
+        # next line is a workaround for a pytorch issue (fixed on master, still present
+        # on 1.7). Without it the code fails with `AssertionError: There is already a CPU
+        # parent event for detach`
+        function_events.populate_cpu_children = lambda: None
+
+        if self.export_to_chrome:
+            filename = f"{function_events.name}_{local_rank}_trace.json"
+            path_to_trace = (
+                filename
+                if self.path_to_export_trace is None else os.path.join(self.path_to_export_trace, filename)
+            )
+            function_events.export_chrome_trace(path_to_trace)
 
-            data = function_events.key_averages(group_by_input_shapes=self.group_by_input_shapes)
-            table = data.table(sort_by=self.sort_by_key, row_limit=self.row_limit)
-            recorded_stats[action_name] = table
+        data = function_events.key_averages(group_by_input_shapes=self.group_by_input_shapes)
+        table = data.table(sort_by=self.sort_by_key, row_limit=self.row_limit)
+        recorded_stats[action_name] = table
 
         return self.stats_to_str(recorded_stats)
+
+    def __del__(self) -> None:
+        super().__del__()
+        self.profiler.__exit__(None, None, None)
+        self._parent_profiler.__exit__(None, None, None)
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 976d3ba9dafcc..51ea837055d0e 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -307,31 +307,29 @@ def test_pytorch_profiler_nested(tmpdir):
         with pytorch_profiler.profile("c"):
             _ = a + b
 
-    pa = pytorch_profiler.profiled_actions
+    actual = {k: [e.name for e in events] for k, events in pytorch_profiler.function_events.items()}
+    if LooseVersion(torch.__version__) >= LooseVersion("1.7.1"):
+        actual = {k: [e.replace("aten::", "") for e in events] for k, events in actual.items()}
 
     # From PyTorch 1.8.0, less operation are being traced.
     if LooseVersion(torch.__version__) >= LooseVersion("1.8.0"):
-        expected_ = {
+        expected = {
             'a': ['ones', 'empty', 'fill_', 'zeros', 'empty', 'zero_', 'add'],
             'b': ['zeros', 'empty', 'zero_'],
             'c': ['add'],
         }
     # From PyTorch 1.6.0, more operation are being traced.
     elif LooseVersion(torch.__version__) >= LooseVersion("1.6.0"):
-        expected_ = {
+        expected = {
             'a': ['ones', 'empty', 'fill_', 'zeros', 'empty', 'zero_', 'fill_', 'add', 'empty'],
             'b': ['zeros', 'empty', 'zero_', 'fill_'],
             'c': ['add', 'empty'],
         }
     else:
-        expected_ = {
+        expected = {
             'a': ['add'],
             'b': [],
             'c': ['add'],
         }
 
-    for n in ('a', 'b', 'c'):
-        pa[n] = [e.name for e in pa[n]]
-        if LooseVersion(torch.__version__) >= LooseVersion("1.7.1"):
-            pa[n] = [e.replace("aten::", "") for e in pa[n]]
-        assert pa[n] == expected_[n]
+    assert actual == expected

From 93aa073e44706a29261286f95ad57b25ee8d9345 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Carlos=20Mochol=C3=AD?= <carlossmocholi@gmail.com>
Date: Tue, 9 Mar 2021 15:29:58 +0100
Subject: [PATCH 04/87] Update pytorch_lightning/profiler/pytorch.py

Co-authored-by: thomas chaton <thomas@grid.ai>
---
 pytorch_lightning/profiler/pytorch.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index 98ab37e02f915..a36b69579d122 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -165,7 +165,7 @@ def __deprecation_check(
     def on_train_start(self, local_rank: Optional[int] = None, log_dir: Optional[str] = None) -> None:
         super().on_train_start(local_rank=local_rank, log_dir=log_dir)
 
-        # if the user didn't `path_to_export_trace`,
+        # if the user didn't provide `path_to_export_trace`,
         # set it as TensorBoardLogger log_dir if exists
         if self.path_to_export_trace is None:
             self.path_to_export_trace = log_dir

From 0f8b6ef1d7d071dff14dfb5670e3bccb0cb0438e Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Thu, 18 Mar 2021 19:45:54 +0000
Subject: [PATCH 05/87] resolve tests

---
 pytorch_lightning/profiler/pytorch.py      | 138 ++++++++-------------
 pytorch_lightning/trainer/training_loop.py |   2 +
 pytorch_lightning/utilities/imports.py     |   1 +
 tests/callbacks/test_pruning.py            |   4 +-
 tests/test_profiler.py                     |  50 +++-----
 5 files changed, 79 insertions(+), 116 deletions(-)

diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index a36b69579d122..11fcb00441892 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -15,10 +15,10 @@
 import inspect
 import logging
 import os
-from typing import List, Optional, Union, Type, Any, Tuple, Dict
+from typing import Any, Dict, List, Optional, Type, Union
 
 import torch
-from torch.autograd.profiler import record_function, EventList, parse_event_records
+from torch.autograd.profiler import EventList, record_function
 
 from pytorch_lightning.profiler.profilers import BaseProfiler
 from pytorch_lightning.utilities import rank_zero_only
@@ -44,6 +44,7 @@ class PyTorchProfiler(BaseProfiler):
         "self_cuda_memory_usage",
         "count",
     )
+    ACTION_NAME_START = "on_fit_start"
 
     def __init__(
         self,
@@ -54,9 +55,9 @@ def __init__(
         path_to_export_trace: Optional[str] = None,
         row_limit: int = 20,
         sort_by_key: Optional[str] = None,
-        record_functions: Optional[List[str]] = None,
+        record_functions: List[str] = [],
         local_rank: Optional[int] = None,
-        profiled_functions: Optional[List[str]] = None,
+        profiled_functions: List[str] = [],
         **profiler_kwargs: Any,
     ) -> None:
         """
@@ -117,7 +118,7 @@ def __init__(
         record_functions = self.__deprecation_check(profiled_functions, record_functions)
 
         self.output_fname = output_filename
-        self.record_functions = record_functions or self.RECORD_FUNCTIONS
+        self.record_functions = record_functions + list(self.RECORD_FUNCTIONS)
         self.sort_by_key = sort_by_key or f"{'cuda' if profiler_kwargs.get('use_cuda', False) else 'cpu'}_time_total"
         self.group_by_input_shapes = group_by_input_shapes and profiler_kwargs.get("record_shapes", False)
         self.row_limit = row_limit
@@ -137,24 +138,21 @@ def __init__(
                 f"Found sort_by_key: {self.sort_by_key}. Should be within {self.AVAILABLE_SORT_KEYS}. "
             )
 
-        self.stack: List[Tuple[str, record_function]] = []
+        self.recording_map: Dict[str, record_function] = {}
         self.profiler: Optional[_PROFILER] = None
-        self.function_events: Dict[str, EventList] = {}
+        self.function_events: Optional[EventList] = None
+        self._profiler_instantiated: bool = False
 
         super().__init__(local_rank=local_rank)
 
-    def __deprecation_check(
-        self,
-        profiled_functions: Optional[List[str]],
-        record_functions: Optional[List[str]]
-    ) -> Optional[List[str]]:
+    def __deprecation_check(self, profiled_functions: List[str] = [], record_functions: List[str] = []) -> List[str]:
         if profiled_functions is not None:
             rank_zero_warn(
                 "`PyTorchProfiler.profiled_functions` has been renamed to"
                 " `record_functions` in v1.3 and will be removed in v1.5", DeprecationWarning
             )
-            if record_functions is None:
-                record_functions = profiled_functions
+            if (len(record_functions) == 0 or len(profiled_functions) == 0):
+                record_functions += profiled_functions
             else:
                 raise MisconfigurationException(
                     "You set `PytorchProfiler.profiled_functions` and `PyTorchProfiler.record_functions`."
@@ -181,75 +179,27 @@ def _rank_zero_only_wrap(self) -> None:
         self.describe = rank_zero_only(self.describe)
 
     def start(self, action_name: str) -> None:
-        if action_name not in self.record_functions:
-            return
+        if not self._profiler_instantiated:
 
-        if self.profiler is None:
             self._create_profilers()
 
             self.profiler.__enter__()
             if self._parent_profiler is not None:
                 self._parent_profiler.__enter__()
 
-        recording = record_function(action_name)
-        self.stack.append((action_name, recording))
-        recording.__enter__()
+            self._profiler_instantiated = True
 
-    def _create_profilers(self) -> None:
-        if self.emit_nvtx:
-            self._parent_profiler = self._create_profiler(torch.cuda.profiler.profile)
-            self.profiler = self._create_profiler(torch.autograd.profiler.emit_nvtx)
-        else:
-            self._parent_profiler = None
-            self.profiler = self._create_profiler(torch.autograd.profiler.profile)
-
-    def _create_profiler(self, profiler: Type[_PROFILER]) -> _PROFILER:
-        init_parameters = inspect.signature(profiler.__init__).parameters
-        kwargs = {k: v for k, v in self.profiler_kwargs.items() if k in init_parameters}
-        return profiler(**kwargs)
+        if (
+            action_name in self.record_functions and action_name != self.ACTION_NAME_START
+            and action_name not in self.recording_map
+        ):
+            recording = record_function(action_name)
+            recording.__enter__()
+            self.recording_map[action_name] = recording
 
     def stop(self, action_name: str) -> None:
-        if self.profiler is None or action_name not in self.record_functions:
-            return
-
-        if not self.stack or self.stack[-1][0] != action_name:
-            raise ValueError(f"Attempting to stop recording an action ({action_name}) which was never started.")
-
-        action_name, recording = self.stack.pop()
-        recording.__exit__(None, None, None)
-
-        self.function_events[action_name] = self.thing()
-        self.profiler.function_events = None
-
-        if not self.stack:
-            self.profiler.__exit__(None, None, None)
-            if self._parent_profiler is not None:
-                self._parent_profiler.__exit__(None, None, None)
-
-    def thing(self):
-        """TODO: Adapted from ..."""
-        profiler = self.profiler
-        kind = torch.autograd.ProfilerState.CUDA if profiler.use_cuda else torch.autograd.ProfilerState.CPU
-        config = torch.autograd.ProfilerConfig(
-            kind,
-            profiler.record_shapes,
-            profiler.profile_memory,
-            profiler.with_stack
-        )
-
-        records = torch.autograd._disable_profiler()
-
-        function_events = EventList(
-            parse_event_records(records),
-            use_cuda=profiler.use_cuda,
-            profile_memory=profiler.profile_memory
-        )
-        if profiler.with_stack:
-            function_events.set_backward_stacktraces()
-
-        torch.autograd._enable_profiler(config)
-
-        return function_events
+        if action_name in self.recording_map:
+            self.recording_map[action_name].__exit__(None, None, None)
 
     def summary(self) -> str:
         if not self.profiler_kwargs.get("enabled", True) or self.emit_nvtx:
@@ -257,28 +207,48 @@ def summary(self) -> str:
 
         local_rank = 0 if self.local_rank is None else self.local_rank
         recorded_stats = {}
-        function_events = self.profiler.function_events
+        self.profiler.__exit__(None, None, None)
+        self.function_events = self.profiler.function_events
+        if self._parent_profiler is not None:
+            self._parent_profiler.__exit__(None, None, None)
+            self._parent_profiler = None
+        self.function_events = self.profiler.function_events
+        self.profiler = None
 
         # next line is a workaround for a pytorch issue (fixed on master, still present
         # on 1.7). Without it the code fails with `AssertionError: There is already a CPU
         # parent event for detach`
-        function_events.populate_cpu_children = lambda: None
+        self.function_events.populate_cpu_children = lambda: None
 
         if self.export_to_chrome:
-            filename = f"{function_events.name}_{local_rank}_trace.json"
+            filename = f"{self.function_events.name}_{local_rank}_trace.json"
             path_to_trace = (
-                filename
-                if self.path_to_export_trace is None else os.path.join(self.path_to_export_trace, filename)
+                filename if self.path_to_export_trace is None else os.path.join(self.path_to_export_trace, filename)
             )
-            function_events.export_chrome_trace(path_to_trace)
+            self.function_events.export_chrome_trace(path_to_trace)
 
-        data = function_events.key_averages(group_by_input_shapes=self.group_by_input_shapes)
+        data = self.function_events.key_averages(group_by_input_shapes=self.group_by_input_shapes)
         table = data.table(sort_by=self.sort_by_key, row_limit=self.row_limit)
-        recorded_stats[action_name] = table
+        recorded_stats["records"] = table
 
         return self.stats_to_str(recorded_stats)
 
-    def __del__(self) -> None:
+    def _create_profilers(self) -> None:
+        if self.emit_nvtx:
+            self._parent_profiler = self._create_profiler(torch.cuda.profiler.profile)
+            self.profiler = self._create_profiler(torch.autograd.profiler.emit_nvtx)
+        else:
+            self._parent_profiler = None
+            self.profiler = self._create_profiler(torch.autograd.profiler.profile)
+
+    def _create_profiler(self, profiler: Type[_PROFILER]) -> _PROFILER:
+        init_parameters = inspect.signature(profiler.__init__).parameters
+        kwargs = {k: v for k, v in self.profiler_kwargs.items() if k in init_parameters}
+        return profiler(**kwargs)
+
+    def __del__(self):
+        if self.profiler is not None:
+            self.profiler.__exit__(None, None, None)
+            if self._parent_profiler is not None:
+                self._parent_profiler.__exit__(None, None, None)
         super().__del__()
-        self.profiler.__exit__(None, None, None)
-        self._parent_profiler.__exit__(None, None, None)
diff --git a/pytorch_lightning/trainer/training_loop.py b/pytorch_lightning/trainer/training_loop.py
index 39548b5ed64c5..fde42eee1a49c 100644
--- a/pytorch_lightning/trainer/training_loop.py
+++ b/pytorch_lightning/trainer/training_loop.py
@@ -121,10 +121,12 @@ def setup_fit(self, model, train_dataloader, val_dataloaders, datamodule):
         self.trainer.callback_connector.attach_model_logging_functions(model)
 
     def on_train_end(self):
+        print("before", self._teardown_already_run)
         if self._teardown_already_run:
             return
 
         self._teardown_already_run = True
+        print("after", self._teardown_already_run)
 
         # trigger checkpoint check. need to temporarily decrease the global step to avoid saving duplicates
         # when a checkpoint was saved at the last step
diff --git a/pytorch_lightning/utilities/imports.py b/pytorch_lightning/utilities/imports.py
index 41a13d6c678a0..22b75981edf7f 100644
--- a/pytorch_lightning/utilities/imports.py
+++ b/pytorch_lightning/utilities/imports.py
@@ -54,6 +54,7 @@ def _compare_version(package: str, op, version) -> bool:
 _TORCH_LOWER_EQUAL_1_4 = _compare_version("torch", operator.le, "1.5.0")
 _TORCH_GREATER_EQUAL_1_6 = _compare_version("torch", operator.ge, "1.6.0")
 _TORCH_GREATER_EQUAL_1_7 = _compare_version("torch", operator.ge, "1.7.0")
+_TORCH_GREATER_EQUAL_1_8 = _compare_version("torch", operator.ge, "1.8.0")
 
 _APEX_AVAILABLE = _module_available("apex.amp")
 _BOLTS_AVAILABLE = _module_available('pl_bolts')
diff --git a/tests/callbacks/test_pruning.py b/tests/callbacks/test_pruning.py
index 23b2fcbb52235..0e63fc29d49b1 100644
--- a/tests/callbacks/test_pruning.py
+++ b/tests/callbacks/test_pruning.py
@@ -11,7 +11,6 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-import os
 from collections import OrderedDict
 from logging import INFO
 
@@ -22,7 +21,7 @@
 from torch.nn import Sequential
 
 from pytorch_lightning import seed_everything, Trainer
-from pytorch_lightning.callbacks import ModelPruning, ModelCheckpoint
+from pytorch_lightning.callbacks import ModelCheckpoint, ModelPruning
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from tests.helpers import BoringModel
 from tests.helpers.runif import RunIf
@@ -274,6 +273,7 @@ def test_permanent_when_model_is_saved_multiple_times(tmpdir, caplog):
     seed_everything(0)
 
     class TestPruning(ModelPruning):
+
         def on_save_checkpoint(self, trainer, pl_module, checkpoint):
             super().on_save_checkpoint(trainer, pl_module, checkpoint)
             assert "layer.mlp_3.weight_orig" not in checkpoint["state_dict"]
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 51ea837055d0e..ab3fa3267bd79 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -217,14 +217,11 @@ def test_pytorch_profiler_value_errors(pytorch_profiler):
     """Ensure errors are raised where expected."""
 
     action = "test_step"
-    with pytest.raises(ValueError):
-        pytorch_profiler.stop(action)
-
     pytorch_profiler.start(action)
     pytorch_profiler.stop(action)
 
     with pytest.raises(MisconfigurationException, match="profiled_functions` and `PyTorchProfiler.record"):
-        PyTorchProfiler(profiled_functions=[], record_functions=[])
+        PyTorchProfiler(profiled_functions=["a"], record_functions=["b"])
 
 
 @RunIf(min_gpus=2, special=True)
@@ -248,8 +245,6 @@ def test_pytorch_profiler_trainer_ddp(tmpdir):
     )
     trainer.fit(model)
 
-    assert len(profiler.summary()) > 0
-    profiler.describe()
     data = Path(profiler.output_fname).read_text()
     assert len(data) > 0
 
@@ -278,15 +273,13 @@ def test_pytorch_profiler_trainer(tmpdir, use_output_filename):
     enabled = use_output_filename or not use_output_filename and profiler.local_rank == 0
 
     if enabled:
-        assert len(profiler.summary()) > 0
-        expected = {'validation_step', 'training_step_and_backward', 'training_step', 'backward'}
-        assert set(profiler.profiled_actions.keys()) == expected
+        expected = ('validation_step', 'training_step_and_backward', 'training_step', 'backward')
+        for name in expected:
+            assert len([e for e in profiler.function_events if name == e.name]) > 0
     else:
-        assert profiler.summary() is None
-        assert set(profiler.profiled_actions.keys()) == set()
+        assert profiler.function_events is None
 
     if use_output_filename:
-        profiler.describe()
         data = Path(profiler.output_fname).read_text()
         assert len(data) > 0
 
@@ -307,29 +300,26 @@ def test_pytorch_profiler_nested(tmpdir):
         with pytorch_profiler.profile("c"):
             _ = a + b
 
-    actual = {k: [e.name for e in events] for k, events in pytorch_profiler.function_events.items()}
-    if LooseVersion(torch.__version__) >= LooseVersion("1.7.1"):
-        actual = {k: [e.replace("aten::", "") for e in events] for k, events in actual.items()}
+    pytorch_profiler.describe()
 
-    # From PyTorch 1.8.0, less operation are being traced.
-    if LooseVersion(torch.__version__) >= LooseVersion("1.8.0"):
+    events_name = {e.name for e in pytorch_profiler.function_events}
+
+    if LooseVersion(torch.__version__) >= LooseVersion("1.5.0"):
         expected = {
-            'a': ['ones', 'empty', 'fill_', 'zeros', 'empty', 'zero_', 'add'],
-            'b': ['zeros', 'empty', 'zero_'],
-            'c': ['add'],
+            'signed char', 'add', 'profiler::_record_function_exit', 'bool', 'char', 'profiler::_record_function_enter'
         }
-    # From PyTorch 1.6.0, more operation are being traced.
-    elif LooseVersion(torch.__version__) >= LooseVersion("1.6.0"):
+
+    if LooseVersion(torch.__version__) >= LooseVersion("1.6.0"):
+        expected = {'add', 'zeros', 'ones', 'zero_', 'b', 'fill_', 'c', 'a', 'empty'}
+
+    if LooseVersion(torch.__version__) >= LooseVersion("1.7.0"):
         expected = {
-            'a': ['ones', 'empty', 'fill_', 'zeros', 'empty', 'zero_', 'fill_', 'add', 'empty'],
-            'b': ['zeros', 'empty', 'zero_', 'fill_'],
-            'c': ['add', 'empty'],
+            'aten::zeros', 'aten::add', 'aten::zero_', 'c', 'b', 'a', 'aten::fill_', 'aten::empty', 'aten::ones'
         }
-    else:
+
+    if LooseVersion(torch.__version__) >= LooseVersion("1.8.0"):
         expected = {
-            'a': ['add'],
-            'b': [],
-            'c': ['add'],
+            'aten::ones', 'a', 'aten::add', 'aten::empty', 'aten::zero_', 'b', 'c', 'aten::zeros', 'aten::fill_'
         }
 
-    assert actual == expected
+    assert events_name == expected

From 8a3d3cf16031938986934b0d2552ebdbbf117026 Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Thu, 18 Mar 2021 20:08:21 +0000
Subject: [PATCH 06/87] resolve tests

---
 pytorch_lightning/trainer/training_loop.py | 2 --
 tests/test_profiler.py                     | 7 +++----
 2 files changed, 3 insertions(+), 6 deletions(-)

diff --git a/pytorch_lightning/trainer/training_loop.py b/pytorch_lightning/trainer/training_loop.py
index 8cc68708a1323..43c9829b91dad 100644
--- a/pytorch_lightning/trainer/training_loop.py
+++ b/pytorch_lightning/trainer/training_loop.py
@@ -120,11 +120,9 @@ def setup_fit(self, model, train_dataloader=None, val_dataloaders=None, datamodu
         self.trainer.callback_connector.attach_model_logging_functions(model)
 
     def on_train_end(self):
-        print("before", self._teardown_already_run)
         if self._teardown_already_run:
             return
         self._teardown_already_run = True
-        print("after", self._teardown_already_run)
 
         # trigger checkpoint check. need to temporarily decrease the global step to avoid saving duplicates
         # when a checkpoint was saved at the last step
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 22e0f3e39fc88..1d707f301e688 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -304,10 +304,9 @@ def test_pytorch_profiler_nested(tmpdir):
 
     events_name = {e.name for e in pytorch_profiler.function_events}
 
-    if LooseVersion(torch.__version__) >= LooseVersion("1.5.0"):
-        expected = {
-            'signed char', 'add', 'profiler::_record_function_exit', 'bool', 'char', 'profiler::_record_function_enter'
-        }
+    expected = {
+        'signed char', 'add', 'profiler::_record_function_exit', 'bool', 'char', 'profiler::_record_function_enter'
+    }
 
     if LooseVersion(torch.__version__) >= LooseVersion("1.6.0"):
         expected = {'add', 'zeros', 'ones', 'zero_', 'b', 'fill_', 'c', 'a', 'empty'}

From af865ff6f519617fa9ec73d6a40aa4837b1ce877 Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Thu, 18 Mar 2021 20:26:43 +0000
Subject: [PATCH 07/87] find output

---
 tests/test_profiler.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 1d707f301e688..d41f83401a327 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -321,4 +321,4 @@ def test_pytorch_profiler_nested(tmpdir):
             'aten::ones', 'a', 'aten::add', 'aten::empty', 'aten::zero_', 'b', 'c', 'aten::zeros', 'aten::fill_'
         }
 
-    assert events_name == expected
+    assert events_name == expected, (events_name, torch.__version__, platform.system())

From 6147e6ee3216f02cc7671d0b6c7a5e64423c0f34 Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Fri, 19 Mar 2021 08:55:10 +0000
Subject: [PATCH 08/87] try something

---
 pytorch_lightning/profiler/profilers.py | 2 ++
 pytorch_lightning/profiler/pytorch.py   | 1 -
 2 files changed, 2 insertions(+), 1 deletion(-)

diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index fd4bcf8732932..c4358bfa4870f 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -56,6 +56,7 @@ def __init__(self, local_rank: Optional[int] = None, log_dir: Optional[str] = No
         # the profiler can be used outside of lightning
         # that's why we call `on_train_start` manually
         self.on_train_start(local_rank=local_rank, log_dir=log_dir)
+        self.output_file = None
 
     def on_train_start(self, local_rank: Optional[int] = None, log_dir: Optional[str] = None):
         """
@@ -132,6 +133,7 @@ class PassThroughProfiler(BaseProfiler):
     This class should be used when you don't want the (small) overhead of profiling.
     The Trainer uses this class by default.
     """
+
     def start(self, action_name: str) -> None:
         pass
 
diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index 11fcb00441892..1ebe8be8511c1 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -14,7 +14,6 @@
 """Profiler to check if there are any bottlenecks in your code."""
 import inspect
 import logging
-import os
 from typing import Any, Dict, List, Optional, Type, Union
 
 import torch

From 5053b4fb2704c89d3436b390515008580cc31c10 Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Fri, 19 Mar 2021 09:10:16 +0000
Subject: [PATCH 09/87] update

---
 pytorch_lightning/profiler/profilers.py | 3 +--
 pytorch_lightning/profiler/pytorch.py   | 7 -------
 2 files changed, 1 insertion(+), 9 deletions(-)

diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index c4358bfa4870f..cb0c41244fe9f 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -53,10 +53,10 @@ class BaseProfiler(AbstractProfiler, ABC):
 
     def __init__(self, local_rank: Optional[int] = None, log_dir: Optional[str] = None) -> None:
         self.output_fname = getattr(self, "output_fname", None)
+        self.output_file = None
         # the profiler can be used outside of lightning
         # that's why we call `on_train_start` manually
         self.on_train_start(local_rank=local_rank, log_dir=log_dir)
-        self.output_file = None
 
     def on_train_start(self, local_rank: Optional[int] = None, log_dir: Optional[str] = None):
         """
@@ -68,7 +68,6 @@ def on_train_start(self, local_rank: Optional[int] = None, log_dir: Optional[str
         self.prepare_file()
 
     def prepare_file(self) -> None:
-        self.output_file = None
         if self.output_fname:
             fs = get_filesystem(self.output_fname)
             self.output_file = fs.open(self.output_fname, "w")
diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index 1ebe8be8511c1..b07cebd0301d5 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -244,10 +244,3 @@ def _create_profiler(self, profiler: Type[_PROFILER]) -> _PROFILER:
         init_parameters = inspect.signature(profiler.__init__).parameters
         kwargs = {k: v for k, v in self.profiler_kwargs.items() if k in init_parameters}
         return profiler(**kwargs)
-
-    def __del__(self):
-        if self.profiler is not None:
-            self.profiler.__exit__(None, None, None)
-            if self._parent_profiler is not None:
-                self._parent_profiler.__exit__(None, None, None)
-        super().__del__()

From 3ae2fbf54aa48256a33fb37513fe23a1cd462dc2 Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Fri, 19 Mar 2021 10:14:14 +0000
Subject: [PATCH 10/87] add support for test and predict

---
 pytorch_lightning/profiler/pytorch.py     | 28 ++++++---
 pytorch_lightning/trainer/predict_loop.py |  3 +
 pytorch_lightning/trainer/trainer.py      |  4 +-
 tests/test_profiler.py                    | 76 ++++++++++++++---------
 4 files changed, 72 insertions(+), 39 deletions(-)

diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index b07cebd0301d5..7c64c730f270f 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -14,6 +14,7 @@
 """Profiler to check if there are any bottlenecks in your code."""
 import inspect
 import logging
+import os
 from typing import Any, Dict, List, Optional, Type, Union
 
 import torch
@@ -31,7 +32,9 @@
 
 class PyTorchProfiler(BaseProfiler):
 
-    RECORD_FUNCTIONS = ("training_step_and_backward", "training_step", "backward", "validation_step", "test_step")
+    RECORD_FUNCTIONS = (
+        "training_step_and_backward", "training_step", "backward", "validation_step", "test_step", "predict"
+    )
     AVAILABLE_SORT_KEYS = (
         "cpu_time",
         "cuda_time",
@@ -50,7 +53,7 @@ def __init__(
         output_filename: Optional[str] = None,
         group_by_input_shapes: bool = False,
         emit_nvtx: bool = False,
-        export_to_chrome: bool = False,
+        export_to_chrome: bool = True,
         path_to_export_trace: Optional[str] = None,
         row_limit: int = 20,
         sort_by_key: Optional[str] = None,
@@ -199,6 +202,7 @@ def start(self, action_name: str) -> None:
     def stop(self, action_name: str) -> None:
         if action_name in self.recording_map:
             self.recording_map[action_name].__exit__(None, None, None)
+            del self.recording_map[action_name]
 
     def summary(self) -> str:
         if not self.profiler_kwargs.get("enabled", True) or self.emit_nvtx:
@@ -208,19 +212,14 @@ def summary(self) -> str:
         recorded_stats = {}
         self.profiler.__exit__(None, None, None)
         self.function_events = self.profiler.function_events
+        self.profiler = None
+
         if self._parent_profiler is not None:
             self._parent_profiler.__exit__(None, None, None)
             self._parent_profiler = None
-        self.function_events = self.profiler.function_events
-        self.profiler = None
-
-        # next line is a workaround for a pytorch issue (fixed on master, still present
-        # on 1.7). Without it the code fails with `AssertionError: There is already a CPU
-        # parent event for detach`
-        self.function_events.populate_cpu_children = lambda: None
 
         if self.export_to_chrome:
-            filename = f"{self.function_events.name}_{local_rank}_trace.json"
+            filename = f"{local_rank}_trace.json"
             path_to_trace = (
                 filename if self.path_to_export_trace is None else os.path.join(self.path_to_export_trace, filename)
             )
@@ -244,3 +243,12 @@ def _create_profiler(self, profiler: Type[_PROFILER]) -> _PROFILER:
         init_parameters = inspect.signature(profiler.__init__).parameters
         kwargs = {k: v for k, v in self.profiler_kwargs.items() if k in init_parameters}
         return profiler(**kwargs)
+
+    def __del__(self):
+        if self.profiler is not None:
+            self.profiler.__exit__(None, None, None)
+        if self._parent_profiler is not None:
+            self._parent_profiler.__exit__(None, None, None)
+        for recording in self.recording_map.values():
+            recording.__exit__(None, None, None)
+        super().__del__()
diff --git a/pytorch_lightning/trainer/predict_loop.py b/pytorch_lightning/trainer/predict_loop.py
index 70329b4fdf514..8d99a4db38ce8 100644
--- a/pytorch_lightning/trainer/predict_loop.py
+++ b/pytorch_lightning/trainer/predict_loop.py
@@ -86,6 +86,9 @@ def predict(self, batch, batch_idx, dataloader_idx):
         return
 
     def on_predict_epoch_end(self):
+        if self.trainer.profiler is not None:
+            self.trainer.profiler.describe()
+
         self.trainer._progress_bar_callback.on_predict_end(self.trainer, self.trainer.lightning_module)
 
         results = self._predictions
diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index 44b0e716a90c0..c6fdaa8fc94c1 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -742,6 +742,9 @@ def run_evaluate(self):
         with self.profiler.profile(f"run_{self._running_stage}_evaluation"):
             eval_loop_results, _ = self.run_evaluation()
 
+        if self.profiler is not None:
+            self.profiler.describe()
+
         if len(eval_loop_results) == 0:
             return 1
 
@@ -789,7 +792,6 @@ def run_predict(self):
                 # lightning module methods
                 with self.profiler.profile("predict"):
                     self.predict_loop.predict(batch, batch_idx, dataloader_idx)
-
         results = self.predict_loop.on_predict_epoch_end()
         return results
 
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index d41f83401a327..e5bc4ca244639 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -13,6 +13,7 @@
 # limitations under the License.
 import logging
 import os
+import platform
 import time
 from distutils.version import LooseVersion
 from pathlib import Path
@@ -225,40 +226,28 @@ def test_pytorch_profiler_value_errors(pytorch_profiler):
 
 
 @RunIf(min_gpus=2, special=True)
-def test_pytorch_profiler_trainer_ddp(tmpdir):
+def test_pytorch_profiler_trainer_ddp(tmpdir, pytorch_profiler):
     """Ensure that the profiler can be given to the training and default step are properly recorded. """
 
-    output_filename = os.path.join(tmpdir, "profiler.txt")
-
-    profiler = PyTorchProfiler(output_filename=output_filename)
-
     model = BoringModel()
     trainer = Trainer(
         max_epochs=1,
         default_root_dir=tmpdir,
         limit_train_batches=6,
         limit_val_batches=6,
-        profiler=profiler,
+        profiler=pytorch_profiler,
         accelerator="ddp",
         gpus=2,
         logger=TensorBoardLogger(tmpdir)
     )
     trainer.fit(model)
 
-    data = Path(profiler.output_fname).read_text()
+    data = Path(pytorch_profiler.output_fname).read_text()
     assert len(data) > 0
 
 
-@pytest.mark.parametrize("use_output_filename", [True])
-def test_pytorch_profiler_trainer(tmpdir, use_output_filename):
-    """Ensure that the profiler can be given to the training and default step are properly recorded. """
-
-    if use_output_filename:
-        output_filename = os.path.join(tmpdir, "profiler.txt")
-    else:
-        output_filename = None
-
-    profiler = PyTorchProfiler(output_filename=output_filename)
+def test_pytorch_profiler_trainer_fit(tmpdir, pytorch_profiler):
+    """Ensure that the profiler can be given to the trainer and training, validation steps are properly recorded. """
 
     model = BoringModel()
     trainer = Trainer(
@@ -266,22 +255,53 @@ def test_pytorch_profiler_trainer(tmpdir, use_output_filename):
         max_epochs=1,
         limit_train_batches=1,
         limit_val_batches=1,
-        profiler=profiler,
+        profiler=pytorch_profiler,
     )
     trainer.fit(model)
 
-    enabled = use_output_filename or not use_output_filename and profiler.local_rank == 0
+    expected = ('validation_step', 'training_step_and_backward', 'training_step', 'backward')
+    for name in expected:
+        assert len([e for e in pytorch_profiler.function_events if name == e.name]) > 0
+
+    data = Path(pytorch_profiler.output_fname).read_text()
+    assert len(data) > 0
+
 
-    if enabled:
-        expected = ('validation_step', 'training_step_and_backward', 'training_step', 'backward')
-        for name in expected:
-            assert len([e for e in profiler.function_events if name == e.name]) > 0
-    else:
-        assert profiler.function_events is None
+def test_pytorch_profiler_trainer_test(tmpdir, pytorch_profiler):
+    """Ensure that the profiler can be given to the trainer and test step are properly recorded. """
+
+    model = BoringModel()
+    trainer = Trainer(
+        default_root_dir=tmpdir,
+        max_epochs=1,
+        limit_test_batches=2,
+        profiler=pytorch_profiler,
+    )
+    trainer.test(model)
 
-    if use_output_filename:
-        data = Path(profiler.output_fname).read_text()
-        assert len(data) > 0
+    assert len([e for e in pytorch_profiler.function_events if 'test_step' == e.name]) > 0
+
+    data = Path(pytorch_profiler.output_fname).read_text()
+    assert len(data) > 0
+
+
+def test_pytorch_profiler_trainer_predict(tmpdir, pytorch_profiler):
+    """Ensure that the profiler can be given to the trainer and predict function are properly recorded. """
+
+    model = BoringModel()
+    model.predict_dataloader = model.train_dataloader
+    trainer = Trainer(
+        default_root_dir=tmpdir,
+        max_epochs=1,
+        limit_test_batches=2,
+        profiler=pytorch_profiler,
+    )
+    trainer.predict(model)
+
+    assert len([e for e in pytorch_profiler.function_events if 'predict' == e.name]) > 0
+
+    data = Path(pytorch_profiler.output_fname).read_text()
+    assert len(data) > 0
 
 
 def test_pytorch_profiler_nested(tmpdir):

From 1d7ac88bccffbe0a58cb286be8f0187c9c1c91a6 Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Fri, 19 Mar 2021 11:30:05 +0000
Subject: [PATCH 11/87] update

---
 pytorch_lightning/profiler/pytorch.py         | 69 +++++++++++++++++++
 .../trainer/connectors/profiler_connector.py  |  2 +
 tests/test_profiler.py                        |  2 +
 3 files changed, 73 insertions(+)

diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index 7c64c730f270f..215619cac4539 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -15,6 +15,7 @@
 import inspect
 import logging
 import os
+from functools import partial
 from typing import Any, Dict, List, Optional, Type, Union
 
 import torch
@@ -30,6 +31,60 @@
 _PROFILER = Union[torch.autograd.profiler.profile, torch.cuda.profiler.profile, torch.autograd.profiler.emit_nvtx]
 
 
+class RegisterRecordFunction:
+    """
+    While profiling autograd operations, this class will add label with module name
+    around the forward function.
+    The Lightning PyTorch Profiler will activate this feature automatically.
+    It can be deactivated as follows:
+    Example::
+        from pytorch_lightning.profilers import PyTorchProfiler
+        profiler = PyTorchProfiler(record_module_names=False)
+        Trainer(profiler=profiler)
+    It can be used outside of Lightning as follows:
+    Example::
+        from pytorch_lightning import Trainer, seed_everything
+        with RegisterRecordFunction(model):
+            out = model(batch)
+    """
+
+    def __init__(self, model):
+        self._model = model
+        self._records = {}
+        self.handles = {}
+
+    def _start_recording_forward(self, module, input, module_name: str = None, is_built_in: bool = None):
+        if module_name is not None:
+            record_name = module_name if is_built_in else f"{type(module)}: {module_name}"
+            self._records[record_name] = record_function(record_name).__enter__()
+        return input
+
+    def _stop_recording_forward(self, module, input, result, module_name: str = None, is_built_in: bool = None):
+        if module_name is not None:
+            record_name = module_name if is_built_in else f"{type(module)}: {module_name}"
+            self._records[record_name].__exit__(None, None, None)
+        return result
+
+    def __enter__(self):
+        built_in_modules = dir(torch.nn)
+        for module_name, module in self._model.named_modules():
+            if module_name != '':
+                is_built_in = module in built_in_modules
+                pre_forward_handle = module.register_forward_pre_hook(
+                    partial(self._start_recording_forward, module_name=module_name, is_built_in=is_built_in)
+                )
+                post_forward_handle = module.register_forward_hook(
+                    partial(self._stop_recording_forward, module_name=module_name, is_built_in=is_built_in)
+                )
+
+                self.handles[module_name] = [pre_forward_handle, post_forward_handle]
+
+    def __exit__(self, exc_type: Any, exc_value: Any, traceback: Any):
+        for handles in self.handles.values():
+            for h in handles:
+                h.remove()
+
+
 class PyTorchProfiler(BaseProfiler):
 
     RECORD_FUNCTIONS = (
@@ -60,6 +115,7 @@ def __init__(
         record_functions: List[str] = [],
         local_rank: Optional[int] = None,
         profiled_functions: List[str] = [],
+        record_module_names: bool = True,
         **profiler_kwargs: Any,
     ) -> None:
         """
@@ -107,6 +163,8 @@ def __init__(
 
             profiler_kwargs: Keyword arguments for the PyTorch profiler. This depends on your PyTorch version
 
+            record_module_names: Whether to add module names while recording autograd operation.
+
         Raises:
             MisconfigurationException:
                 If arg ``sort_by_key`` is not present in ``AVAILABLE_SORT_KEYS``, or
@@ -127,6 +185,9 @@ def __init__(
         self.emit_nvtx = emit_nvtx
         self.export_to_chrome = export_to_chrome
         self.path_to_export_trace = path_to_export_trace
+        self.record_module_names = record_module_names
+        self.lightning_module = None  # set by ProfilerConnector
+        self.register = None
         self.profiler_kwargs = profiler_kwargs
 
         if self.export_to_chrome and self.path_to_export_trace is None:
@@ -191,6 +252,10 @@ def start(self, action_name: str) -> None:
 
             self._profiler_instantiated = True
 
+            if self.record_module_names and self.lightning_module is not None:
+                self.register = RegisterRecordFunction(self.lightning_module)
+                self.register.__enter__()
+
         if (
             action_name in self.record_functions and action_name != self.ACTION_NAME_START
             and action_name not in self.recording_map
@@ -213,11 +278,15 @@ def summary(self) -> str:
         self.profiler.__exit__(None, None, None)
         self.function_events = self.profiler.function_events
         self.profiler = None
+        self._profiler_instantiated = False
 
         if self._parent_profiler is not None:
             self._parent_profiler.__exit__(None, None, None)
             self._parent_profiler = None
 
+        if self.register is not None:
+            self.register.__exit__(None, None, None)
+
         if self.export_to_chrome:
             filename = f"{local_rank}_trace.json"
             path_to_trace = (
diff --git a/pytorch_lightning/trainer/connectors/profiler_connector.py b/pytorch_lightning/trainer/connectors/profiler_connector.py
index 7639926424090..231aa884a47df 100644
--- a/pytorch_lightning/trainer/connectors/profiler_connector.py
+++ b/pytorch_lightning/trainer/connectors/profiler_connector.py
@@ -13,6 +13,7 @@
 # limitations under the License
 
 from typing import Union
+from weakref import proxy
 
 from pytorch_lightning.profiler import (
     AdvancedProfiler,
@@ -57,4 +58,5 @@ def on_trainer_init(self, profiler: Union[BaseProfiler, str]):
     def on_train_start(self, trainer):
         if not isinstance(trainer.profiler, PassThroughProfiler):
             local_rank = trainer.local_rank if trainer.world_size > 1 else None
+            self.trainer.profiler.lightning_module = proxy(self.trainer.lightning_module)
             self.trainer.profiler.on_train_start(local_rank=local_rank, log_dir=self.trainer.log_dir)
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index e5bc4ca244639..16f21b793561e 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -25,6 +25,7 @@
 from pytorch_lightning import Trainer
 from pytorch_lightning.loggers import TensorBoardLogger
 from pytorch_lightning.profiler import AdvancedProfiler, PyTorchProfiler, SimpleProfiler
+from pytorch_lightning.profiler.pytorch import RegisterRecordFunction
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from tests.helpers import BoringModel
 from tests.helpers.runif import RunIf
@@ -265,6 +266,7 @@ def test_pytorch_profiler_trainer_fit(tmpdir, pytorch_profiler):
 
     data = Path(pytorch_profiler.output_fname).read_text()
     assert len(data) > 0
+    print(tmpdir)
 
 
 def test_pytorch_profiler_trainer_test(tmpdir, pytorch_profiler):

From 64f8a58249bd05c2e4fb207c0a1ab75edf184213 Mon Sep 17 00:00:00 2001
From: thomas chaton <thomas@grid.ai>
Date: Fri, 19 Mar 2021 11:34:25 +0000
Subject: [PATCH 12/87] update

---
 tests/special_tests.sh |  2 +-
 tests/test_profiler.py | 16 ++++++++++++++++
 2 files changed, 17 insertions(+), 1 deletion(-)

diff --git a/tests/special_tests.sh b/tests/special_tests.sh
index 43658721e9226..e5c6e313bb6d8 100644
--- a/tests/special_tests.sh
+++ b/tests/special_tests.sh
@@ -33,4 +33,4 @@ python ${DEFAULTS} tests/models/test_hooks.py::test_transfer_batch_hook_ddp
 python ${DEFAULTS} tests/trainer/test_data_loading.py::test_replace_distrubuted_sampler_custom_dataloader_custom_batch_sampler
 python ${DEFAULTS} tests/trainer/optimization/test_manual_optimization.py::test_step_with_optimizer_closure_with_different_frequencies_ddp_with_toggle_model
 python ${DEFAULTS} tests/checkpointing/test_checkpoint_callback_frequency.py::test_top_k_ddp
-nvprof --profile-from-start off -o trace_name.prof -- python ${DEFAULTS} tests/trainer/test_trainer.py::test_pytorch_profiler_nested_emit_nvtx
+nvprof --profile-from-start off -o trace_name.prof -- python ${DEFAULTS} tests/test_profiler.py::test_pytorch_profiler_nested_emit_nvtx
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 16f21b793561e..36fc8b9741771 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -306,6 +306,22 @@ def test_pytorch_profiler_trainer_predict(tmpdir, pytorch_profiler):
     assert len(data) > 0
 
 
+@RunIf(min_gpus=1, special=True)
+def test_pytorch_profiler_nested_emit_nvtx(tmpdir):
+    """
+    This test check emit_nvtx is correctly supported
+    """
+    profiler = PyTorchProfiler(use_cuda=True, emit_nvtx=True)
+
+    model = BoringModel()
+    trainer = Trainer(
+        fast_dev_run=True,
+        profiler=profiler,
+        gpus=1,
+    )
+    trainer.fit(model)
+
+
 def test_pytorch_profiler_nested(tmpdir):
     """Ensure that the profiler handles nested context"""
 

From 655ff46a4983aa58d44c7efebb121ccc196ef2b7 Mon Sep 17 00:00:00 2001
From: thomas chaton <thomas@grid.ai>
Date: Fri, 19 Mar 2021 11:36:04 +0000
Subject: [PATCH 13/87] use getattr

---
 pytorch_lightning/profiler/profilers.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index cb0c41244fe9f..eeb20c112887b 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -123,7 +123,7 @@ def stats_to_str(self, stats: dict) -> str:
 
     def __del__(self) -> None:
         """Close profiler's stream."""
-        if self.output_file:
+        if getattr(self, "output_file") is not None:
             self.output_file.close()
 
 

From 3f5c4d67d6d4ccc133c033e3e0317636cc4424cf Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Fri, 19 Mar 2021 11:51:11 +0000
Subject: [PATCH 14/87] test

---
 pytorch_lightning/profiler/profilers.py | 4 +++-
 tests/test_profiler.py                  | 1 -
 2 files changed, 3 insertions(+), 2 deletions(-)

diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index eeb20c112887b..828d00da70dc2 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -123,8 +123,10 @@ def stats_to_str(self, stats: dict) -> str:
 
     def __del__(self) -> None:
         """Close profiler's stream."""
-        if getattr(self, "output_file") is not None:
+        try:
             self.output_file.close()
+        except AttributeError:
+            pass
 
 
 class PassThroughProfiler(BaseProfiler):
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 36fc8b9741771..f3750aded0356 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -25,7 +25,6 @@
 from pytorch_lightning import Trainer
 from pytorch_lightning.loggers import TensorBoardLogger
 from pytorch_lightning.profiler import AdvancedProfiler, PyTorchProfiler, SimpleProfiler
-from pytorch_lightning.profiler.pytorch import RegisterRecordFunction
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from tests.helpers import BoringModel
 from tests.helpers.runif import RunIf

From ced0d66ea5883f83e2c938051c97a45f43ba7424 Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Fri, 19 Mar 2021 12:19:09 +0000
Subject: [PATCH 15/87] test

---
 0_trace.json                                          |  1 +
 pytorch_lightning/profiler/pytorch.py                 | 11 ++---------
 .../trainer/connectors/profiler_connector.py          |  2 ++
 tests/test_profiler.py                                |  3 ++-
 4 files changed, 7 insertions(+), 10 deletions(-)
 create mode 100644 0_trace.json

diff --git a/0_trace.json b/0_trace.json
new file mode 100644
index 0000000000000..9946c108fe5c7
--- /dev/null
+++ b/0_trace.json
@@ -0,0 +1 @@
+[{"name": "profiler::_record_function_enter", "ph": "X", "ts": 18.0, "dur": 4.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_enter", "ph": "X", "ts": 18.0, "dur": 4.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_enter", "ph": "X", "ts": 18.0, "dur": 4.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "signed char", "ph": "X", "ts": 22.0, "dur": 178.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "signed char", "ph": "X", "ts": 23.0, "dur": 177.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "signed char", "ph": "X", "ts": 23.0, "dur": 177.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_enter", "ph": "X", "ts": 108.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_enter", "ph": "X", "ts": 108.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_enter", "ph": "X", "ts": 108.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "bool", "ph": "X", "ts": 110.0, "dur": 20.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "bool", "ph": "X", "ts": 110.0, "dur": 21.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "bool", "ph": "X", "ts": 110.0, "dur": 21.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_exit", "ph": "X", "ts": 129.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_exit", "ph": "X", "ts": 129.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_exit", "ph": "X", "ts": 129.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_enter", "ph": "X", "ts": 144.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_enter", "ph": "X", "ts": 144.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_enter", "ph": "X", "ts": 144.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "char", "ph": "X", "ts": 145.0, "dur": 46.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "char", "ph": "X", "ts": 145.0, "dur": 46.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "char", "ph": "X", "ts": 145.0, "dur": 46.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "add", "ph": "X", "ts": 173.0, "dur": 11.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "add", "ph": "X", "ts": 173.0, "dur": 11.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "add", "ph": "X", "ts": 174.0, "dur": 9.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_exit", "ph": "X", "ts": 190.0, "dur": 0.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_exit", "ph": "X", "ts": 190.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_exit", "ph": "X", "ts": 190.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_exit", "ph": "X", "ts": 198.0, "dur": 2.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_exit", "ph": "X", "ts": 199.0, "dur": 0.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_exit", "ph": "X", "ts": 199.0, "dur": 0.0, "tid": 0, "pid": "CPU functions", "args": {}}]
diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index 215619cac4539..ce2295092763d 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -189,6 +189,8 @@ def __init__(
         self.lightning_module = None  # set by ProfilerConnector
         self.register = None
         self.profiler_kwargs = profiler_kwargs
+        self.profiler = None
+        self._parent_profiler = None
 
         if self.export_to_chrome and self.path_to_export_trace is None:
             rank_zero_warn(
@@ -312,12 +314,3 @@ def _create_profiler(self, profiler: Type[_PROFILER]) -> _PROFILER:
         init_parameters = inspect.signature(profiler.__init__).parameters
         kwargs = {k: v for k, v in self.profiler_kwargs.items() if k in init_parameters}
         return profiler(**kwargs)
-
-    def __del__(self):
-        if self.profiler is not None:
-            self.profiler.__exit__(None, None, None)
-        if self._parent_profiler is not None:
-            self._parent_profiler.__exit__(None, None, None)
-        for recording in self.recording_map.values():
-            recording.__exit__(None, None, None)
-        super().__del__()
diff --git a/pytorch_lightning/trainer/connectors/profiler_connector.py b/pytorch_lightning/trainer/connectors/profiler_connector.py
index 231aa884a47df..4779d61587295 100644
--- a/pytorch_lightning/trainer/connectors/profiler_connector.py
+++ b/pytorch_lightning/trainer/connectors/profiler_connector.py
@@ -54,6 +54,8 @@ def on_trainer_init(self, profiler: Union[BaseProfiler, str]):
                     " `Trainer`, it can only be 'simple' or 'advanced'"
                 )
         self.trainer.profiler = profiler or PassThroughProfiler()
+        if isinstance(self.trainer.profiler, PyTorchProfiler):
+            self.trainer.profiler = proxy(self.trainer.profiler)
 
     def on_train_start(self, trainer):
         if not isinstance(trainer.profiler, PassThroughProfiler):
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index f3750aded0356..3a3c2836e48c2 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -200,7 +200,8 @@ def test_advanced_profiler_value_errors(advanced_profiler):
 @pytest.fixture
 def pytorch_profiler(tmpdir):
     profiler = PyTorchProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"), local_rank=0)
-    return profiler
+    yield profiler
+    del profiler
 
 
 def test_pytorch_profiler_describe(pytorch_profiler):

From 662f8de22f4da2b928c99c832638f1bc3e091fd1 Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Fri, 19 Mar 2021 12:53:41 +0000
Subject: [PATCH 16/87] update

---
 pytorch_lightning/trainer/connectors/profiler_connector.py | 1 -
 tests/test_profiler.py                                     | 1 +
 2 files changed, 1 insertion(+), 1 deletion(-)

diff --git a/pytorch_lightning/trainer/connectors/profiler_connector.py b/pytorch_lightning/trainer/connectors/profiler_connector.py
index 4779d61587295..2d286eb0be7f2 100644
--- a/pytorch_lightning/trainer/connectors/profiler_connector.py
+++ b/pytorch_lightning/trainer/connectors/profiler_connector.py
@@ -60,5 +60,4 @@ def on_trainer_init(self, profiler: Union[BaseProfiler, str]):
     def on_train_start(self, trainer):
         if not isinstance(trainer.profiler, PassThroughProfiler):
             local_rank = trainer.local_rank if trainer.world_size > 1 else None
-            self.trainer.profiler.lightning_module = proxy(self.trainer.lightning_module)
             self.trainer.profiler.on_train_start(local_rank=local_rank, log_dir=self.trainer.log_dir)
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 3a3c2836e48c2..abadb3c099283 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -326,6 +326,7 @@ def test_pytorch_profiler_nested(tmpdir):
     """Ensure that the profiler handles nested context"""
 
     pytorch_profiler = PyTorchProfiler(
+        export_to_chrome=False,
         record_functions=["a", "b", "c"],
         use_cuda=torch.cuda.is_available(),
         output_filename=os.path.join(tmpdir, "profiler.txt")

From 753f63bcac26e59b05a2ea861a7611f326139312 Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Fri, 19 Mar 2021 13:03:22 +0000
Subject: [PATCH 17/87] tests

---
 pytorch_lightning/profiler/pytorch.py | 11 +++++++++++
 tests/test_profiler.py                |  3 +--
 2 files changed, 12 insertions(+), 2 deletions(-)

diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index ce2295092763d..d291465dd3cd5 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -314,3 +314,14 @@ def _create_profiler(self, profiler: Type[_PROFILER]) -> _PROFILER:
         init_parameters = inspect.signature(profiler.__init__).parameters
         kwargs = {k: v for k, v in self.profiler_kwargs.items() if k in init_parameters}
         return profiler(**kwargs)
+
+    def __del__(self):
+        try:
+            self.profiler.__exit__(None, None, None)
+        except RuntimeError:
+            pass
+        try:
+            self._parent_profiler.__exit__(None, None, None)
+        except RuntimeError:
+            pass
+        super().__del__()
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index abadb3c099283..962c1a698ec21 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -200,8 +200,7 @@ def test_advanced_profiler_value_errors(advanced_profiler):
 @pytest.fixture
 def pytorch_profiler(tmpdir):
     profiler = PyTorchProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"), local_rank=0)
-    yield profiler
-    del profiler
+    return profiler
 
 
 def test_pytorch_profiler_describe(pytorch_profiler):

From e6a69173a139fbbc8ed2033009e614e588e5ee34 Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Fri, 19 Mar 2021 13:06:44 +0000
Subject: [PATCH 18/87] update

---
 pytorch_lightning/profiler/pytorch.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index d291465dd3cd5..fdf9cfcf273b5 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -318,10 +318,10 @@ def _create_profiler(self, profiler: Type[_PROFILER]) -> _PROFILER:
     def __del__(self):
         try:
             self.profiler.__exit__(None, None, None)
-        except RuntimeError:
+        except (AttributeError, RuntimeError):
             pass
         try:
             self._parent_profiler.__exit__(None, None, None)
-        except RuntimeError:
+        except (AttributeError, RuntimeError):
             pass
         super().__del__()

From a7f7f4c4c82f0222f3d37c6ac14f3ec4ed7add89 Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Fri, 19 Mar 2021 13:20:28 +0000
Subject: [PATCH 19/87] update

---
 pytorch_lightning/trainer/connectors/profiler_connector.py | 2 --
 1 file changed, 2 deletions(-)

diff --git a/pytorch_lightning/trainer/connectors/profiler_connector.py b/pytorch_lightning/trainer/connectors/profiler_connector.py
index 2d286eb0be7f2..7f96c1a6c0ace 100644
--- a/pytorch_lightning/trainer/connectors/profiler_connector.py
+++ b/pytorch_lightning/trainer/connectors/profiler_connector.py
@@ -54,8 +54,6 @@ def on_trainer_init(self, profiler: Union[BaseProfiler, str]):
                     " `Trainer`, it can only be 'simple' or 'advanced'"
                 )
         self.trainer.profiler = profiler or PassThroughProfiler()
-        if isinstance(self.trainer.profiler, PyTorchProfiler):
-            self.trainer.profiler = proxy(self.trainer.profiler)
 
     def on_train_start(self, trainer):
         if not isinstance(trainer.profiler, PassThroughProfiler):

From c221d7d9b8d6d22fbc15c3560f0adeed364c1242 Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Fri, 19 Mar 2021 13:23:28 +0000
Subject: [PATCH 20/87] update

---
 pytorch_lightning/trainer/connectors/profiler_connector.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/pytorch_lightning/trainer/connectors/profiler_connector.py b/pytorch_lightning/trainer/connectors/profiler_connector.py
index 7f96c1a6c0ace..7639926424090 100644
--- a/pytorch_lightning/trainer/connectors/profiler_connector.py
+++ b/pytorch_lightning/trainer/connectors/profiler_connector.py
@@ -13,7 +13,6 @@
 # limitations under the License
 
 from typing import Union
-from weakref import proxy
 
 from pytorch_lightning.profiler import (
     AdvancedProfiler,

From e39f6d7f5a601390436fbe425a43c9a9f6eac088 Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Fri, 19 Mar 2021 13:47:45 +0000
Subject: [PATCH 21/87] update

---
 pytorch_lightning/profiler/pytorch.py | 11 +++++++++++
 1 file changed, 11 insertions(+)

diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index fdf9cfcf273b5..aad0262ca821a 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -208,6 +208,12 @@ def __init__(
         self.function_events: Optional[EventList] = None
         self._profiler_instantiated: bool = False
 
+        # disable profiler if the user already created a profiler
+        try:
+            torch.autograd._disable_profiler()
+        except RuntimeError:
+            pass
+
         super().__init__(local_rank=local_rank)
 
     def __deprecation_check(self, profiled_functions: List[str] = [], record_functions: List[str] = []) -> List[str]:
@@ -324,4 +330,9 @@ def __del__(self):
             self._parent_profiler.__exit__(None, None, None)
         except (AttributeError, RuntimeError):
             pass
+        # disable profiler if the user already created a profiler
+        try:
+            torch.autograd._disable_profiler()
+        except RuntimeError:
+            pass
         super().__del__()

From e4858503463440ba9ed49c45c71e426405f54285 Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Fri, 19 Mar 2021 14:18:36 +0000
Subject: [PATCH 22/87] update

---
 pytorch_lightning/profiler/pytorch.py | 22 --------------------
 tests/test_profiler.py                | 29 +++++++++++----------------
 2 files changed, 12 insertions(+), 39 deletions(-)

diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index aad0262ca821a..ce2295092763d 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -208,12 +208,6 @@ def __init__(
         self.function_events: Optional[EventList] = None
         self._profiler_instantiated: bool = False
 
-        # disable profiler if the user already created a profiler
-        try:
-            torch.autograd._disable_profiler()
-        except RuntimeError:
-            pass
-
         super().__init__(local_rank=local_rank)
 
     def __deprecation_check(self, profiled_functions: List[str] = [], record_functions: List[str] = []) -> List[str]:
@@ -320,19 +314,3 @@ def _create_profiler(self, profiler: Type[_PROFILER]) -> _PROFILER:
         init_parameters = inspect.signature(profiler.__init__).parameters
         kwargs = {k: v for k, v in self.profiler_kwargs.items() if k in init_parameters}
         return profiler(**kwargs)
-
-    def __del__(self):
-        try:
-            self.profiler.__exit__(None, None, None)
-        except (AttributeError, RuntimeError):
-            pass
-        try:
-            self._parent_profiler.__exit__(None, None, None)
-        except (AttributeError, RuntimeError):
-            pass
-        # disable profiler if the user already created a profiler
-        try:
-            torch.autograd._disable_profiler()
-        except RuntimeError:
-            pass
-        super().__del__()
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 962c1a698ec21..a0160be5d43f4 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -197,14 +197,9 @@ def test_advanced_profiler_value_errors(advanced_profiler):
     advanced_profiler.stop(action)
 
 
-@pytest.fixture
-def pytorch_profiler(tmpdir):
-    profiler = PyTorchProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"), local_rank=0)
-    return profiler
-
-
-def test_pytorch_profiler_describe(pytorch_profiler):
+def test_pytorch_profiler_describe(tmpdir):
     """Ensure the profiler won't fail when reporting the summary."""
+    pytorch_profiler = PyTorchProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"), local_rank=0)
     with pytorch_profiler.profile("test_step"):
         pass
 
@@ -214,9 +209,9 @@ def test_pytorch_profiler_describe(pytorch_profiler):
     assert len(data) > 0
 
 
-def test_pytorch_profiler_value_errors(pytorch_profiler):
+def test_pytorch_profiler_value_errors(tmpdir):
     """Ensure errors are raised where expected."""
-
+    pytorch_profiler = PyTorchProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"), local_rank=0)
     action = "test_step"
     pytorch_profiler.start(action)
     pytorch_profiler.stop(action)
@@ -226,9 +221,9 @@ def test_pytorch_profiler_value_errors(pytorch_profiler):
 
 
 @RunIf(min_gpus=2, special=True)
-def test_pytorch_profiler_trainer_ddp(tmpdir, pytorch_profiler):
+def test_pytorch_profiler_trainer_ddp(tmpdir):
     """Ensure that the profiler can be given to the training and default step are properly recorded. """
-
+    pytorch_profiler = PyTorchProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"), local_rank=0)
     model = BoringModel()
     trainer = Trainer(
         max_epochs=1,
@@ -246,9 +241,9 @@ def test_pytorch_profiler_trainer_ddp(tmpdir, pytorch_profiler):
     assert len(data) > 0
 
 
-def test_pytorch_profiler_trainer_fit(tmpdir, pytorch_profiler):
+def test_pytorch_profiler_trainer_fit(tmpdir):
     """Ensure that the profiler can be given to the trainer and training, validation steps are properly recorded. """
-
+    pytorch_profiler = PyTorchProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"), local_rank=0)
     model = BoringModel()
     trainer = Trainer(
         default_root_dir=tmpdir,
@@ -268,9 +263,9 @@ def test_pytorch_profiler_trainer_fit(tmpdir, pytorch_profiler):
     print(tmpdir)
 
 
-def test_pytorch_profiler_trainer_test(tmpdir, pytorch_profiler):
+def test_pytorch_profiler_trainer_test(tmpdir):
     """Ensure that the profiler can be given to the trainer and test step are properly recorded. """
-
+    pytorch_profiler = PyTorchProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"), local_rank=0)
     model = BoringModel()
     trainer = Trainer(
         default_root_dir=tmpdir,
@@ -286,9 +281,9 @@ def test_pytorch_profiler_trainer_test(tmpdir, pytorch_profiler):
     assert len(data) > 0
 
 
-def test_pytorch_profiler_trainer_predict(tmpdir, pytorch_profiler):
+def test_pytorch_profiler_trainer_predict(tmpdir):
     """Ensure that the profiler can be given to the trainer and predict function are properly recorded. """
-
+    pytorch_profiler = PyTorchProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"), local_rank=0)
     model = BoringModel()
     model.predict_dataloader = model.train_dataloader
     trainer = Trainer(

From 00d355a32882a6ab5fac7729df3d9771c7db512a Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Fri, 19 Mar 2021 14:24:13 +0000
Subject: [PATCH 23/87] remove file

---
 0_trace.json | 1 -
 1 file changed, 1 deletion(-)
 delete mode 100644 0_trace.json

diff --git a/0_trace.json b/0_trace.json
deleted file mode 100644
index 9946c108fe5c7..0000000000000
--- a/0_trace.json
+++ /dev/null
@@ -1 +0,0 @@
-[{"name": "profiler::_record_function_enter", "ph": "X", "ts": 18.0, "dur": 4.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_enter", "ph": "X", "ts": 18.0, "dur": 4.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_enter", "ph": "X", "ts": 18.0, "dur": 4.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "signed char", "ph": "X", "ts": 22.0, "dur": 178.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "signed char", "ph": "X", "ts": 23.0, "dur": 177.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "signed char", "ph": "X", "ts": 23.0, "dur": 177.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_enter", "ph": "X", "ts": 108.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_enter", "ph": "X", "ts": 108.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_enter", "ph": "X", "ts": 108.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "bool", "ph": "X", "ts": 110.0, "dur": 20.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "bool", "ph": "X", "ts": 110.0, "dur": 21.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "bool", "ph": "X", "ts": 110.0, "dur": 21.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_exit", "ph": "X", "ts": 129.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_exit", "ph": "X", "ts": 129.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_exit", "ph": "X", "ts": 129.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_enter", "ph": "X", "ts": 144.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_enter", "ph": "X", "ts": 144.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_enter", "ph": "X", "ts": 144.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "char", "ph": "X", "ts": 145.0, "dur": 46.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "char", "ph": "X", "ts": 145.0, "dur": 46.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "char", "ph": "X", "ts": 145.0, "dur": 46.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "add", "ph": "X", "ts": 173.0, "dur": 11.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "add", "ph": "X", "ts": 173.0, "dur": 11.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "add", "ph": "X", "ts": 174.0, "dur": 9.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_exit", "ph": "X", "ts": 190.0, "dur": 0.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_exit", "ph": "X", "ts": 190.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_exit", "ph": "X", "ts": 190.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_exit", "ph": "X", "ts": 198.0, "dur": 2.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_exit", "ph": "X", "ts": 199.0, "dur": 0.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_exit", "ph": "X", "ts": 199.0, "dur": 0.0, "tid": 0, "pid": "CPU functions", "args": {}}]

From 61da390b1f5c85777aa177bf05a0ccdbaf44cffc Mon Sep 17 00:00:00 2001
From: thomas chaton <thomas@grid.ai>
Date: Fri, 19 Mar 2021 14:30:45 +0000
Subject: [PATCH 24/87] update

---
 0_trace.json                          | 2 +-
 pytorch_lightning/profiler/pytorch.py | 6 ++++++
 2 files changed, 7 insertions(+), 1 deletion(-)

diff --git a/0_trace.json b/0_trace.json
index 9946c108fe5c7..c86b649ec22a0 100644
--- a/0_trace.json
+++ b/0_trace.json
@@ -1 +1 @@
-[{"name": "profiler::_record_function_enter", "ph": "X", "ts": 18.0, "dur": 4.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_enter", "ph": "X", "ts": 18.0, "dur": 4.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_enter", "ph": "X", "ts": 18.0, "dur": 4.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "signed char", "ph": "X", "ts": 22.0, "dur": 178.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "signed char", "ph": "X", "ts": 23.0, "dur": 177.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "signed char", "ph": "X", "ts": 23.0, "dur": 177.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_enter", "ph": "X", "ts": 108.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_enter", "ph": "X", "ts": 108.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_enter", "ph": "X", "ts": 108.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "bool", "ph": "X", "ts": 110.0, "dur": 20.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "bool", "ph": "X", "ts": 110.0, "dur": 21.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "bool", "ph": "X", "ts": 110.0, "dur": 21.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_exit", "ph": "X", "ts": 129.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_exit", "ph": "X", "ts": 129.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_exit", "ph": "X", "ts": 129.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_enter", "ph": "X", "ts": 144.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_enter", "ph": "X", "ts": 144.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_enter", "ph": "X", "ts": 144.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "char", "ph": "X", "ts": 145.0, "dur": 46.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "char", "ph": "X", "ts": 145.0, "dur": 46.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "char", "ph": "X", "ts": 145.0, "dur": 46.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "add", "ph": "X", "ts": 173.0, "dur": 11.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "add", "ph": "X", "ts": 173.0, "dur": 11.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "add", "ph": "X", "ts": 174.0, "dur": 9.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_exit", "ph": "X", "ts": 190.0, "dur": 0.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_exit", "ph": "X", "ts": 190.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_exit", "ph": "X", "ts": 190.0, "dur": 1.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_exit", "ph": "X", "ts": 198.0, "dur": 2.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_exit", "ph": "X", "ts": 199.0, "dur": 0.0, "tid": 0, "pid": "CPU functions", "args": {}}, {"name": "profiler::_record_function_exit", "ph": "X", "ts": 199.0, "dur": 0.0, "tid": 0, "pid": "CPU functions", "args": {}}]
+[{"name": "aten::is_floating_point", "ph": "X", "ts": 129.565, "dur": 2.926000000000016, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::to", "ph": "X", "ts": 138.162, "dur": 2.0960000000000036, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::_has_compatible_shallow_copy_type", "ph": "X", "ts": 148.114, "dur": 1.7849999999999966, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::set_data", "ph": "X", "ts": 155.128, "dur": 5.027000000000015, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::_has_compatible_shallow_copy_type", "ph": "X", "ts": 157.16, "dur": 1.1049999999999898, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::is_floating_point", "ph": "X", "ts": 178.132, "dur": 1.2519999999999811, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::to", "ph": "X", "ts": 182.618, "dur": 1.5870000000000175, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::_has_compatible_shallow_copy_type", 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{}}, {"name": "aten::expand", "ph": "X", "ts": 22623.578, "dur": 4.7520000000004075, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 22625.728, "dur": 1.3580000000001746, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::copy_", "ph": "X", "ts": 22631.556, "dur": 10.023000000001048, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::stride", "ph": "X", "ts": 22637.374, "dur": 1.0689999999995052, "tid": 1, "pid": "CPU functions", "args": {}}]
\ No newline at end of file
diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index ce2295092763d..953f04c622c4b 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -245,6 +245,12 @@ def _rank_zero_only_wrap(self) -> None:
 
     def start(self, action_name: str) -> None:
         if not self._profiler_instantiated:
+            
+            # close profiler is already opened
+            try:
+                torch.autograd._disable_profiler()
+            except (AttributeError, RuntimeError):
+                pass
 
             self._create_profilers()
 

From e565e8a41a8826e5b7f10cde9db8f6838b9b4718 Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Fri, 19 Mar 2021 14:36:34 +0000
Subject: [PATCH 25/87] update

---
 0_trace.json | 1 -
 1 file changed, 1 deletion(-)
 delete mode 100644 0_trace.json

diff --git a/0_trace.json b/0_trace.json
deleted file mode 100644
index c86b649ec22a0..0000000000000
--- a/0_trace.json
+++ /dev/null
@@ -1 +0,0 @@
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"pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 22028.863, "dur": 2.024999999997817, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::expand", "ph": "X", "ts": 22032.709, "dur": 4.6010000000023865, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 22034.809, "dur": 1.2769999999982247, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::copy_", "ph": "X", "ts": 22040.653, "dur": 10.210000000002765, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::stride", "ph": "X", "ts": 22046.563, "dur": 1.1120000000009895, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::select", "ph": "X", "ts": 22110.036, "dur": 10.880000000001019, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 22114.959, "dur": 2.044000000001688, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::stack", "ph": "X", "ts": 22131.643, "dur": 39.9429999999993, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::unsqueeze", "ph": "X", "ts": 22135.666, "dur": 5.329999999998108, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 22138.474, "dur": 1.4130000000004657, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::cat", "ph": "X", "ts": 22142.49, "dur": 26.337999999999738, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::_cat", "ph": "X", "ts": 22144.833, "dur": 22.41400000000067, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 22148.311, "dur": 2.275999999998021, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::resize_", "ph": "X", "ts": 22153.93, "dur": 2.305000000000291, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::stride", "ph": "X", "ts": 22158.336, "dur": 1.0900000000001455, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::stride", "ph": "X", "ts": 22161.006, "dur": 4.7369999999973516, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::zeros", "ph": "X", "ts": 22191.679, "dur": 13.298999999999069, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 22194.179, "dur": 2.559000000001106, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::zero_", "ph": "X", "ts": 22198.505, "dur": 5.27100000000064, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::fill_", "ph": "X", "ts": 22200.148, "dur": 2.602999999999156, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "predict", "ph": "X", "ts": 22214.093, "dur": 178.10399999999936, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 22216.31, "dur": 1.6659999999974389, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::to", "ph": "X", "ts": 22253.785, "dur": 2.0469999999986612, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::t", "ph": "X", "ts": 22294.747, "dur": 17.93800000000192, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::transpose", "ph": "X", "ts": 22298.605, "dur": 9.68999999999869, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 22300.83, "dur": 6.227999999999156, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::addmm", "ph": "X", "ts": 22317.564, "dur": 33.119000000002416, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 22322.178, "dur": 2.2150000000001455, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::expand", "ph": "X", "ts": 22326.167, "dur": 4.764999999999418, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 22328.292, "dur": 1.3979999999974098, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::copy_", "ph": "X", "ts": 22334.311, "dur": 10.086999999999534, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::stride", "ph": "X", "ts": 22340.165, "dur": 1.0429999999978463, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::select", "ph": "X", "ts": 22404.448, "dur": 13.995999999999185, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 22409.448, "dur": 5.126000000000204, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::stack", "ph": "X", "ts": 22429.285, "dur": 36.41100000000006, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::unsqueeze", "ph": "X", "ts": 22433.379, "dur": 5.504000000000815, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 22436.31, "dur": 1.4389999999984866, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::cat", "ph": "X", "ts": 22440.294, "dur": 22.65599999999904, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::_cat", "ph": "X", "ts": 22442.678, "dur": 18.77600000000166, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 22446.068, "dur": 2.2109999999993306, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::resize_", "ph": "X", "ts": 22451.757, "dur": 2.290999999997439, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::stride", "ph": "X", "ts": 22456.178, "dur": 1.1120000000009895, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::stride", "ph": "X", "ts": 22459.005, "dur": 1.0309999999990396, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::zeros", "ph": "X", "ts": 22489.336, "dur": 13.183000000000902, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 22491.959, "dur": 2.5339999999996508, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::zero_", "ph": "X", "ts": 22496.269, "dur": 5.059000000001106, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::fill_", "ph": "X", "ts": 22497.89, "dur": 2.4089999999996508, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "predict", "ph": "X", "ts": 22511.789, "dur": 173.29000000000087, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 22513.916, "dur": 1.8799999999973807, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::to", "ph": "X", "ts": 22551.526, "dur": 2.0679999999993015, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::t", "ph": "X", "ts": 22592.626, "dur": 14.209999999999127, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::transpose", "ph": "X", "ts": 22596.473, "dur": 6.05199999999968, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 22598.69, "dur": 2.6130000000011933, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::addmm", "ph": "X", "ts": 22611.098, "dur": 36.536999999996624, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 22619.605, "dur": 2.114000000001397, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::expand", "ph": "X", "ts": 22623.578, "dur": 4.7520000000004075, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 22625.728, "dur": 1.3580000000001746, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::copy_", "ph": "X", "ts": 22631.556, "dur": 10.023000000001048, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::stride", "ph": "X", "ts": 22637.374, "dur": 1.0689999999995052, "tid": 1, "pid": "CPU functions", "args": {}}]
\ No newline at end of file

From 6f2258f5d07c919cd9b7b040d8cb52e630cd4c62 Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Fri, 19 Mar 2021 14:58:01 +0000
Subject: [PATCH 26/87] update

---
 tests/test_profiler.py | 9 ++++++---
 1 file changed, 6 insertions(+), 3 deletions(-)

diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index a0160be5d43f4..8e4254821a833 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -337,9 +337,12 @@ def test_pytorch_profiler_nested(tmpdir):
 
     events_name = {e.name for e in pytorch_profiler.function_events}
 
-    expected = {
-        'signed char', 'add', 'profiler::_record_function_exit', 'bool', 'char', 'profiler::_record_function_enter'
-    }
+    if platform.system() == "Windows":
+        expected = {'a', 'add', 'b', 'c', 'profiler::_record_function_enter', 'profiler::_record_function_exit'}
+    else:
+        expected = {
+            'signed char', 'add', 'profiler::_record_function_exit', 'bool', 'char', 'profiler::_record_function_enter'
+        }
 
     if LooseVersion(torch.__version__) >= LooseVersion("1.6.0"):
         expected = {'add', 'zeros', 'ones', 'zero_', 'b', 'fill_', 'c', 'a', 'empty'}

From 883b242bec06ce7817df4561273cb7beccf79920 Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Sun, 21 Mar 2021 10:47:43 +0000
Subject: [PATCH 27/87] update

---
 .gitignore                              |  1 +
 pytorch_lightning/profiler/profilers.py | 19 +++++++++++--------
 pytorch_lightning/profiler/pytorch.py   | 21 +++++++++++++++++----
 3 files changed, 29 insertions(+), 12 deletions(-)

diff --git a/.gitignore b/.gitignore
index cd0ba22453512..99939ff7fce0c 100644
--- a/.gitignore
+++ b/.gitignore
@@ -157,3 +157,4 @@ tags
 data
 MNIST
 runs
+*trace*
diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index 828d00da70dc2..01aad6926f584 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -51,8 +51,13 @@ class BaseProfiler(AbstractProfiler, ABC):
     If you wish to write a custom profiler, you should inherit from this class.
     """
 
-    def __init__(self, local_rank: Optional[int] = None, log_dir: Optional[str] = None) -> None:
-        self.output_fname = getattr(self, "output_fname", None)
+    def __init__(
+        self,
+        output_filename: Optional[str] = None,
+        local_rank: Optional[int] = None,
+        log_dir: Optional[str] = None
+    ) -> None:
+        self.output_fname = output_filename
         self.output_file = None
         # the profiler can be used outside of lightning
         # that's why we call `on_train_start` manually
@@ -110,6 +115,7 @@ def describe(self) -> None:
             write(self.summary())
         if self.output_file:
             self.output_file.flush()
+        self.teardown()
 
     def stats_to_str(self, stats: dict) -> str:
         output = ["Profiler Report"]
@@ -121,12 +127,10 @@ def stats_to_str(self, stats: dict) -> str:
             output.append(value)
         return os.linesep.join(output)
 
-    def __del__(self) -> None:
+    def teardown(self) -> None:
         """Close profiler's stream."""
-        try:
+        if self.output_file:
             self.output_file.close()
-        except AttributeError:
-            pass
 
 
 class PassThroughProfiler(BaseProfiler):
@@ -250,10 +254,9 @@ def __init__(self, output_filename: Optional[str] = None, line_count_restriction
             ValueError:
                 If you attempt to stop recording an action which was never started.
         """
-        self.output_fname = output_filename
+        super().__init__(output_filename=output_filename)
         self.profiled_actions = {}
         self.line_count_restriction = line_count_restriction
-        super().__init__()
 
     def start(self, action_name: str) -> None:
         if action_name not in self.profiled_actions:
diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index 953f04c622c4b..70b30bc505b1f 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -208,7 +208,7 @@ def __init__(
         self.function_events: Optional[EventList] = None
         self._profiler_instantiated: bool = False
 
-        super().__init__(local_rank=local_rank)
+        super().__init__(output_filename=output_filename, local_rank=local_rank)
 
     def __deprecation_check(self, profiled_functions: List[str] = [], record_functions: List[str] = []) -> List[str]:
         if profiled_functions is not None:
@@ -245,8 +245,8 @@ def _rank_zero_only_wrap(self) -> None:
 
     def start(self, action_name: str) -> None:
         if not self._profiler_instantiated:
-            
-            # close profiler is already opened
+
+            # close profiler if it is already opened
             try:
                 torch.autograd._disable_profiler()
             except (AttributeError, RuntimeError):
@@ -282,7 +282,8 @@ def summary(self) -> str:
             return ""
 
         local_rank = 0 if self.local_rank is None else self.local_rank
-        recorded_stats = {}
+        self.function_events = self.profiler.function_events
+
         self.profiler.__exit__(None, None, None)
         self.function_events = self.profiler.function_events
         self.profiler = None
@@ -304,6 +305,8 @@ def summary(self) -> str:
 
         data = self.function_events.key_averages(group_by_input_shapes=self.group_by_input_shapes)
         table = data.table(sort_by=self.sort_by_key, row_limit=self.row_limit)
+
+        recorded_stats = {}
         recorded_stats["records"] = table
 
         return self.stats_to_str(recorded_stats)
@@ -320,3 +323,13 @@ def _create_profiler(self, profiler: Type[_PROFILER]) -> _PROFILER:
         init_parameters = inspect.signature(profiler.__init__).parameters
         kwargs = {k: v for k, v in self.profiler_kwargs.items() if k in init_parameters}
         return profiler(**kwargs)
+
+    def teardown(self):
+        if self.profiler is not None:
+            self.profiler.__exit__(None, None, None)
+
+        if self._parent_profiler is not None:
+            self._parent_profiler.__exit__(None, None, None)
+            self._parent_profiler = None
+
+        super().teardown()

From 9b957bdbda666d90e87a930f142ea3ef8c2a608d Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Sun, 21 Mar 2021 11:10:17 +0000
Subject: [PATCH 28/87] update

---
 pytorch_lightning/profiler/pytorch.py | 6 ++++++
 tests/test_profiler.py                | 9 +++++++--
 2 files changed, 13 insertions(+), 2 deletions(-)

diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index 70b30bc505b1f..d84d70a5d21fc 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -332,4 +332,10 @@ def teardown(self):
             self._parent_profiler.__exit__(None, None, None)
             self._parent_profiler = None
 
+        if self.register is not None:
+            self.register.__exit__(None, None, None)
+
+        for record in self.recording_map.values():
+            record.__exit__(None, None, None)
+
         super().teardown()
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 8e4254821a833..71f0f8df12d59 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -120,8 +120,7 @@ def test_simple_profiler_value_errors(simple_profiler):
 
 @pytest.fixture
 def advanced_profiler(tmpdir):
-    profiler = AdvancedProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"))
-    return profiler
+    return AdvancedProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"))
 
 
 @pytest.mark.parametrize(["action", "expected"], [
@@ -207,6 +206,7 @@ def test_pytorch_profiler_describe(tmpdir):
     pytorch_profiler.describe()
     data = Path(pytorch_profiler.output_fname).read_text()
     assert len(data) > 0
+    pytorch_profiler.teardown()
 
 
 def test_pytorch_profiler_value_errors(tmpdir):
@@ -218,6 +218,7 @@ def test_pytorch_profiler_value_errors(tmpdir):
 
     with pytest.raises(MisconfigurationException, match="profiled_functions` and `PyTorchProfiler.record"):
         PyTorchProfiler(profiled_functions=["a"], record_functions=["b"])
+    pytorch_profiler.teardown()
 
 
 @RunIf(min_gpus=2, special=True)
@@ -239,6 +240,7 @@ def test_pytorch_profiler_trainer_ddp(tmpdir):
 
     data = Path(pytorch_profiler.output_fname).read_text()
     assert len(data) > 0
+    pytorch_profiler.teardown()
 
 
 def test_pytorch_profiler_trainer_fit(tmpdir):
@@ -261,6 +263,7 @@ def test_pytorch_profiler_trainer_fit(tmpdir):
     data = Path(pytorch_profiler.output_fname).read_text()
     assert len(data) > 0
     print(tmpdir)
+    pytorch_profiler.teardown()
 
 
 def test_pytorch_profiler_trainer_test(tmpdir):
@@ -279,6 +282,7 @@ def test_pytorch_profiler_trainer_test(tmpdir):
 
     data = Path(pytorch_profiler.output_fname).read_text()
     assert len(data) > 0
+    pytorch_profiler.teardown()
 
 
 def test_pytorch_profiler_trainer_predict(tmpdir):
@@ -298,6 +302,7 @@ def test_pytorch_profiler_trainer_predict(tmpdir):
 
     data = Path(pytorch_profiler.output_fname).read_text()
     assert len(data) > 0
+    pytorch_profiler.teardown()
 
 
 @RunIf(min_gpus=1, special=True)

From 70cc20d7e1438f1a4310e6fbdcac658fc700bc08 Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Sun, 21 Mar 2021 11:29:45 +0000
Subject: [PATCH 29/87] test

---
 pytorch_lightning/profiler/profilers.py | 2 +-
 tests/test_profiler.py                  | 2 ++
 2 files changed, 3 insertions(+), 1 deletion(-)

diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index 01aad6926f584..2bfb1759f09be 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -73,7 +73,7 @@ def on_train_start(self, local_rank: Optional[int] = None, log_dir: Optional[str
         self.prepare_file()
 
     def prepare_file(self) -> None:
-        if self.output_fname:
+        if self.output_fname and self.output_file is None:
             fs = get_filesystem(self.output_fname)
             self.output_file = fs.open(self.output_fname, "w")
         self.write_streams = [self.output_file.write] if self.output_file else [log.info]
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 71f0f8df12d59..b313e6c5cd020 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -319,6 +319,7 @@ def test_pytorch_profiler_nested_emit_nvtx(tmpdir):
         gpus=1,
     )
     trainer.fit(model)
+    pytorch_profiler.teardown()
 
 
 def test_pytorch_profiler_nested(tmpdir):
@@ -363,3 +364,4 @@ def test_pytorch_profiler_nested(tmpdir):
         }
 
     assert events_name == expected, (events_name, torch.__version__, platform.system())
+    pytorch_profiler.teardown()

From 226e0be70eeb287b76531bb9aa66b2e19d0f80ff Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Sun, 21 Mar 2021 12:43:06 +0000
Subject: [PATCH 30/87] update#

---
 pytorch_lightning/profiler/profilers.py   | 18 +++++++++++++-----
 pytorch_lightning/profiler/pytorch.py     |  6 ++++--
 pytorch_lightning/trainer/predict_loop.py |  2 ++
 tests/checkpointing/test_torch_saving.py  |  2 ++
 tests/test_profiler.py                    | 13 ++++++++-----
 5 files changed, 29 insertions(+), 12 deletions(-)

diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index 2bfb1759f09be..b54d228c6fb2f 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -51,6 +51,8 @@ class BaseProfiler(AbstractProfiler, ABC):
     If you wish to write a custom profiler, you should inherit from this class.
     """
 
+    _ACTIONS_TO_PREPARE_FILE = ('on_train_start', 'on_validation_step', 'on_test_start', 'on_predict_start')
+
     def __init__(
         self,
         output_filename: Optional[str] = None,
@@ -59,6 +61,8 @@ def __init__(
     ) -> None:
         self.output_fname = output_filename
         self.output_file = None
+        self._file_prepared = False
+        self.write_streams = []
         # the profiler can be used outside of lightning
         # that's why we call `on_train_start` manually
         self.on_train_start(local_rank=local_rank, log_dir=log_dir)
@@ -70,13 +74,14 @@ def on_train_start(self, local_rank: Optional[int] = None, log_dir: Optional[str
         """
         self.local_rank = local_rank
         self.log_dir = log_dir
-        self.prepare_file()
 
     def prepare_file(self) -> None:
-        if self.output_fname and self.output_file is None:
-            fs = get_filesystem(self.output_fname)
-            self.output_file = fs.open(self.output_fname, "w")
-        self.write_streams = [self.output_file.write] if self.output_file else [log.info]
+        if not self._file_prepared:
+            if self.output_fname and self.output_file is None:
+                fs = get_filesystem(self.output_fname)
+                self.output_file = fs.open(self.output_fname, "w")
+            self.write_streams = [self.output_file.write] if self.output_file else [log.info]
+        self._file_prepared = True
 
     @contextmanager
     def profile(self, action_name: str) -> None:
@@ -92,6 +97,9 @@ def profile(self, action_name: str) -> None:
         stop once you exit the code block.
         """
         try:
+            # Needs to be created after spawn processes
+            if action_name in self._ACTIONS_TO_PREPARE_FILE and not self._file_prepared:
+                self.prepare_file()
             self.start(action_name)
             yield action_name
         finally:
diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index d84d70a5d21fc..4e4081fe5fd59 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -244,7 +244,9 @@ def _rank_zero_only_wrap(self) -> None:
         self.describe = rank_zero_only(self.describe)
 
     def start(self, action_name: str) -> None:
-        if not self._profiler_instantiated:
+        if not self._profiler_instantiated and action_name in (
+            list(self._ACTIONS_TO_PREPARE_FILE) + list(self.record_functions)
+        ):
 
             # close profiler if it is already opened
             try:
@@ -265,7 +267,7 @@ def start(self, action_name: str) -> None:
                 self.register.__enter__()
 
         if (
-            action_name in self.record_functions and action_name != self.ACTION_NAME_START
+            self._profiler_instantiated and action_name in self.record_functions
             and action_name not in self.recording_map
         ):
             recording = record_function(action_name)
diff --git a/pytorch_lightning/trainer/predict_loop.py b/pytorch_lightning/trainer/predict_loop.py
index 8d99a4db38ce8..fe0719aa14da9 100644
--- a/pytorch_lightning/trainer/predict_loop.py
+++ b/pytorch_lightning/trainer/predict_loop.py
@@ -44,6 +44,8 @@ def on_predict_model_eval(self, *_, **__):
         model_ref.on_predict_model_eval()
 
     def setup(self, model, max_batches, dataloaders):
+        self.trainer.call_hook("on_predict_start")
+
         # copy properties for forward overrides
         self.trainer.model_connector.copy_trainer_model_properties(model)
 
diff --git a/tests/checkpointing/test_torch_saving.py b/tests/checkpointing/test_torch_saving.py
index c8b1e96aeaf0a..0c703a58d57a4 100644
--- a/tests/checkpointing/test_torch_saving.py
+++ b/tests/checkpointing/test_torch_saving.py
@@ -47,6 +47,8 @@ def test_model_torch_save_ddp_cpu(tmpdir):
         max_epochs=num_epochs,
         accelerator="ddp_cpu",
         num_processes=2,
+        profiler=None,
+        logger=None,
     )
     temp_path = os.path.join(tmpdir, 'temp.pt')
     trainer.fit(model)
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index b313e6c5cd020..d954b349c5d45 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -49,6 +49,7 @@ def _sleep_generator(durations):
 @pytest.fixture
 def simple_profiler():
     profiler = SimpleProfiler()
+    profiler.prepare_file()
     return profiler
 
 
@@ -120,7 +121,9 @@ def test_simple_profiler_value_errors(simple_profiler):
 
 @pytest.fixture
 def advanced_profiler(tmpdir):
-    return AdvancedProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"))
+    profiler = AdvancedProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"))
+    profiler.prepare_file()
+    return profiler
 
 
 @pytest.mark.parametrize(["action", "expected"], [
@@ -199,6 +202,7 @@ def test_advanced_profiler_value_errors(advanced_profiler):
 def test_pytorch_profiler_describe(tmpdir):
     """Ensure the profiler won't fail when reporting the summary."""
     pytorch_profiler = PyTorchProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"), local_rank=0)
+    pytorch_profiler.prepare_file()
     with pytorch_profiler.profile("test_step"):
         pass
 
@@ -255,14 +259,12 @@ def test_pytorch_profiler_trainer_fit(tmpdir):
         profiler=pytorch_profiler,
     )
     trainer.fit(model)
-
     expected = ('validation_step', 'training_step_and_backward', 'training_step', 'backward')
     for name in expected:
         assert len([e for e in pytorch_profiler.function_events if name == e.name]) > 0
 
     data = Path(pytorch_profiler.output_fname).read_text()
     assert len(data) > 0
-    print(tmpdir)
     pytorch_profiler.teardown()
 
 
@@ -310,12 +312,12 @@ def test_pytorch_profiler_nested_emit_nvtx(tmpdir):
     """
     This test check emit_nvtx is correctly supported
     """
-    profiler = PyTorchProfiler(use_cuda=True, emit_nvtx=True)
+    pytorch_profiler = PyTorchProfiler(use_cuda=True, emit_nvtx=True)
 
     model = BoringModel()
     trainer = Trainer(
         fast_dev_run=True,
-        profiler=profiler,
+        profiler=pytorch_profiler,
         gpus=1,
     )
     trainer.fit(model)
@@ -331,6 +333,7 @@ def test_pytorch_profiler_nested(tmpdir):
         use_cuda=torch.cuda.is_available(),
         output_filename=os.path.join(tmpdir, "profiler.txt")
     )
+    pytorch_profiler.prepare_file()
 
     with pytorch_profiler.profile("a"):
         a = torch.ones(42)

From 27348c775c5e844dc66b9dcce803b9042836d154 Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Sun, 21 Mar 2021 13:29:17 +0000
Subject: [PATCH 31/87] update

---
 pytorch_lightning/profiler/profilers.py                    | 7 ++-----
 pytorch_lightning/profiler/pytorch.py                      | 4 ++--
 pytorch_lightning/trainer/connectors/profiler_connector.py | 5 ++---
 3 files changed, 6 insertions(+), 10 deletions(-)

diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index b54d228c6fb2f..93d7b3e0f604e 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -51,8 +51,6 @@ class BaseProfiler(AbstractProfiler, ABC):
     If you wish to write a custom profiler, you should inherit from this class.
     """
 
-    _ACTIONS_TO_PREPARE_FILE = ('on_train_start', 'on_validation_step', 'on_test_start', 'on_predict_start')
-
     def __init__(
         self,
         output_filename: Optional[str] = None,
@@ -97,9 +95,6 @@ def profile(self, action_name: str) -> None:
         stop once you exit the code block.
         """
         try:
-            # Needs to be created after spawn processes
-            if action_name in self._ACTIONS_TO_PREPARE_FILE and not self._file_prepared:
-                self.prepare_file()
             self.start(action_name)
             yield action_name
         finally:
@@ -119,6 +114,7 @@ def profile_iterable(self, iterable, action_name: str) -> None:
 
     def describe(self) -> None:
         """Logs a profile report after the conclusion of the training run."""
+        self.prepare_file()
         for write in self.write_streams:
             write(self.summary())
         if self.output_file:
@@ -139,6 +135,7 @@ def teardown(self) -> None:
         """Close profiler's stream."""
         if self.output_file:
             self.output_file.close()
+        self.write_streams = []
 
 
 class PassThroughProfiler(BaseProfiler):
diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index 4e4081fe5fd59..45f2e92c2a504 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -101,7 +101,7 @@ class PyTorchProfiler(BaseProfiler):
         "self_cuda_memory_usage",
         "count",
     )
-    ACTION_NAME_START = "on_fit_start"
+    START_RECORD_FUNCTIONS = ('on_train_start', 'on_validation_step', 'on_test_start', 'on_predict_start')
 
     def __init__(
         self,
@@ -245,7 +245,7 @@ def _rank_zero_only_wrap(self) -> None:
 
     def start(self, action_name: str) -> None:
         if not self._profiler_instantiated and action_name in (
-            list(self._ACTIONS_TO_PREPARE_FILE) + list(self.record_functions)
+            list(self.START_RECORD_FUNCTIONS) + list(self.record_functions)
         ):
 
             # close profiler if it is already opened
diff --git a/pytorch_lightning/trainer/connectors/profiler_connector.py b/pytorch_lightning/trainer/connectors/profiler_connector.py
index 7639926424090..21160e687953c 100644
--- a/pytorch_lightning/trainer/connectors/profiler_connector.py
+++ b/pytorch_lightning/trainer/connectors/profiler_connector.py
@@ -55,6 +55,5 @@ def on_trainer_init(self, profiler: Union[BaseProfiler, str]):
         self.trainer.profiler = profiler or PassThroughProfiler()
 
     def on_train_start(self, trainer):
-        if not isinstance(trainer.profiler, PassThroughProfiler):
-            local_rank = trainer.local_rank if trainer.world_size > 1 else None
-            self.trainer.profiler.on_train_start(local_rank=local_rank, log_dir=self.trainer.log_dir)
+        local_rank = trainer.local_rank if trainer.world_size > 1 else None
+        self.trainer.profiler.on_train_start(local_rank=local_rank, log_dir=self.trainer.log_dir)

From 853d36c63e0720f743fa31f600d66af1050f60a2 Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Sun, 21 Mar 2021 14:42:04 +0000
Subject: [PATCH 32/87] update tests

---
 pytorch_lightning/profiler/profilers.py |  8 ++---
 tests/special_tests.sh                  |  2 +-
 tests/test_profiler.py                  | 40 +++++++++----------------
 3 files changed, 19 insertions(+), 31 deletions(-)

diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index 93d7b3e0f604e..78def777de49c 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -21,7 +21,7 @@
 from abc import ABC, abstractmethod
 from collections import defaultdict
 from contextlib import contextmanager
-from typing import Optional
+from typing import Dict, Optional
 
 import numpy as np
 
@@ -73,7 +73,7 @@ def on_train_start(self, local_rank: Optional[int] = None, log_dir: Optional[str
         self.local_rank = local_rank
         self.log_dir = log_dir
 
-    def prepare_file(self) -> None:
+    def _prepare_file(self) -> None:
         if not self._file_prepared:
             if self.output_fname and self.output_file is None:
                 fs = get_filesystem(self.output_fname)
@@ -114,14 +114,14 @@ def profile_iterable(self, iterable, action_name: str) -> None:
 
     def describe(self) -> None:
         """Logs a profile report after the conclusion of the training run."""
-        self.prepare_file()
+        self._prepare_file()
         for write in self.write_streams:
             write(self.summary())
         if self.output_file:
             self.output_file.flush()
         self.teardown()
 
-    def stats_to_str(self, stats: dict) -> str:
+    def stats_to_str(self, stats: Dict[str, str]) -> str:
         output = ["Profiler Report"]
         for action, value in stats.items():
             header = f"Profile stats for: {action}"
diff --git a/tests/special_tests.sh b/tests/special_tests.sh
index e5c6e313bb6d8..4a7b1f300f79d 100644
--- a/tests/special_tests.sh
+++ b/tests/special_tests.sh
@@ -28,7 +28,7 @@ python ${DEFAULTS} tests/trainer/test_trainer.py::test_trainer_predict_ddp
 python ${DEFAULTS} tests/trainer/test_trainer.py::test_trainer_predict_dp
 python ${DEFAULTS} tests/trainer/logging_/test_train_loop_logging_1_0.py::test_logging_sync_dist_true_ddp
 python ${DEFAULTS} tests/callbacks/test_pruning.py::test_pruning_callback_ddp
-python ${DEFAULTS} tests/trainer/test_trainer.py::test_pytorch_profiler_trainer_ddp
+python ${DEFAULTS} tests/test_profiler.py::test_pytorch_profiler_trainer_ddp
 python ${DEFAULTS} tests/models/test_hooks.py::test_transfer_batch_hook_ddp
 python ${DEFAULTS} tests/trainer/test_data_loading.py::test_replace_distrubuted_sampler_custom_dataloader_custom_batch_sampler
 python ${DEFAULTS} tests/trainer/optimization/test_manual_optimization.py::test_step_with_optimizer_closure_with_different_frequencies_ddp_with_toggle_model
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index d954b349c5d45..2866b78ea0a15 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -48,9 +48,7 @@ def _sleep_generator(durations):
 
 @pytest.fixture
 def simple_profiler():
-    profiler = SimpleProfiler()
-    profiler.prepare_file()
-    return profiler
+    return SimpleProfiler()
 
 
 @pytest.mark.parametrize(["action", "expected"], [
@@ -121,9 +119,7 @@ def test_simple_profiler_value_errors(simple_profiler):
 
 @pytest.fixture
 def advanced_profiler(tmpdir):
-    profiler = AdvancedProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"))
-    profiler.prepare_file()
-    return profiler
+    return AdvancedProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"))
 
 
 @pytest.mark.parametrize(["action", "expected"], [
@@ -199,10 +195,13 @@ def test_advanced_profiler_value_errors(advanced_profiler):
     advanced_profiler.stop(action)
 
 
-def test_pytorch_profiler_describe(tmpdir):
+@pytest.fixture
+def pytorch_profiler(tmpdir):
+    return PyTorchProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"), local_rank=0)
+
+
+def test_pytorch_profiler_describe(pytorch_profiler):
     """Ensure the profiler won't fail when reporting the summary."""
-    pytorch_profiler = PyTorchProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"), local_rank=0)
-    pytorch_profiler.prepare_file()
     with pytorch_profiler.profile("test_step"):
         pass
 
@@ -210,12 +209,10 @@ def test_pytorch_profiler_describe(tmpdir):
     pytorch_profiler.describe()
     data = Path(pytorch_profiler.output_fname).read_text()
     assert len(data) > 0
-    pytorch_profiler.teardown()
 
 
-def test_pytorch_profiler_value_errors(tmpdir):
+def test_pytorch_profiler_value_errors(pytorch_profiler):
     """Ensure errors are raised where expected."""
-    pytorch_profiler = PyTorchProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"), local_rank=0)
     action = "test_step"
     pytorch_profiler.start(action)
     pytorch_profiler.stop(action)
@@ -226,9 +223,8 @@ def test_pytorch_profiler_value_errors(tmpdir):
 
 
 @RunIf(min_gpus=2, special=True)
-def test_pytorch_profiler_trainer_ddp(tmpdir):
+def test_pytorch_profiler_trainer_ddp(tmpdir, pytorch_profiler):
     """Ensure that the profiler can be given to the training and default step are properly recorded. """
-    pytorch_profiler = PyTorchProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"), local_rank=0)
     model = BoringModel()
     trainer = Trainer(
         max_epochs=1,
@@ -244,12 +240,10 @@ def test_pytorch_profiler_trainer_ddp(tmpdir):
 
     data = Path(pytorch_profiler.output_fname).read_text()
     assert len(data) > 0
-    pytorch_profiler.teardown()
 
 
-def test_pytorch_profiler_trainer_fit(tmpdir):
+def test_pytorch_profiler_trainer_fit(tmpdir, pytorch_profiler):
     """Ensure that the profiler can be given to the trainer and training, validation steps are properly recorded. """
-    pytorch_profiler = PyTorchProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"), local_rank=0)
     model = BoringModel()
     trainer = Trainer(
         default_root_dir=tmpdir,
@@ -265,12 +259,10 @@ def test_pytorch_profiler_trainer_fit(tmpdir):
 
     data = Path(pytorch_profiler.output_fname).read_text()
     assert len(data) > 0
-    pytorch_profiler.teardown()
 
 
-def test_pytorch_profiler_trainer_test(tmpdir):
+def test_pytorch_profiler_trainer_test(tmpdir, pytorch_profiler):
     """Ensure that the profiler can be given to the trainer and test step are properly recorded. """
-    pytorch_profiler = PyTorchProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"), local_rank=0)
     model = BoringModel()
     trainer = Trainer(
         default_root_dir=tmpdir,
@@ -284,12 +276,10 @@ def test_pytorch_profiler_trainer_test(tmpdir):
 
     data = Path(pytorch_profiler.output_fname).read_text()
     assert len(data) > 0
-    pytorch_profiler.teardown()
 
 
-def test_pytorch_profiler_trainer_predict(tmpdir):
+def test_pytorch_profiler_trainer_predict(tmpdir, pytorch_profiler):
     """Ensure that the profiler can be given to the trainer and predict function are properly recorded. """
-    pytorch_profiler = PyTorchProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"), local_rank=0)
     model = BoringModel()
     model.predict_dataloader = model.train_dataloader
     trainer = Trainer(
@@ -304,7 +294,6 @@ def test_pytorch_profiler_trainer_predict(tmpdir):
 
     data = Path(pytorch_profiler.output_fname).read_text()
     assert len(data) > 0
-    pytorch_profiler.teardown()
 
 
 @RunIf(min_gpus=1, special=True)
@@ -316,6 +305,7 @@ def test_pytorch_profiler_nested_emit_nvtx(tmpdir):
 
     model = BoringModel()
     trainer = Trainer(
+        default_root_dir=tmpdir,
         fast_dev_run=True,
         profiler=pytorch_profiler,
         gpus=1,
@@ -333,7 +323,6 @@ def test_pytorch_profiler_nested(tmpdir):
         use_cuda=torch.cuda.is_available(),
         output_filename=os.path.join(tmpdir, "profiler.txt")
     )
-    pytorch_profiler.prepare_file()
 
     with pytorch_profiler.profile("a"):
         a = torch.ones(42)
@@ -367,4 +356,3 @@ def test_pytorch_profiler_nested(tmpdir):
         }
 
     assert events_name == expected, (events_name, torch.__version__, platform.system())
-    pytorch_profiler.teardown()

From 9004e92fb2d75f6a44bcb895f9c4e0522caf3141 Mon Sep 17 00:00:00 2001
From: thomas chaton <thomas@grid.ai>
Date: Sun, 21 Mar 2021 15:31:58 +0000
Subject: [PATCH 33/87] update

---
 pytorch_lightning/profiler/profilers.py | 1 +
 pytorch_lightning/profiler/pytorch.py   | 9 ++++++---
 tests/test_profiler.py                  | 1 -
 3 files changed, 7 insertions(+), 4 deletions(-)

diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index 78def777de49c..b60c726c5b642 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -136,6 +136,7 @@ def teardown(self) -> None:
         if self.output_file:
             self.output_file.close()
         self.write_streams = []
+        self._file_prepared = False
 
 
 class PassThroughProfiler(BaseProfiler):
diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index 45f2e92c2a504..874a4e607c784 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -280,14 +280,14 @@ def stop(self, action_name: str) -> None:
             del self.recording_map[action_name]
 
     def summary(self) -> str:
-        if not self.profiler_kwargs.get("enabled", True) or self.emit_nvtx:
+        if not self.profiler_kwargs.get("enabled", True):
             return ""
 
         local_rank = 0 if self.local_rank is None else self.local_rank
-        self.function_events = self.profiler.function_events
 
         self.profiler.__exit__(None, None, None)
-        self.function_events = self.profiler.function_events
+        if not self.emit_nvtx:
+            self.function_events = self.profiler.function_events
         self.profiler = None
         self._profiler_instantiated = False
 
@@ -298,6 +298,9 @@ def summary(self) -> str:
         if self.register is not None:
             self.register.__exit__(None, None, None)
 
+        if self.emit_nvtx:
+            return ""
+
         if self.export_to_chrome:
             filename = f"{local_rank}_trace.json"
             path_to_trace = (
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 2866b78ea0a15..33550f3e548ba 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -311,7 +311,6 @@ def test_pytorch_profiler_nested_emit_nvtx(tmpdir):
         gpus=1,
     )
     trainer.fit(model)
-    pytorch_profiler.teardown()
 
 
 def test_pytorch_profiler_nested(tmpdir):

From fbbb9a2d310bf7548f9938b151a395df0b454984 Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Mon, 22 Mar 2021 01:33:33 +0100
Subject: [PATCH 34/87] Refactor basic profilers

---
 pytorch_lightning/profiler/profilers.py | 177 +++++++++++++-----------
 pytorch_lightning/profiler/pytorch.py   |  52 ++-----
 2 files changed, 106 insertions(+), 123 deletions(-)

diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index d704ba83236c1..e7cb263b1d26e 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -21,7 +21,7 @@
 from abc import ABC, abstractmethod
 from collections import defaultdict
 from contextlib import contextmanager
-from typing import Optional, Union
+from typing import Dict, Optional
 
 import numpy as np
 
@@ -30,22 +30,8 @@
 log = logging.getLogger(__name__)
 
 
-class BaseProfiler(ABC):
-    """
-    If you wish to write a custom profiler, you should inhereit from this class.
-    """
-
-    def __init__(self, output_streams: Optional[Union[list, tuple]] = None):
-        """
-        Args:
-            output_streams: callable
-        """
-        if output_streams:
-            if not isinstance(output_streams, (list, tuple)):
-                output_streams = [output_streams]
-        else:
-            output_streams = []
-        self.write_streams = output_streams
+class AbstractProfiler(ABC):
+    """Specification of a profiler."""
 
     @abstractmethod
     def start(self, action_name: str) -> None:
@@ -55,6 +41,49 @@ def start(self, action_name: str) -> None:
     def stop(self, action_name: str) -> None:
         """Defines how to record the duration once an action is complete."""
 
+    @abstractmethod
+    def summary(self) -> str:
+        """Create profiler summary in text format."""
+
+    def teardown(self) -> None:
+        """Execute arbitrary post-profiling tear-down steps as defined by subclass."""
+
+
+class BaseProfiler(AbstractProfiler):
+    """
+    If you wish to write a custom profiler, you should inherit from this class.
+    """
+
+    def __init__(
+        self,
+        output_filename: Optional[str] = None,
+        local_rank: Optional[int] = None,
+        log_dir: Optional[str] = None
+    ) -> None:
+        self.output_fname = output_filename
+        self.output_file = None
+        self._file_prepared = False
+        self.write_streams = []
+        # the profiler can be used outside of lightning
+        # that's why we call `on_train_start` manually
+        self.on_train_start(local_rank=local_rank, log_dir=log_dir)
+
+    def on_train_start(self, local_rank: Optional[int] = None, log_dir: Optional[str] = None):
+        """
+        This function is used by the Trainer to inject local_rank with `DDP`
+        and `TensorBoardLogger` log_dir in the profiler.
+        """
+        self.local_rank = local_rank
+        self.log_dir = log_dir
+
+    def _prepare_file(self) -> None:
+        if not self._file_prepared:
+            if self.output_fname and self.output_file is None:
+                fs = get_filesystem(self.output_fname)
+                self.output_file = fs.open(self.output_fname, "w")
+            self.write_streams = [self.output_file.write] if self.output_file else [log.info]
+        self._file_prepared = True
+
     @contextmanager
     def profile(self, action_name: str) -> None:
         """
@@ -88,15 +117,41 @@ def profile_iterable(self, iterable, action_name: str) -> None:
 
     def describe(self) -> None:
         """Logs a profile report after the conclusion of the training run."""
+        self._prepare_file()
         for write in self.write_streams:
             write(self.summary())
+        if self.output_file:
+            self.output_file.flush()
+        self.teardown()
+
+    def stats_to_str(self, stats: Dict[str, str]) -> str:
+        output = ["Profiler Report"]
+        for action, value in stats.items():
+            header = f"Profile stats for: {action}"
+            if getattr(self, "local_rank", None) is not None:
+                header += f" rank: {self.local_rank}"
+            output.append(header)
+            output.append(value)
+        return os.linesep.join(output)
+
+    def teardown(self) -> None:
+        """Close profiler's stream."""
+        if self.output_file:
+            self.output_file.close()
+        self.write_streams = []
+        self._file_prepared = False
 
-    @abstractmethod
-    def summary(self) -> str:
-        """Create profiler summary in text format."""
+    def __del__(self):
+        self.teardown()
 
-    def on_train_start(self, local_rank: Optional[int] = None):
-        self.local_rank = local_rank
+    def start(self, action_name: str) -> None:
+        raise NotImplementedError
+
+    def stop(self, action_name: str) -> None:
+        raise NotImplementedError
+
+    def summary(self) -> str:
+        raise NotImplementedError
 
 
 class PassThroughProfiler(BaseProfiler):
@@ -105,9 +160,6 @@ class PassThroughProfiler(BaseProfiler):
     The Trainer uses this class by default.
     """
 
-    def __init__(self):
-        super().__init__(output_streams=None)
-
     def start(self, action_name: str) -> None:
         pass
 
@@ -117,6 +169,9 @@ def stop(self, action_name: str) -> None:
     def summary(self) -> str:
         return ""
 
+    def teardown(self) -> None:
+        pass
+
 
 class SimpleProfiler(BaseProfiler):
     """
@@ -124,7 +179,7 @@ class SimpleProfiler(BaseProfiler):
     the mean duration of each action and the total time spent over the entire training run.
     """
 
-    def __init__(self, output_filename: Optional[str] = None, extended=True):
+    def __init__(self, output_filename: Optional[str] = None, extended: bool = True):
         """
         Args:
             output_filename: optionally save profile results to file instead of printing
@@ -135,19 +190,12 @@ def __init__(self, output_filename: Optional[str] = None, extended=True):
                 If you attempt to start an action which has already started, or
                 if you attempt to stop recording an action which was never started.
         """
+        self.output_fname = output_filename
         self.current_actions = {}
         self.recorded_durations = defaultdict(list)
         self.extended = extended
-
-        self.output_fname = output_filename
-        self.output_file = None
-        if self.output_fname:
-            fs = get_filesystem(self.output_fname)
-            self.output_file = fs.open(self.output_fname, "w")
-
-        streaming_out = [self.output_file.write] if self.output_file else [log.info]
+        super().__init__()
         self.start_time = time.monotonic()
-        super().__init__(output_streams=streaming_out)
 
     def start(self, action_name: str) -> None:
         if action_name in self.current_actions:
@@ -169,7 +217,8 @@ def make_report(self):
         return report, total_duration
 
     def summary(self) -> str:
-        output_string = "\n\nProfiler Report\n"
+        sep = os.linesep
+        output_string = f"Profiler Report{sep}"
 
         if self.extended:
 
@@ -177,16 +226,16 @@ def summary(self) -> str:
                 max_key = np.max([len(k) for k in self.recorded_durations.keys()])
 
                 def log_row(action, mean, num_calls, total, per):
-                    row = f"{os.linesep}{action:<{max_key}s}\t|  {mean:<15}\t|"
+                    row = f"{sep}{action:<{max_key}s}\t|  {mean:<15}\t|"
                     row += f"{num_calls:<15}\t|  {total:<15}\t|  {per:<15}\t|"
                     return row
 
                 output_string += log_row("Action", "Mean duration (s)", "Num calls", "Total time (s)", "Percentage %")
                 output_string_len = len(output_string)
-                output_string += f"{os.linesep}{'-' * output_string_len}"
+                output_string += f"{sep}{'-' * output_string_len}"
                 report, total_duration = self.make_report()
                 output_string += log_row("Total", "-", "_", f"{total_duration:.5}", "100 %")
-                output_string += f"{os.linesep}{'-' * output_string_len}"
+                output_string += f"{sep}{'-' * output_string_len}"
                 for action, durations, duration_per in report:
                     output_string += log_row(
                         action,
@@ -198,27 +247,16 @@ def log_row(action, mean, num_calls, total, per):
         else:
 
             def log_row(action, mean, total):
-                return f"{os.linesep}{action:<20s}\t|  {mean:<15}\t|  {total:<15}"
+                return f"{sep}{action:<20s}\t|  {mean:<15}\t|  {total:<15}"
 
             output_string += log_row("Action", "Mean duration (s)", "Total time (s)")
-            output_string += f"{os.linesep}{'-' * 65}"
+            output_string += f"{sep}{'-' * 65}"
 
             for action, durations in self.recorded_durations.items():
                 output_string += log_row(action, f"{np.mean(durations):.5}", f"{np.sum(durations):.5}")
-        output_string += os.linesep
+        output_string += sep
         return output_string
 
-    def describe(self):
-        """Logs a profile report after the conclusion of the training run."""
-        super().describe()
-        if self.output_file:
-            self.output_file.flush()
-
-    def __del__(self):
-        """Close profiler's stream."""
-        if self.output_file:
-            self.output_file.close()
-
 
 class AdvancedProfiler(BaseProfiler):
     """
@@ -240,18 +278,10 @@ def __init__(self, output_filename: Optional[str] = None, line_count_restriction
             ValueError:
                 If you attempt to stop recording an action which was never started.
         """
+        super().__init__(output_filename=output_filename)
         self.profiled_actions = {}
         self.line_count_restriction = line_count_restriction
 
-        self.output_fname = output_filename
-        self.output_file = None
-        if self.output_fname:
-            fs = get_filesystem(self.output_fname)
-            self.output_file = fs.open(self.output_fname, "w")
-
-        streaming_out = [self.output_file.write] if self.output_file else [log.info]
-        super().__init__(output_streams=streaming_out)
-
     def start(self, action_name: str) -> None:
         if action_name not in self.profiled_actions:
             self.profiled_actions[action_name] = cProfile.Profile()
@@ -260,9 +290,7 @@ def start(self, action_name: str) -> None:
     def stop(self, action_name: str) -> None:
         pr = self.profiled_actions.get(action_name)
         if pr is None:
-            raise ValueError(  # pragma: no-cover
-                f"Attempting to stop recording an action ({action_name}) which was never started."
-            )
+            raise ValueError(f"Attempting to stop recording an action ({action_name}) which was never started.")
         pr.disable()
 
     def summary(self) -> str:
@@ -272,21 +300,4 @@ def summary(self) -> str:
             ps = pstats.Stats(pr, stream=s).strip_dirs().sort_stats('cumulative')
             ps.print_stats(self.line_count_restriction)
             recorded_stats[action_name] = s.getvalue()
-
-        # log to standard out
-        output_string = f"{os.linesep}Profiler Report{os.linesep}"
-        for action, stats in recorded_stats.items():
-            output_string += f"{os.linesep}Profile stats for: {action}{os.linesep}{stats}"
-
-        return output_string
-
-    def describe(self):
-        """Logs a profile report after the conclusion of the training run."""
-        super().describe()
-        if self.output_file:
-            self.output_file.flush()
-
-    def __del__(self):
-        """Close profiler's stream."""
-        if self.output_file:
-            self.output_file.close()
+        return self.stats_to_str(recorded_stats)
diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index 88a33a3d367f8..30c553ee46e57 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -159,33 +159,21 @@ def __init__(
         self.running_stack = []
         self.profiler = None
 
-        self.output_fname = output_filename
-        self.output_file = None
-        if local_rank is not None:
-            self.on_train_start(local_rank=local_rank)
-            self.on_train_start = super().on_train_start
+        super().__init__(output_filename=output_filename, local_rank=local_rank)
 
-    def on_train_start(self, local_rank: Optional[str] = None):
-        self.local_rank = local_rank
+    def on_train_start(self, local_rank: Optional[int] = None, log_dir: Optional[str] = None) -> None:
+        super().on_train_start(local_rank=local_rank, log_dir=log_dir)
 
-        # when logging to `log.info`, only perform profiling on rank 0
-        if local_rank != 0 and self.output_fname is None:
-            self.wrap_functions_into_rank_zero_only()
-
-        if self.output_fname:
-            if local_rank is not None:
-                if '.txt' not in self.output_fname:
-                    raise MisconfigurationException("Log file should be .txt file.")
-
-                self.output_fname = self.output_fname.replace(".txt", f"_{self.local_rank}.txt")
-
-            fs = get_filesystem(self.output_fname)
-            self.output_file = fs.open(self.output_fname, "w")
+        # if the user didn't provide `path_to_export_trace`,
+        # set it as TensorBoardLogger log_dir if exists
+        if self.path_to_export_trace is None:
+            self.path_to_export_trace = log_dir
 
-        streaming_out = [self.output_file.write] if self.output_file else [log.info]
-        super().__init__(output_streams=streaming_out)
+        # when logging to `log.info`, only perform profiling on rank 0
+        if local_rank is not None and local_rank > 0 and self.output_fname is None:
+            self._rank_zero_only_wrap()
 
-    def wrap_functions_into_rank_zero_only(self):
+    def _rank_zero_only_wrap(self) -> None:
         self.start = rank_zero_only(self.start)
         self.stop = rank_zero_only(self.stop)
         self.summary = rank_zero_only(self.summary)
@@ -284,20 +272,4 @@ def summary(self) -> str:
                 table = data.table(sort_by=self.sort_by_key, row_limit=self.row_limit)
                 recorded_stats[action_name] = table
 
-        # log to standard out
-        output_string = f"{os.linesep}Profiler Report{os.linesep}"
-        for action, stats in recorded_stats.items():
-            output_string += (f"{os.linesep}Profile stats for: {action} rank: {local_rank} {os.linesep}{stats}")
-
-        return output_string
-
-    def describe(self):
-        """Logs a profile report after the conclusion of the training run."""
-        super().describe()
-        if self.output_file:
-            self.output_file.flush()
-
-    def __del__(self):
-        """Close profiler's stream."""
-        if self.output_file:
-            self.output_file.close()
+        return self.stats_to_str(recorded_stats)

From 2a82e05d4a999bdbfefec16a60a8b841ffaa957f Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Mon, 22 Mar 2021 02:07:02 +0100
Subject: [PATCH 35/87] Fixes

---
 pytorch_lightning/profiler/profilers.py | 19 +++++++++----------
 pytorch_lightning/trainer/trainer.py    |  1 +
 tests/test_profiler.py                  | 18 ++++++++++++++++++
 3 files changed, 28 insertions(+), 10 deletions(-)

diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index e7cb263b1d26e..8c573ab1c7e31 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -21,7 +21,7 @@
 from abc import ABC, abstractmethod
 from collections import defaultdict
 from contextlib import contextmanager
-from typing import Dict, Optional
+from typing import Dict, Optional, Tuple
 
 import numpy as np
 
@@ -68,7 +68,7 @@ def __init__(
         # that's why we call `on_train_start` manually
         self.on_train_start(local_rank=local_rank, log_dir=log_dir)
 
-    def on_train_start(self, local_rank: Optional[int] = None, log_dir: Optional[str] = None):
+    def on_train_start(self, local_rank: Optional[int] = None, log_dir: Optional[str] = None) -> None:
         """
         This function is used by the Trainer to inject local_rank with `DDP`
         and `TensorBoardLogger` log_dir in the profiler.
@@ -141,7 +141,7 @@ def teardown(self) -> None:
         self.write_streams = []
         self._file_prepared = False
 
-    def __del__(self):
+    def __del__(self) -> None:
         self.teardown()
 
     def start(self, action_name: str) -> None:
@@ -179,7 +179,7 @@ class SimpleProfiler(BaseProfiler):
     the mean duration of each action and the total time spent over the entire training run.
     """
 
-    def __init__(self, output_filename: Optional[str] = None, extended: bool = True):
+    def __init__(self, output_filename: Optional[str] = None, extended: bool = True) -> None:
         """
         Args:
             output_filename: optionally save profile results to file instead of printing
@@ -190,11 +190,10 @@ def __init__(self, output_filename: Optional[str] = None, extended: bool = True)
                 If you attempt to start an action which has already started, or
                 if you attempt to stop recording an action which was never started.
         """
-        self.output_fname = output_filename
-        self.current_actions = {}
+        self.current_actions: Dict[str, float] = {}
         self.recorded_durations = defaultdict(list)
         self.extended = extended
-        super().__init__()
+        super().__init__(output_filename=output_filename)
         self.start_time = time.monotonic()
 
     def start(self, action_name: str) -> None:
@@ -210,7 +209,7 @@ def stop(self, action_name: str) -> None:
         duration = end_time - start_time
         self.recorded_durations[action_name].append(duration)
 
-    def make_report(self):
+    def _make_report(self) -> Tuple[list, float]:
         total_duration = time.monotonic() - self.start_time
         report = [[a, d, 100. * np.sum(d) / total_duration] for a, d in self.recorded_durations.items()]
         report.sort(key=lambda x: x[2], reverse=True)
@@ -233,7 +232,7 @@ def log_row(action, mean, num_calls, total, per):
                 output_string += log_row("Action", "Mean duration (s)", "Num calls", "Total time (s)", "Percentage %")
                 output_string_len = len(output_string)
                 output_string += f"{sep}{'-' * output_string_len}"
-                report, total_duration = self.make_report()
+                report, total_duration = self._make_report()
                 output_string += log_row("Total", "-", "_", f"{total_duration:.5}", "100 %")
                 output_string += f"{sep}{'-' * output_string_len}"
                 for action, durations, duration_per in report:
@@ -265,7 +264,7 @@ class AdvancedProfiler(BaseProfiler):
     verbose and you should only use this if you want very detailed reports.
     """
 
-    def __init__(self, output_filename: Optional[str] = None, line_count_restriction: float = 1.0):
+    def __init__(self, output_filename: Optional[str] = None, line_count_restriction: float = 1.0) -> None:
         """
         Args:
             output_filename: optionally save profile results to file instead of printing
diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index 53b4920bd85ef..cc95146932382 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -1077,6 +1077,7 @@ def call_teardown_hook(self, model: LightningModule) -> None:
         else:
             state = None
 
+        self.profiler.teardown()
         self.teardown(stage=state)
         model.teardown(stage=state)
 
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 5221c0cbf7bf6..63d2334d1d068 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -316,3 +316,21 @@ def test_pytorch_profiler_nested_emit_nvtx(tmpdir):
         gpus=1,
     )
     trainer.fit(model)
+
+
+@pytest.mark.parametrize("cls", (SimpleProfiler, AdvancedProfiler, PyTorchProfiler))
+def test_profiler_teardown(tmpdir, cls):
+    """
+    This test checks if profiler teardown method is called when trainer is exiting.
+    """
+    profiler = cls(output_filename=os.path.join(tmpdir, "profiler.txt"))
+
+    model = BoringModel()
+    trainer = Trainer(
+        default_root_dir=tmpdir,
+        fast_dev_run=True,
+        profiler=profiler,
+    )
+    trainer.fit(model)
+
+    assert profiler.output_file.closed

From ff125e211431d4d267e03c254a0f7c938f3c07f9 Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Mon, 22 Mar 2021 02:23:34 +0100
Subject: [PATCH 36/87] Unused import

---
 pytorch_lightning/profiler/pytorch.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index 30c553ee46e57..fdd838517fd71 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -22,7 +22,6 @@
 
 from pytorch_lightning.profiler.profilers import BaseProfiler
 from pytorch_lightning.utilities import rank_zero_only
-from pytorch_lightning.utilities.cloud_io import get_filesystem
 from pytorch_lightning.utilities.distributed import rank_zero_warn
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 

From 01a760e7a42ae0686a67ca80b5f06188e5f7f9f7 Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Mon, 22 Mar 2021 02:50:09 +0100
Subject: [PATCH 37/87] Introduce setup

---
 pytorch_lightning/profiler/profilers.py       | 53 +++++++++----------
 pytorch_lightning/profiler/pytorch.py         | 12 ++---
 .../trainer/connectors/profiler_connector.py  |  4 --
 pytorch_lightning/trainer/trainer.py          |  3 ++
 pytorch_lightning/trainer/training_loop.py    |  3 --
 tests/test_profiler.py                        |  2 +-
 6 files changed, 33 insertions(+), 44 deletions(-)

diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index 8c573ab1c7e31..6ca9b8446e08a 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -45,6 +45,9 @@ def stop(self, action_name: str) -> None:
     def summary(self) -> str:
         """Create profiler summary in text format."""
 
+    def setup(self) -> None:
+        """Execute arbitrary pre-profiling set-up steps as defined by subclass."""
+
     def teardown(self) -> None:
         """Execute arbitrary post-profiling tear-down steps as defined by subclass."""
 
@@ -54,35 +57,13 @@ class BaseProfiler(AbstractProfiler):
     If you wish to write a custom profiler, you should inherit from this class.
     """
 
-    def __init__(
-        self,
-        output_filename: Optional[str] = None,
-        local_rank: Optional[int] = None,
-        log_dir: Optional[str] = None
-    ) -> None:
+    def __init__(self, output_filename: Optional[str] = None) -> None:
         self.output_fname = output_filename
         self.output_file = None
-        self._file_prepared = False
+        self.local_rank = None
+        self.log_dir = None
         self.write_streams = []
-        # the profiler can be used outside of lightning
-        # that's why we call `on_train_start` manually
-        self.on_train_start(local_rank=local_rank, log_dir=log_dir)
-
-    def on_train_start(self, local_rank: Optional[int] = None, log_dir: Optional[str] = None) -> None:
-        """
-        This function is used by the Trainer to inject local_rank with `DDP`
-        and `TensorBoardLogger` log_dir in the profiler.
-        """
-        self.local_rank = local_rank
-        self.log_dir = log_dir
-
-    def _prepare_file(self) -> None:
-        if not self._file_prepared:
-            if self.output_fname and self.output_file is None:
-                fs = get_filesystem(self.output_fname)
-                self.output_file = fs.open(self.output_fname, "w")
-            self.write_streams = [self.output_file.write] if self.output_file else [log.info]
-        self._file_prepared = True
+        self._file_prepared = False
 
     @contextmanager
     def profile(self, action_name: str) -> None:
@@ -115,6 +96,14 @@ def profile_iterable(self, iterable, action_name: str) -> None:
                 self.stop(action_name)
                 break
 
+    def _prepare_file(self) -> None:
+        if not self._file_prepared:
+            if self.output_fname and self.output_file is None:
+                fs = get_filesystem(self.output_fname)
+                self.output_file = fs.open(self.output_fname, "w")
+            self.write_streams = [self.output_file.write] if self.output_file else [log.info]
+        self._file_prepared = True
+
     def describe(self) -> None:
         """Logs a profile report after the conclusion of the training run."""
         self._prepare_file()
@@ -124,7 +113,7 @@ def describe(self) -> None:
             self.output_file.flush()
         self.teardown()
 
-    def stats_to_str(self, stats: Dict[str, str]) -> str:
+    def _stats_to_str(self, stats: Dict[str, str]) -> str:
         output = ["Profiler Report"]
         for action, value in stats.items():
             header = f"Profile stats for: {action}"
@@ -134,6 +123,14 @@ def stats_to_str(self, stats: Dict[str, str]) -> str:
             output.append(value)
         return os.linesep.join(output)
 
+    def setup(self, local_rank: Optional[int] = None, log_dir: Optional[str] = None) -> None:
+        """
+        This function is used by the Trainer to inject local_rank with `DDP`
+        and `TensorBoardLogger` log_dir in the profiler.
+        """
+        self.local_rank = local_rank
+        self.log_dir = log_dir
+
     def teardown(self) -> None:
         """Close profiler's stream."""
         if self.output_file:
@@ -299,4 +296,4 @@ def summary(self) -> str:
             ps = pstats.Stats(pr, stream=s).strip_dirs().sort_stats('cumulative')
             ps.print_stats(self.line_count_restriction)
             recorded_stats[action_name] = s.getvalue()
-        return self.stats_to_str(recorded_stats)
+        return self._stats_to_str(recorded_stats)
diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index fdd838517fd71..1f8d68b2c6375 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -60,7 +60,6 @@ def __init__(
         row_limit: int = 20,
         sort_by_key: Optional[str] = None,
         profiled_functions: Optional[List] = None,
-        local_rank: Optional[int] = None,
     ):
         """
         This profiler uses PyTorch's Autograd Profiler and lets you inspect the cost of
@@ -115,9 +114,6 @@ def __init__(
             profiled_functions: list of profiled functions which will create a context manager on.
                 Any other will be pass through.
 
-            local_rank: When running in distributed setting, local_rank is used for each process
-                to write to their own file if `output_fname` is provided.
-
         Raises:
             MisconfigurationException:
                 If arg ``sort_by_key`` is not present in ``AVAILABLE_SORT_KEYS``, or
@@ -158,10 +154,10 @@ def __init__(
         self.running_stack = []
         self.profiler = None
 
-        super().__init__(output_filename=output_filename, local_rank=local_rank)
+        super().__init__(output_filename=output_filename)
 
-    def on_train_start(self, local_rank: Optional[int] = None, log_dir: Optional[str] = None) -> None:
-        super().on_train_start(local_rank=local_rank, log_dir=log_dir)
+    def setup(self, local_rank: Optional[int] = None, log_dir: Optional[str] = None) -> None:
+        super().setup(local_rank=local_rank, log_dir=log_dir)
 
         # if the user didn't provide `path_to_export_trace`,
         # set it as TensorBoardLogger log_dir if exists
@@ -271,4 +267,4 @@ def summary(self) -> str:
                 table = data.table(sort_by=self.sort_by_key, row_limit=self.row_limit)
                 recorded_stats[action_name] = table
 
-        return self.stats_to_str(recorded_stats)
+        return self._stats_to_str(recorded_stats)
diff --git a/pytorch_lightning/trainer/connectors/profiler_connector.py b/pytorch_lightning/trainer/connectors/profiler_connector.py
index 98d65c1285ff7..efb58fc844696 100644
--- a/pytorch_lightning/trainer/connectors/profiler_connector.py
+++ b/pytorch_lightning/trainer/connectors/profiler_connector.py
@@ -53,7 +53,3 @@ def on_trainer_init(self, profiler: Union[BaseProfiler, str]):
                     " `Trainer`, it can only be 'simple' or 'advanced'"
                 )
         self.trainer.profiler = profiler or PassThroughProfiler()
-
-    def on_train_start(self, trainer):
-        local_rank = trainer.local_rank if trainer.world_size > 1 else None
-        self.trainer.profiler.on_train_start(local_rank)
diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index cc95146932382..c8f3a0c435c66 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -1068,6 +1068,9 @@ def call_setup_hook(self, model: LightningModule) -> None:
             if not called:
                 self.datamodule.setup(stage=state)
 
+        local_rank = self.local_rank if self.world_size > 1 else None
+        self.profiler.setup(local_rank=local_rank)
+
         self.setup(model, stage=state)
         model.setup(stage=state)
 
diff --git a/pytorch_lightning/trainer/training_loop.py b/pytorch_lightning/trainer/training_loop.py
index 7e737c424ff26..f56fd6bd0567d 100644
--- a/pytorch_lightning/trainer/training_loop.py
+++ b/pytorch_lightning/trainer/training_loop.py
@@ -102,9 +102,6 @@ def on_train_start(self):
         # hook
         self.trainer.call_hook("on_train_start")
 
-        # provide rank to profiler
-        self.trainer.profile_connector.on_train_start(self.trainer)
-
     def setup_fit(self, model, train_dataloader=None, val_dataloaders=None, datamodule=None):
         # clean hparams
         if hasattr(model, "hparams"):
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 63d2334d1d068..aafe45ba7d5ad 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -196,7 +196,7 @@ def test_advanced_profiler_value_errors(advanced_profiler):
 
 @pytest.fixture
 def pytorch_profiler(tmpdir):
-    profiler = PyTorchProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"), local_rank=0)
+    profiler = PyTorchProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"))
     return profiler
 
 

From b31831e26fb59095a7b3f70251c0b9217f2c9f98 Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Mon, 22 Mar 2021 04:05:45 +0100
Subject: [PATCH 38/87] Profile on all ranks. Print to stdout on 0

---
 pytorch_lightning/profiler/profilers.py |  9 +++++----
 pytorch_lightning/profiler/pytorch.py   | 10 ----------
 2 files changed, 5 insertions(+), 14 deletions(-)

diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index 6ca9b8446e08a..0bcd93edbefe2 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -96,12 +96,13 @@ def profile_iterable(self, iterable, action_name: str) -> None:
                 self.stop(action_name)
                 break
 
+    def _rank_zero_info(self, *args, **kwargs) -> None:
+        if self.local_rank in (None, 0):
+            log.info(*args, **kwargs)
+
     def _prepare_file(self) -> None:
         if not self._file_prepared:
-            if self.output_fname and self.output_file is None:
-                fs = get_filesystem(self.output_fname)
-                self.output_file = fs.open(self.output_fname, "w")
-            self.write_streams = [self.output_file.write] if self.output_file else [log.info]
+            self.write_streams = [self.output_file.write] if self.output_file else [self._rank_zero_info]
         self._file_prepared = True
 
     def describe(self) -> None:
diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index 1f8d68b2c6375..11ac03b914620 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -164,16 +164,6 @@ def setup(self, local_rank: Optional[int] = None, log_dir: Optional[str] = None)
         if self.path_to_export_trace is None:
             self.path_to_export_trace = log_dir
 
-        # when logging to `log.info`, only perform profiling on rank 0
-        if local_rank is not None and local_rank > 0 and self.output_fname is None:
-            self._rank_zero_only_wrap()
-
-    def _rank_zero_only_wrap(self) -> None:
-        self.start = rank_zero_only(self.start)
-        self.stop = rank_zero_only(self.stop)
-        self.summary = rank_zero_only(self.summary)
-        self.describe = rank_zero_only(self.describe)
-
     def start(self, action_name: str) -> None:
         if action_name not in self.profiled_functions:
             return

From f8a87723dfee1b4079888b61112b1d9f19e65304 Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Mon, 22 Mar 2021 04:27:18 +0100
Subject: [PATCH 39/87] Introduce dirpath + filename

---
 pytorch_lightning/profiler/profilers.py | 63 ++++++++++++++++++++-----
 pytorch_lightning/profiler/pytorch.py   | 18 +++----
 pytorch_lightning/trainer/trainer.py    |  2 +-
 tests/deprecated_api/test_remove_1-5.py | 10 ++++
 tests/test_profiler.py                  | 53 +++++++--------------
 5 files changed, 91 insertions(+), 55 deletions(-)

diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index 0bcd93edbefe2..73e83ff32fdaa 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -21,10 +21,12 @@
 from abc import ABC, abstractmethod
 from collections import defaultdict
 from contextlib import contextmanager
-from typing import Dict, Optional, Tuple
+from pathlib import Path
+from typing import Dict, Optional, Tuple, Union
 
 import numpy as np
 
+from pytorch_lightning.utilities import rank_zero_warn
 from pytorch_lightning.utilities.cloud_io import get_filesystem
 
 log = logging.getLogger(__name__)
@@ -57,8 +59,23 @@ class BaseProfiler(AbstractProfiler):
     If you wish to write a custom profiler, you should inherit from this class.
     """
 
-    def __init__(self, output_filename: Optional[str] = None) -> None:
-        self.output_fname = output_filename
+    def __init__(
+        self,
+        dirpath: Optional[Union[str, Path]] = None,
+        filename: Optional[str] = None,
+        output_filename: Optional[str] = None,
+    ) -> None:
+        self.dirpath = dirpath
+        self.filename = filename
+        if output_filename is not None:
+            rank_zero_warn(
+                "`Profiler` signature has changed in v1.3. The `output_filename` parameter has been removed in"
+                " favor of `dirpath` and `filename`. Support for the old signature will be removed in v1.5",
+                DeprecationWarning
+            )
+            filepath = Path(output_filename)
+            self.dirpath = filepath.parent
+            self.filename = filepath.name
         self.output_file = None
         self.local_rank = None
         self.log_dir = None
@@ -102,6 +119,11 @@ def _rank_zero_info(self, *args, **kwargs) -> None:
 
     def _prepare_file(self) -> None:
         if not self._file_prepared:
+            if self.filename and self.output_file is None:
+                dirpath = self.dirpath or self.log_dir
+                filepath = os.path.join(dirpath, self.filename)
+                fs = get_filesystem(filepath)
+                self.output_file = fs.open(filepath, "a")
             self.write_streams = [self.output_file.write] if self.output_file else [self._rank_zero_info]
         self._file_prepared = True
 
@@ -177,11 +199,20 @@ class SimpleProfiler(BaseProfiler):
     the mean duration of each action and the total time spent over the entire training run.
     """
 
-    def __init__(self, output_filename: Optional[str] = None, extended: bool = True) -> None:
+    def __init__(
+        self,
+        dirpath: Optional[Union[str, Path]] = None,
+        filename: Optional[str] = None,
+        extended: bool = True,
+        output_filename: Optional[str] = None,
+    ) -> None:
         """
         Args:
-            output_filename: optionally save profile results to file instead of printing
-                to std out when training is finished.
+            dirpath: Directory path for the ``filename``. If ``dirpath`` is ``None`` but ``filename`` is present, the
+                ``trainer.log_dir`` (from :class:`~pytorch_lightning.loggers.tensorboard.TensorBoardLogger`)
+                will be used.
+
+            filename: If present, filename where the profiler results will be saved instead of printing to stdout.
 
         Raises:
             ValueError:
@@ -191,7 +222,7 @@ def __init__(self, output_filename: Optional[str] = None, extended: bool = True)
         self.current_actions: Dict[str, float] = {}
         self.recorded_durations = defaultdict(list)
         self.extended = extended
-        super().__init__(output_filename=output_filename)
+        super().__init__(dirpath=dirpath, filename=filename, output_filename=output_filename)
         self.start_time = time.monotonic()
 
     def start(self, action_name: str) -> None:
@@ -262,11 +293,21 @@ class AdvancedProfiler(BaseProfiler):
     verbose and you should only use this if you want very detailed reports.
     """
 
-    def __init__(self, output_filename: Optional[str] = None, line_count_restriction: float = 1.0) -> None:
+    def __init__(
+        self,
+        dirpath: Optional[Union[str, Path]] = None,
+        filename: Optional[str] = None,
+        line_count_restriction: float = 1.0,
+        output_filename: Optional[str] = None,
+    ) -> None:
         """
         Args:
-            output_filename: optionally save profile results to file instead of printing
-                to std out when training is finished.
+            dirpath: Directory path for the ``filename``. If ``dirpath`` is ``None`` but ``filename`` is present, the
+                ``trainer.log_dir`` (from :class:`~pytorch_lightning.loggers.tensorboard.TensorBoardLogger`)
+                will be used.
+
+            filename: If present, filename where the profiler results will be saved instead of printing to stdout.
+
             line_count_restriction: this can be used to limit the number of functions
                 reported for each action. either an integer (to select a count of lines),
                 or a decimal fraction between 0.0 and 1.0 inclusive (to select a percentage of lines)
@@ -275,7 +316,7 @@ def __init__(self, output_filename: Optional[str] = None, line_count_restriction
             ValueError:
                 If you attempt to stop recording an action which was never started.
         """
-        super().__init__(output_filename=output_filename)
+        super().__init__(dirpath=dirpath, filename=filename, output_filename=output_filename)
         self.profiled_actions = {}
         self.line_count_restriction = line_count_restriction
 
diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index 11ac03b914620..8357d110663b2 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -16,12 +16,12 @@
 import inspect
 import logging
 import os
-from typing import List, Optional
+from pathlib import Path
+from typing import List, Optional, Union
 
 import torch
 
 from pytorch_lightning.profiler.profilers import BaseProfiler
-from pytorch_lightning.utilities import rank_zero_only
 from pytorch_lightning.utilities.distributed import rank_zero_warn
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 
@@ -45,7 +45,8 @@ class PyTorchProfiler(BaseProfiler):
 
     def __init__(
         self,
-        output_filename: Optional[str] = None,
+        dirpath: Optional[Union[str, Path]] = None,
+        filename: Optional[str] = None,
         enabled: bool = True,
         use_cuda: bool = False,
         record_shapes: bool = False,
@@ -60,17 +61,18 @@ def __init__(
         row_limit: int = 20,
         sort_by_key: Optional[str] = None,
         profiled_functions: Optional[List] = None,
+        output_filename: Optional[str] = None,
     ):
         """
         This profiler uses PyTorch's Autograd Profiler and lets you inspect the cost of
         different operators inside your model - both on the CPU and GPU
 
         Args:
+            dirpath: Directory path for the ``filename``. If ``dirpath`` is ``None`` but ``filename`` is present, the
+                ``trainer.log_dir`` (from :class:`~pytorch_lightning.loggers.tensorboard.TensorBoardLogger`)
+                will be used.
 
-            output_filename: optionally save profile results to file instead of printing
-                to std out when training is finished. When using ``ddp``,
-                each rank will stream the profiled operation to their own file
-                with the extension ``_{rank}.txt``
+            filename: If present, filename where the profiler results will be saved instead of printing to stdout.
 
             enabled: Setting this to False makes this context manager a no-op.
 
@@ -154,7 +156,7 @@ def __init__(
         self.running_stack = []
         self.profiler = None
 
-        super().__init__(output_filename=output_filename)
+        super().__init__(dirpath=dirpath, filename=filename, output_filename=output_filename)
 
     def setup(self, local_rank: Optional[int] = None, log_dir: Optional[str] = None) -> None:
         super().setup(local_rank=local_rank, log_dir=log_dir)
diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index c8f3a0c435c66..580a9de22fd53 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -1069,7 +1069,7 @@ def call_setup_hook(self, model: LightningModule) -> None:
                 self.datamodule.setup(stage=state)
 
         local_rank = self.local_rank if self.world_size > 1 else None
-        self.profiler.setup(local_rank=local_rank)
+        self.profiler.setup(local_rank=local_rank, log_dir=self.log_dir)
 
         self.setup(model, stage=state)
         model.setup(stage=state)
diff --git a/tests/deprecated_api/test_remove_1-5.py b/tests/deprecated_api/test_remove_1-5.py
index f449a37e33c25..6f2c65c7a1171 100644
--- a/tests/deprecated_api/test_remove_1-5.py
+++ b/tests/deprecated_api/test_remove_1-5.py
@@ -20,6 +20,7 @@
 from pytorch_lightning import Callback, Trainer
 from pytorch_lightning.callbacks import ModelCheckpoint
 from pytorch_lightning.loggers import WandbLogger
+from pytorch_lightning.profiler import BaseProfiler, SimpleProfiler, AdvancedProfiler, PyTorchProfiler
 from pytorch_lightning.trainer.callback_hook import warning_cache as callback_warning_cache
 from tests.deprecated_api import no_deprecated_call
 from tests.helpers import BoringModel
@@ -203,3 +204,12 @@ def on_test_epoch_end(self, outputs):
     model = NewSignatureModel()
     with no_deprecated_call(match="`ModelHooks.on_test_epoch_end` signature has changed in v1.3."):
         trainer.test(model)
+
+
+@pytest.mark.parametrize("cls", (BaseProfiler, SimpleProfiler, AdvancedProfiler, PyTorchProfiler))
+def test_v1_5_0_profiler_output_filename(tmpdir, cls):
+    filepath = str(tmpdir / "test")
+    with pytest.deprecated_call(match="`output_filename` parameter has been removed"):
+        profiler = cls(output_filename=filepath)
+    assert profiler.dirpath == tmpdir
+    assert profiler.filename == "test"
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index aafe45ba7d5ad..e16ad96992fda 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -12,10 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import logging
-import os
 import time
 from distutils.version import LooseVersion
-from pathlib import Path
 
 import numpy as np
 import pytest
@@ -45,8 +43,7 @@ def _sleep_generator(durations):
 
 @pytest.fixture
 def simple_profiler():
-    profiler = SimpleProfiler()
-    return profiler
+    return SimpleProfiler()
 
 
 @pytest.mark.parametrize(["action", "expected"], [
@@ -117,8 +114,7 @@ def test_simple_profiler_value_errors(simple_profiler):
 
 @pytest.fixture
 def advanced_profiler(tmpdir):
-    profiler = AdvancedProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"))
-    return profiler
+    return AdvancedProfiler(dirpath=tmpdir, filename="profiler.txt")
 
 
 @pytest.mark.parametrize(["action", "expected"], [
@@ -179,7 +175,8 @@ def test_advanced_profiler_describe(tmpdir, advanced_profiler):
         pass
     # log to stdout and print to file
     advanced_profiler.describe()
-    data = Path(advanced_profiler.output_fname).read_text()
+    path = advanced_profiler.dirpath / advanced_profiler.filename
+    data = path.read_text("utf-8")
     assert len(data) > 0
 
 
@@ -196,8 +193,7 @@ def test_advanced_profiler_value_errors(advanced_profiler):
 
 @pytest.fixture
 def pytorch_profiler(tmpdir):
-    profiler = PyTorchProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"))
-    return profiler
+    return PyTorchProfiler(dirpath=tmpdir, filename="profiler.txt")
 
 
 def test_pytorch_profiler_describe(pytorch_profiler):
@@ -207,7 +203,8 @@ def test_pytorch_profiler_describe(pytorch_profiler):
 
     # log to stdout and print to file
     pytorch_profiler.describe()
-    data = Path(pytorch_profiler.output_fname).read_text()
+    path = pytorch_profiler.dirpath / pytorch_profiler.filename
+    data = path.read_text("utf-8")
     assert len(data) > 0
 
 
@@ -223,46 +220,32 @@ def test_pytorch_profiler_value_errors(pytorch_profiler):
 
 
 @RunIf(min_gpus=2, special=True)
-@pytest.mark.parametrize("use_output_filename", [False, True])
-def test_pytorch_profiler_trainer_ddp(tmpdir, use_output_filename):
+def test_pytorch_profiler_trainer_ddp(tmpdir, pytorch_profiler):
     """Ensure that the profiler can be given to the training and default step are properly recorded. """
-
-    if use_output_filename:
-        output_filename = os.path.join(tmpdir, "profiler.txt")
-    else:
-        output_filename = None
-
-    profiler = PyTorchProfiler(output_filename=output_filename)
-
     model = BoringModel()
     trainer = Trainer(
+        default_root_dir=tmpdir,
         fast_dev_run=True,
-        profiler=profiler,
+        profiler=pytorch_profiler,
         accelerator="ddp",
         gpus=2,
     )
     trainer.fit(model)
 
-    enabled = use_output_filename or not use_output_filename and profiler.local_rank == 0
-
-    if enabled:
-        assert len(profiler.summary()) > 0
-        assert set(profiler.profiled_actions.keys()) == {'training_step_and_backward', 'validation_step'}
-    else:
-        assert profiler.summary() is None
-        assert set(profiler.profiled_actions.keys()) == set()
+    assert len(pytorch_profiler.summary()) > 0
+    assert set(pytorch_profiler.profiled_actions.keys()) == {'training_step_and_backward', 'validation_step'}
 
-    if use_output_filename:
-        profiler.describe()
-        data = Path(profiler.output_fname).read_text()
-        assert len(data) > 0
+    pytorch_profiler.describe()
+    path = pytorch_profiler.dirpath / pytorch_profiler.filename
+    data = path.read_text("utf-8")
+    assert len(data) > 0
 
 
 def test_pytorch_profiler_nested(tmpdir):
     """Ensure that the profiler handles nested context"""
 
     pytorch_profiler = PyTorchProfiler(
-        profiled_functions=["a", "b", "c"], use_cuda=False, output_filename=os.path.join(tmpdir, "profiler.txt")
+        profiled_functions=["a", "b", "c"], use_cuda=False, dirpath=tmpdir, filename="profiler.txt"
     )
 
     with pytorch_profiler.profile("a"):
@@ -323,7 +306,7 @@ def test_profiler_teardown(tmpdir, cls):
     """
     This test checks if profiler teardown method is called when trainer is exiting.
     """
-    profiler = cls(output_filename=os.path.join(tmpdir, "profiler.txt"))
+    profiler = cls(dirpath=tmpdir, filename="profiler.txt")
 
     model = BoringModel()
     trainer = Trainer(

From aa4b7dd6026a5ec42f12c627719c5f8c3c99e19d Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Mon, 22 Mar 2021 04:34:23 +0100
Subject: [PATCH 40/87] CHANGELOG

---
 CHANGELOG.md | 9 +++++++++
 1 file changed, 9 insertions(+)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 6004a28dd0829..df15771d5aa8c 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -43,6 +43,12 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Added `Trainer.predict` config validation ([#6543](https://github.com/PyTorchLightning/pytorch-lightning/pull/6543))
 
 
+- Added `AbstractProfiler` interface ([#6621](https://github.com/PyTorchLightning/pytorch-lightning/pull/6621))
+
+
+- Added `setup` method to `BaseProfiler` to enable subclasses defining pre-profiling steps ([#6621](https://github.com/PyTorchLightning/pytorch-lightning/pull/6621))
+
+
 - Added `outputs` parameter to callback's `on_validation_epoch_end` & `on_test_epoch_end` hooks ([#6120](https://github.com/PyTorchLightning/pytorch-lightning/pull/6120))
 
 
@@ -68,6 +74,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Deprecated `trainer.running_sanity_check` in favor of `trainer.sanity_checking` ([#4945](https://github.com/PyTorchLightning/pytorch-lightning/pull/4945))
 
 
+- Deprecated `Profiler(output_filename)` in favor of `dirpath` and `filename` ([#6621](https://github.com/PyTorchLightning/pytorch-lightning/pull/6621))
+
+
 - Deprecated metrics in favor of `torchmetrics` ([#6505](https://github.com/PyTorchLightning/pytorch-lightning/pull/6505),
 
     [#6530](https://github.com/PyTorchLightning/pytorch-lightning/pull/6530),

From 8e3034e8f09e7296f417a118751015c8a3f2d1de Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Mon, 22 Mar 2021 04:47:56 +0100
Subject: [PATCH 41/87] Add tests. Address comments

---
 pytorch_lightning/profiler/profilers.py |  5 ++---
 tests/test_profiler.py                  | 19 +++++++++++++++++++
 2 files changed, 21 insertions(+), 3 deletions(-)

diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index 73e83ff32fdaa..9521ac439fbd6 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -148,8 +148,7 @@ def _stats_to_str(self, stats: Dict[str, str]) -> str:
 
     def setup(self, local_rank: Optional[int] = None, log_dir: Optional[str] = None) -> None:
         """
-        This function is used by the Trainer to inject local_rank with `DDP`
-        and `TensorBoardLogger` log_dir in the profiler.
+        This function is used by the Trainer to inject the local_rank on distributed and `TensorBoardLogger.log_dir`.
         """
         self.local_rank = local_rank
         self.log_dir = log_dir
@@ -219,10 +218,10 @@ def __init__(
                 If you attempt to start an action which has already started, or
                 if you attempt to stop recording an action which was never started.
         """
+        super().__init__(dirpath=dirpath, filename=filename, output_filename=output_filename)
         self.current_actions: Dict[str, float] = {}
         self.recorded_durations = defaultdict(list)
         self.extended = extended
-        super().__init__(dirpath=dirpath, filename=filename, output_filename=output_filename)
         self.start_time = time.monotonic()
 
     def start(self, action_name: str) -> None:
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index e16ad96992fda..28674c2769799 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -112,6 +112,25 @@ def test_simple_profiler_value_errors(simple_profiler):
     simple_profiler.stop(action)
 
 
+def test_simple_profiler_log_dir(tmpdir):
+    """Ensure the profiler dirpath defaults to `trainer.log_dir` when not present"""
+    profiler = SimpleProfiler(filename="profiler.txt")
+    assert profiler.log_dir is None
+
+    model = BoringModel()
+    trainer = Trainer(
+        default_root_dir=tmpdir,
+        max_epochs=1,
+        profiler=profiler,
+    )
+    trainer.fit(model)
+
+    expected = tmpdir / "lightning_logs" / "version_0"
+    assert trainer.log_dir == expected
+    assert profiler.log_dir == trainer.log_dir
+    assert expected.join("profiler.txt").exists()
+
+
 @pytest.fixture
 def advanced_profiler(tmpdir):
     return AdvancedProfiler(dirpath=tmpdir, filename="profiler.txt")

From e4e0dd6278a6d0a97c6286d04b7c24bcf0947f6f Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Mon, 22 Mar 2021 10:19:42 +0000
Subject: [PATCH 42/87] add `on_run_stage_setup`

---
 pytorch_lightning/plugins/training_type/horovod.py        | 7 +++----
 .../plugins/training_type/training_type_plugin.py         | 6 +++---
 pytorch_lightning/trainer/trainer.py                      | 8 ++++++++
 3 files changed, 14 insertions(+), 7 deletions(-)

diff --git a/pytorch_lightning/plugins/training_type/horovod.py b/pytorch_lightning/plugins/training_type/horovod.py
index 9f1bafe309f89..06ab7500dacc8 100644
--- a/pytorch_lightning/plugins/training_type/horovod.py
+++ b/pytorch_lightning/plugins/training_type/horovod.py
@@ -96,22 +96,21 @@ def start_training(self, trainer):
                 stack.enter_context(optimizer.skip_synchronize())
 
             # set up training routine
-            self._results = trainer.run_train()
+            self._results = trainer.run_stage()
 
         # Make sure all workers have finished training before returning to the user
         hvd.join()
 
     def start_evaluating(self, trainer):
         with ExitStack():
-            self._results = trainer.run_evaluate()
+            self._results = trainer.run_stage()
 
         # Make sure all workers have finished training before returning to the user
         hvd.join()
 
     def start_predicting(self, trainer):
         with ExitStack():
-            # set up training routine
-            self._results = trainer.run_predict()
+            self._results = trainer.run_stage()
 
         # Make sure all workers have finished training before returning to the user
         hvd.join()
diff --git a/pytorch_lightning/plugins/training_type/training_type_plugin.py b/pytorch_lightning/plugins/training_type/training_type_plugin.py
index 6a87792c7bd03..a00eefd77d129 100644
--- a/pytorch_lightning/plugins/training_type/training_type_plugin.py
+++ b/pytorch_lightning/plugins/training_type/training_type_plugin.py
@@ -132,15 +132,15 @@ def rpc_enabled(self) -> bool:
 
     def start_training(self, trainer: 'Trainer') -> None:
         # double dispatch to initiate the training loop
-        self._results = trainer.run_train()
+        self._results = trainer.run_stage()
 
     def start_evaluating(self, trainer: 'Trainer') -> None:
         # double dispatch to initiate the test loop
-        self._results = trainer.run_evaluate()
+        self._results = trainer.run_stage()
 
     def start_predicting(self, trainer: 'Trainer') -> None:
         # double dispatch to initiate the predicting loop
-        self._results = trainer.run_predict()
+        self._results = trainer.run_stage()
 
     def training_step(self, *args, **kwargs):
         return self.lightning_module.training_step(*args, **kwargs)
diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index 580a9de22fd53..dc346d441dc39 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -516,8 +516,16 @@ def dispatch(self):
         else:
             self.accelerator.start_training(self)
 
+    def on_run_stage_setup(self):
+        # setup profiler with the rank info and log_dir
+        local_rank = self.local_rank if self.world_size > 1 else None
+        self.profiler.setup(local_rank=local_rank, log_dir=self.log_dir)
+
     def run_stage(self):
         results = None
+
+        self.on_run_stage_setup()
+
         if self.evaluating:
             results = self.run_evaluate()
         elif self.predicting:

From d0fdbb9ddfdfe4b169479247505131acfdaf832b Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Mon, 22 Mar 2021 10:31:38 +0000
Subject: [PATCH 43/87] add on_run_stage_setup function

---
 pytorch_lightning/trainer/trainer.py | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index dc346d441dc39..a91454d627312 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -517,9 +517,7 @@ def dispatch(self):
             self.accelerator.start_training(self)
 
     def on_run_stage_setup(self):
-        # setup profiler with the rank info and log_dir
-        local_rank = self.local_rank if self.world_size > 1 else None
-        self.profiler.setup(local_rank=local_rank, log_dir=self.log_dir)
+        self.profiler.setup(local_rank=self.local_rank if self.world_size > 1 else None, log_dir=self.log_dir)
 
     def run_stage(self):
         results = None

From 1a16bb3e837944fafc34bdc99ba373f76e45a93e Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Mon, 22 Mar 2021 10:33:53 +0000
Subject: [PATCH 44/87] update

---
 pytorch_lightning/trainer/trainer.py | 3 ---
 1 file changed, 3 deletions(-)

diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index a91454d627312..b4d7fd6febc06 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -1074,9 +1074,6 @@ def call_setup_hook(self, model: LightningModule) -> None:
             if not called:
                 self.datamodule.setup(stage=state)
 
-        local_rank = self.local_rank if self.world_size > 1 else None
-        self.profiler.setup(local_rank=local_rank, log_dir=self.log_dir)
-
         self.setup(model, stage=state)
         model.setup(stage=state)
 

From 52fa69b182c2e16989d5d5a3951b066a0a67b5b3 Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Mon, 22 Mar 2021 11:06:14 +0000
Subject: [PATCH 45/87] add test for RegisterRecordFunction

---
 pytorch_lightning/profiler/pytorch.py | 41 +++++++++++++++------------
 tests/test_profiler.py                | 38 +++++++++++++++++++++++++
 2 files changed, 61 insertions(+), 18 deletions(-)

diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index 874a4e607c784..a5bbfffb4e6be 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -19,6 +19,7 @@
 from typing import Any, Dict, List, Optional, Type, Union
 
 import torch
+from torch import nn, Tensor
 from torch.autograd.profiler import EventList, record_function
 
 from pytorch_lightning.profiler.profilers import BaseProfiler
@@ -48,33 +49,31 @@ class RegisterRecordFunction:
             out = model(batch)
     """
 
-    def __init__(self, model):
+    def __init__(self, model: nn.Module):
         self._model = model
         self._records = {}
         self.handles = {}
 
-    def _start_recording_forward(self, module, input, module_name: str = None, is_built_in: bool = None):
-        if module_name is not None:
-            record_name = module_name if is_built_in else f"{type(module)}: {module_name}"
-            self._records[record_name] = record_function(record_name).__enter__()
+    def _start_recording_forward(self, module: nn.Module, input: Tensor, record_name: str):
+        record = record_function(record_name)
+        record.__enter__()
+        self._records[record_name] = record
         return input
 
-    def _stop_recording_forward(self, module, input, result, module_name: str = None, is_built_in: bool = None):
-        if module_name is not None:
-            record_name = module_name if is_built_in else f"{type(module)}: {module_name}"
-            self._records[record_name].__exit__(None, None, None)
-        return result
+    def _stop_recording_forward(self, module: nn.Module, input: Tensor, output: Tensor, record_name: str):
+        self._records[record_name].__exit__(None, None, None)
+        return output
 
     def __enter__(self):
-        built_in_modules = dir(torch.nn)
         for module_name, module in self._model.named_modules():
             if module_name != '':
-                is_built_in = module in built_in_modules
+                full_name = type(module).__module__ + '.' + type(module).__name__
+                record_name = f"{full_name}: {module_name}"
                 pre_forward_handle = module.register_forward_pre_hook(
-                    partial(self._start_recording_forward, module_name=module_name, is_built_in=is_built_in)
+                    partial(self._start_recording_forward, record_name=record_name)
                 )
                 post_forward_handle = module.register_forward_hook(
-                    partial(self._stop_recording_forward, module_name=module_name, is_built_in=is_built_in)
+                    partial(self._stop_recording_forward, record_name=record_name)
                 )
 
                 self.handles[module_name] = [pre_forward_handle, post_forward_handle]
@@ -112,9 +111,9 @@ def __init__(
         path_to_export_trace: Optional[str] = None,
         row_limit: int = 20,
         sort_by_key: Optional[str] = None,
-        record_functions: List[str] = [],
+        record_functions: List[str] = None,
         local_rank: Optional[int] = None,
-        profiled_functions: List[str] = [],
+        profiled_functions: List[str] = None,
         record_module_names: bool = True,
         **profiler_kwargs: Any,
     ) -> None:
@@ -146,7 +145,7 @@ def __init__(
             path_to_export_trace: Directory path to export ``.json`` traces when using ``export_to_chrome=True``.
                 By default, it will be save where the file being is being run.
 
-            row_limit: Limit the number of rows in a table, ``0`` is a special value that
+            row_limit: Limit the number of rows in a table, ``-1`` is a special value that
                 removes the limit completely.
 
             sort_by_key: Attribute used to sort entries. By default
@@ -178,7 +177,7 @@ def __init__(
         record_functions = self.__deprecation_check(profiled_functions, record_functions)
 
         self.output_fname = output_filename
-        self.record_functions = record_functions + list(self.RECORD_FUNCTIONS)
+        self.record_functions = set(record_functions + list(self.RECORD_FUNCTIONS))
         self.sort_by_key = sort_by_key or f"{'cuda' if profiler_kwargs.get('use_cuda', False) else 'cpu'}_time_total"
         self.group_by_input_shapes = group_by_input_shapes and profiler_kwargs.get("record_shapes", False)
         self.row_limit = row_limit
@@ -211,6 +210,9 @@ def __init__(
         super().__init__(output_filename=output_filename, local_rank=local_rank)
 
     def __deprecation_check(self, profiled_functions: List[str] = [], record_functions: List[str] = []) -> List[str]:
+        if record_functions is None:
+            record_functions = []
+
         if profiled_functions is not None:
             rank_zero_warn(
                 "`PyTorchProfiler.profiled_functions` has been renamed to"
@@ -223,6 +225,9 @@ def __deprecation_check(self, profiled_functions: List[str] = [], record_functio
                     "You set `PytorchProfiler.profiled_functions` and `PyTorchProfiler.record_functions`."
                     "  Please use only the later."
                 )
+        if record_functions is None:
+            record_functions = []
+
         return record_functions
 
     def on_train_start(self, local_rank: Optional[int] = None, log_dir: Optional[str] = None) -> None:
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 7a95bb6bbb75a..2fcf825292e66 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -25,6 +25,7 @@
 from pytorch_lightning import Trainer
 from pytorch_lightning.loggers import TensorBoardLogger
 from pytorch_lightning.profiler import AdvancedProfiler, PyTorchProfiler, SimpleProfiler
+from pytorch_lightning.profiler.pytorch import RegisterRecordFunction
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from tests.helpers import BoringModel
 from tests.helpers.runif import RunIf
@@ -354,3 +355,40 @@ def test_pytorch_profiler_nested_emit_nvtx(tmpdir):
         gpus=1,
     )
     trainer.fit(model)
+
+
+@RunIf(min_torch="1.5.0")
+def test_register_record_function(tmpdir):
+
+    use_cuda = torch.cuda.is_available()
+
+    pytorch_profiler = PyTorchProfiler(
+        export_to_chrome=False,
+        record_functions=["a"],
+        use_cuda=use_cuda,
+        output_filename=os.path.join(tmpdir, "profiler.txt")
+    )
+
+    class TestModel(BoringModel):
+
+        def __init__(self):
+            super().__init__()
+            self.layer = torch.nn.Sequential(torch.nn.Linear(32, 32), torch.nn.ReLU(), torch.nn.Linear(32, 2))
+
+    model = TestModel()
+    input = torch.rand((1, 32))
+
+    if use_cuda:
+        model = model.cuda()
+        input = input.cuda()
+
+    with pytorch_profiler.profile("a"):
+        with RegisterRecordFunction(model):
+            model(input)
+
+    pytorch_profiler.describe()
+    event_names = [e.name for e in pytorch_profiler.function_events]
+    assert 'torch.nn.modules.container.Sequential: layer' in event_names
+    assert 'torch.nn.modules.linear.Linear: layer.0' in event_names
+    assert 'torch.nn.modules.activation.ReLU: layer.1' in event_names
+    assert 'torch.nn.modules.linear.Linear: layer.2' in event_names

From 63b6988f2fc495c2c17fa2fc3305aabb380c6404 Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Mon, 22 Mar 2021 11:10:57 +0000
Subject: [PATCH 46/87] update lightnng flow direction

---
 0_trace.json                         |  1 +
 pytorch_lightning/trainer/trainer.py | 18 ++++++++++--------
 2 files changed, 11 insertions(+), 8 deletions(-)
 create mode 100644 0_trace.json

diff --git a/0_trace.json b/0_trace.json
new file mode 100644
index 0000000000000..2b9487adf83a1
--- /dev/null
+++ b/0_trace.json
@@ -0,0 +1 @@
+[{"name": "aten::empty", "ph": "X", "ts": 434.706, "dur": 4.123999999999967, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::random_", "ph": "X", "ts": 460.465, "dur": 8.160000000000025, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::is_floating_point", "ph": "X", "ts": 517.229, "dur": 0.5319999999999254, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::item", "ph": "X", "ts": 521.148, "dur": 4.944999999999936, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::_local_scalar_dense", "ph": "X", "ts": 523.151, "dur": 2.3920000000000528, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::zeros", "ph": "X", "ts": 550.11, "dur": 6.506999999999948, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 552.022, "dur": 1.8149999999999409, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::zero_", "ph": "X", "ts": 555.346, "dur": 0.8869999999999436, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "enumerate(DataLoader)#_SingleProcessDataLoaderIter.__next__", "ph": "X", "ts": 570.759, "dur": 90.41200000000003, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 572.027, "dur": 1.2229999999999563, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::select", "ph": "X", "ts": 590.516, "dur": 7.359000000000037, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 593.307, "dur": 1.2479999999999336, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::stack", "ph": "X", "ts": 611.293, "dur": 18.946000000000026, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::unsqueeze", "ph": "X", "ts": 614.671, "dur": 2.647999999999911, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 615.849, "dur": 0.8669999999999618, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::cat", "ph": "X", "ts": 618.48, 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"aten::linear", "ph": "X", "ts": 13933.401, "dur": 22.036000000000058, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::t", "ph": "X", "ts": 13934.361, "dur": 5.274999999999636, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::transpose", "ph": "X", "ts": 13935.675, "dur": 2.5310000000008586, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 13936.598, "dur": 1.0229999999992287, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::addmm", "ph": "X", "ts": 13940.381, "dur": 14.26300000000083, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 13941.784, "dur": 0.7049999999999272, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::expand", "ph": "X", "ts": 13943.373, "dur": 2.015000000001237, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 13944.484, "dur": 0.4709999999995489, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::copy_", "ph": "X", "ts": 13949.232, "dur": 3.105999999999767, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::zeros", "ph": "X", "ts": 13986.665, "dur": 3.580999999998312, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 13987.536, "dur": 1.1559999999990396, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::zero_", "ph": "X", "ts": 13989.544, "dur": 0.3850000000002183, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "enumerate(DataLoader)#_SingleProcessDataLoaderIter.__next__", "ph": "X", "ts": 13995.88, "dur": 10.150000000001455, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 13996.686, "dur": 0.9040000000004511, "tid": 1, "pid": "CPU functions", "args": {}}]
diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index b4d7fd6febc06..4500053719294 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -445,13 +445,15 @@ def fit(
                                 |                             ||
                          {self.dispatch}                      ||
                                 |                             ||  LIGHTNING
-                {self.accelerator.start_training} or          ||
-                {self.accelerator.start_evaluating} or        ||  FLOW
-                {self.accelerator.start_predicting}           ||
+                {self.accelerator.start_training}             ||
+                or {self.accelerator.start_evaluating}        ||
+                or {self.accelerator.start_predicting}        ||  FLOW
+                                |                             ||
+                         {self.run_stage}                     ||
                                 |                             ||  DIRECTION
-                        {self.run_train} or                   ||
-                     {self.run_evaluation} or                 ||
-                       {self.run_predict}                     ||
+                        {self.run_train}                      ||
+                     or {self.run_evaluation}                 ||
+                     or  {self.run_predict}                   ||
                                 |                             ||
                              results                          \/
         This is used to guide readers to the core loops: train, test, predict.
@@ -516,13 +518,13 @@ def dispatch(self):
         else:
             self.accelerator.start_training(self)
 
-    def on_run_stage_setup(self):
+    def _on_run_stage_setup(self):
         self.profiler.setup(local_rank=self.local_rank if self.world_size > 1 else None, log_dir=self.log_dir)
 
     def run_stage(self):
         results = None
 
-        self.on_run_stage_setup()
+        self._on_run_stage_setup()
 
         if self.evaluating:
             results = self.run_evaluate()

From 1cf5a6422c2d5be6bb2df3bd36aa040c8ec015e2 Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Mon, 22 Mar 2021 11:21:42 +0000
Subject: [PATCH 47/87] move variable to private

---
 pytorch_lightning/profiler/pytorch.py | 91 +++++++++++++--------------
 1 file changed, 45 insertions(+), 46 deletions(-)

diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index a5bbfffb4e6be..e81b79faec74f 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -177,36 +177,35 @@ def __init__(
         record_functions = self.__deprecation_check(profiled_functions, record_functions)
 
         self.output_fname = output_filename
-        self.record_functions = set(record_functions + list(self.RECORD_FUNCTIONS))
-        self.sort_by_key = sort_by_key or f"{'cuda' if profiler_kwargs.get('use_cuda', False) else 'cpu'}_time_total"
-        self.group_by_input_shapes = group_by_input_shapes and profiler_kwargs.get("record_shapes", False)
-        self.row_limit = row_limit
-        self.emit_nvtx = emit_nvtx
-        self.export_to_chrome = export_to_chrome
-        self.path_to_export_trace = path_to_export_trace
-        self.record_module_names = record_module_names
-        self.lightning_module = None  # set by ProfilerConnector
-        self.register = None
-        self.profiler_kwargs = profiler_kwargs
-        self.profiler = None
+        self.profiler: Optional[_PROFILER] = None
+        self.function_events: Optional[EventList] = None
+
+        self._record_functions = set(record_functions + list(self.RECORD_FUNCTIONS))
+        self._sort_by_key = sort_by_key or f"{'cuda' if profiler_kwargs.get('use_cuda', False) else 'cpu'}_time_total"
+        self._group_by_input_shapes = group_by_input_shapes and profiler_kwargs.get("record_shapes", False)
+        self._row_limit = row_limit
+        self._emit_nvtx = emit_nvtx
+        self._export_to_chrome = export_to_chrome
+        self._path_to_export_trace = path_to_export_trace
+        self._record_module_names = record_module_names
+        self._lightning_module = None  # set by ProfilerConnector
+        self._register = None
+        self._profiler_kwargs = profiler_kwargs
         self._parent_profiler = None
+        self._recording_map: Dict[str, record_function] = {}
+        self._profiler_instantiated: bool = False
 
-        if self.export_to_chrome and self.path_to_export_trace is None:
+        if self._export_to_chrome and self._path_to_export_trace is None:
             rank_zero_warn(
                 "The exported trace would be saved locally as `path_to_export_trace` is None."
                 " Note: Each functions will generate its own traced file."
             )
 
-        if self.sort_by_key not in self.AVAILABLE_SORT_KEYS:
+        if self._sort_by_key not in self.AVAILABLE_SORT_KEYS:
             raise MisconfigurationException(
-                f"Found sort_by_key: {self.sort_by_key}. Should be within {self.AVAILABLE_SORT_KEYS}. "
+                f"Found sort_by_key: {self._sort_by_key}. Should be within {self.AVAILABLE_SORT_KEYS}. "
             )
 
-        self.recording_map: Dict[str, record_function] = {}
-        self.profiler: Optional[_PROFILER] = None
-        self.function_events: Optional[EventList] = None
-        self._profiler_instantiated: bool = False
-
         super().__init__(output_filename=output_filename, local_rank=local_rank)
 
     def __deprecation_check(self, profiled_functions: List[str] = [], record_functions: List[str] = []) -> List[str]:
@@ -235,8 +234,8 @@ def on_train_start(self, local_rank: Optional[int] = None, log_dir: Optional[str
 
         # if the user didn't provide `path_to_export_trace`,
         # set it as TensorBoardLogger log_dir if exists
-        if self.path_to_export_trace is None:
-            self.path_to_export_trace = log_dir
+        if self._path_to_export_trace is None:
+            self._path_to_export_trace = log_dir
 
         # when logging to `log.info`, only perform profiling on rank 0
         if local_rank is not None and local_rank > 0 and self.output_fname is None:
@@ -250,7 +249,7 @@ def _rank_zero_only_wrap(self) -> None:
 
     def start(self, action_name: str) -> None:
         if not self._profiler_instantiated and action_name in (
-            list(self.START_RECORD_FUNCTIONS) + list(self.record_functions)
+            list(self.START_RECORD_FUNCTIONS) + list(self._record_functions)
         ):
 
             # close profiler if it is already opened
@@ -267,31 +266,31 @@ def start(self, action_name: str) -> None:
 
             self._profiler_instantiated = True
 
-            if self.record_module_names and self.lightning_module is not None:
-                self.register = RegisterRecordFunction(self.lightning_module)
-                self.register.__enter__()
+            if self._record_module_names and self._lightning_module is not None:
+                self._register = RegisterRecordFunction(self._lightning_module)
+                self._register.__enter__()
 
         if (
-            self._profiler_instantiated and action_name in self.record_functions
-            and action_name not in self.recording_map
+            self._profiler_instantiated and action_name in self._record_functions
+            and action_name not in self._recording_map
         ):
             recording = record_function(action_name)
             recording.__enter__()
-            self.recording_map[action_name] = recording
+            self._recording_map[action_name] = recording
 
     def stop(self, action_name: str) -> None:
-        if action_name in self.recording_map:
-            self.recording_map[action_name].__exit__(None, None, None)
-            del self.recording_map[action_name]
+        if action_name in self._recording_map:
+            self._recording_map[action_name].__exit__(None, None, None)
+            del self._recording_map[action_name]
 
     def summary(self) -> str:
-        if not self.profiler_kwargs.get("enabled", True):
+        if not self._profiler_kwargs.get("enabled", True):
             return ""
 
         local_rank = 0 if self.local_rank is None else self.local_rank
 
         self.profiler.__exit__(None, None, None)
-        if not self.emit_nvtx:
+        if not self._emit_nvtx:
             self.function_events = self.profiler.function_events
         self.profiler = None
         self._profiler_instantiated = False
@@ -300,21 +299,21 @@ def summary(self) -> str:
             self._parent_profiler.__exit__(None, None, None)
             self._parent_profiler = None
 
-        if self.register is not None:
-            self.register.__exit__(None, None, None)
+        if self._register is not None:
+            self._register.__exit__(None, None, None)
 
-        if self.emit_nvtx:
+        if self._emit_nvtx:
             return ""
 
-        if self.export_to_chrome:
+        if self._export_to_chrome:
             filename = f"{local_rank}_trace.json"
             path_to_trace = (
-                filename if self.path_to_export_trace is None else os.path.join(self.path_to_export_trace, filename)
+                filename if self._path_to_export_trace is None else os.path.join(self._path_to_export_trace, filename)
             )
             self.function_events.export_chrome_trace(path_to_trace)
 
-        data = self.function_events.key_averages(group_by_input_shapes=self.group_by_input_shapes)
-        table = data.table(sort_by=self.sort_by_key, row_limit=self.row_limit)
+        data = self.function_events.key_averages(group_by_input_shapes=self._group_by_input_shapes)
+        table = data.table(sort_by=self._sort_by_key, row_limit=self._row_limit)
 
         recorded_stats = {}
         recorded_stats["records"] = table
@@ -322,7 +321,7 @@ def summary(self) -> str:
         return self.stats_to_str(recorded_stats)
 
     def _create_profilers(self) -> None:
-        if self.emit_nvtx:
+        if self._emit_nvtx:
             self._parent_profiler = self._create_profiler(torch.cuda.profiler.profile)
             self.profiler = self._create_profiler(torch.autograd.profiler.emit_nvtx)
         else:
@@ -331,7 +330,7 @@ def _create_profilers(self) -> None:
 
     def _create_profiler(self, profiler: Type[_PROFILER]) -> _PROFILER:
         init_parameters = inspect.signature(profiler.__init__).parameters
-        kwargs = {k: v for k, v in self.profiler_kwargs.items() if k in init_parameters}
+        kwargs = {k: v for k, v in vars(self).items() if k in init_parameters}
         return profiler(**kwargs)
 
     def teardown(self):
@@ -342,10 +341,10 @@ def teardown(self):
             self._parent_profiler.__exit__(None, None, None)
             self._parent_profiler = None
 
-        if self.register is not None:
-            self.register.__exit__(None, None, None)
+        if self._register is not None:
+            self._register.__exit__(None, None, None)
 
-        for record in self.recording_map.values():
+        for record in self._recording_map.values():
             record.__exit__(None, None, None)
 
         super().teardown()

From a05acdd02a523fbaa880222e203ffc1d6935c1e6 Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Mon, 22 Mar 2021 12:29:38 +0000
Subject: [PATCH 48/87] remove trace

---
 0_trace.json | 1 -
 1 file changed, 1 deletion(-)
 delete mode 100644 0_trace.json

diff --git a/0_trace.json b/0_trace.json
deleted file mode 100644
index 2b9487adf83a1..0000000000000
--- a/0_trace.json
+++ /dev/null
@@ -1 +0,0 @@
-[{"name": "aten::empty", "ph": "X", "ts": 434.706, "dur": 4.123999999999967, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::random_", "ph": "X", "ts": 460.465, "dur": 8.160000000000025, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::is_floating_point", "ph": "X", "ts": 517.229, "dur": 0.5319999999999254, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::item", "ph": "X", "ts": 521.148, "dur": 4.944999999999936, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::_local_scalar_dense", "ph": "X", "ts": 523.151, "dur": 2.3920000000000528, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::zeros", "ph": "X", "ts": 550.11, "dur": 6.506999999999948, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 552.022, "dur": 1.8149999999999409, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::zero_", "ph": "X", "ts": 555.346, "dur": 0.8869999999999436, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "enumerate(DataLoader)#_SingleProcessDataLoaderIter.__next__", "ph": "X", "ts": 570.759, "dur": 90.41200000000003, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 572.027, "dur": 1.2229999999999563, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::select", "ph": "X", "ts": 590.516, "dur": 7.359000000000037, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 593.307, "dur": 1.2479999999999336, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::stack", "ph": "X", "ts": 611.293, "dur": 18.946000000000026, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::unsqueeze", "ph": "X", "ts": 614.671, "dur": 2.647999999999911, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 615.849, "dur": 0.8669999999999618, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::cat", "ph": "X", "ts": 618.48, "dur": 10.204999999999927, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::_cat", "ph": "X", "ts": 620.28, "dur": 7.537000000000035, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 621.824, "dur": 0.7570000000000618, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::resize_", "ph": "X", "ts": 624.749, "dur": 1.7419999999999618, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::zeros", "ph": "X", "ts": 673.509, "dur": 3.905999999999949, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 674.565, "dur": 1.2449999999998909, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::zero_", "ph": "X", "ts": 676.664, "dur": 0.39999999999997726, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "predict", "ph": "X", "ts": 682.945, "dur": 136.89499999999998, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 683.766, "dur": 0.9970000000000709, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::to", "ph": "X", "ts": 719.439, "dur": 0.6900000000000546, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::linear", "ph": "X", "ts": 756.527, "dur": 31.145999999999958, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::t", "ph": "X", "ts": 758.133, "dur": 7.706999999999994, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::transpose", "ph": "X", "ts": 760.317, "dur": 3.59699999999998, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 761.541, "dur": 1.6059999999999945, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::addmm", "ph": "X", "ts": 767.014, "dur": 19.521999999999935, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 769.084, "dur": 0.7690000000000055, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::expand", "ph": "X", "ts": 771.655, "dur": 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"args": {}}, {"name": "aten::resize_", "ph": "X", "ts": 12773.408, "dur": 0.8880000000008295, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::zeros", "ph": "X", "ts": 12792.406, "dur": 5.511999999998807, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 12793.328, "dur": 0.875, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::zero_", "ph": "X", "ts": 12794.999, "dur": 2.587999999999738, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "predict", "ph": "X", "ts": 12802.584, "dur": 90.54799999999886, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 12803.354, "dur": 0.9130000000004657, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::to", "ph": "X", "ts": 12825.614, "dur": 0.4250000000010914, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::linear", "ph": "X", "ts": 12846.364, "dur": 24.137000000000626, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::t", "ph": "X", "ts": 12847.304, "dur": 5.167999999999665, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::transpose", "ph": "X", "ts": 12848.595, "dur": 2.519000000000233, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 12849.533, "dur": 0.956000000000131, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::addmm", "ph": "X", "ts": 12853.256, "dur": 16.33100000000013, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 12857.108, "dur": 2.855999999999767, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::expand", "ph": "X", "ts": 12860.885, "dur": 1.951999999999316, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 12861.899, "dur": 0.4819999999999709, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::copy_", "ph": "X", "ts": 12864.436, "dur": 3.0090000000000146, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::zeros", "ph": "X", "ts": 12900.911, "dur": 6.020000000000437, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 12901.771, "dur": 1.1199999999989814, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::zero_", "ph": "X", "ts": 12903.715, "dur": 2.8690000000005966, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "enumerate(DataLoader)#_SingleProcessDataLoaderIter.__next__", "ph": "X", "ts": 12912.403, "dur": 38.89300000000003, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 12913.277, "dur": 0.956000000000131, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::select", "ph": "X", "ts": 12922.239, "dur": 3.757999999999811, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 12923.748, "dur": 0.6020000000007713, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::stack", "ph": "X", "ts": 12931.921, "dur": 13.05699999999888, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::unsqueeze", "ph": "X", "ts": 12933.561, "dur": 1.5709999999999127, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 12934.29, "dur": 0.5309999999990396, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::cat", "ph": "X", "ts": 12937.833, "dur": 5.947000000000116, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::_cat", "ph": "X", "ts": 12938.738, "dur": 4.505000000001019, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 12939.574, "dur": 0.5979999999999563, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::resize_", "ph": "X", "ts": 12941.567, "dur": 0.8000000000010914, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::zeros", "ph": "X", "ts": 12960.526, "dur": 3.264000000001033, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 12961.445, "dur": 0.8450000000011642, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::zero_", "ph": "X", "ts": 12963.131, "dur": 0.3580000000001746, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "predict", "ph": "X", "ts": 12970.648, "dur": 640.8760000000002, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 12971.442, "dur": 0.875, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::to", "ph": "X", "ts": 12993.194, "dur": 0.43699999999989814, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::linear", "ph": "X", "ts": 13013.671, "dur": 568.098, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::t", "ph": "X", "ts": 13014.584, "dur": 5.342999999998938, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::transpose", "ph": "X", "ts": 13015.967, "dur": 2.5090000000000146, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 13016.911, "dur": 0.9549999999999272, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::addmm", "ph": "X", "ts": 13020.728, "dur": 559.7790000000005, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 13022.136, "dur": 0.657999999999447, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::expand", "ph": "X", "ts": 13569.571, "dur": 2.5419999999994616, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 13570.921, "dur": 0.6440000000002328, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::copy_", "ph": "X", "ts": 13574.051, "dur": 3.4800000000013824, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::zeros", "ph": "X", "ts": 13620.213, "dur": 4.345000000001164, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 13621.283, "dur": 1.4950000000008004, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::zero_", "ph": "X", "ts": 13623.781, "dur": 0.4379999999982829, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "enumerate(DataLoader)#_SingleProcessDataLoaderIter.__next__", "ph": "X", "ts": 13630.574, "dur": 48.39499999999862, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 13634.072, "dur": 0.907999999999447, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::select", "ph": "X", "ts": 13644.527, "dur": 4.183999999999287, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 13646.218, "dur": 0.6439999999984138, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::stack", "ph": "X", "ts": 13655.739, "dur": 16.61499999999978, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::unsqueeze", "ph": "X", "ts": 13657.516, "dur": 1.668999999999869, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 13658.306, "dur": 0.5299999999988358, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::cat", "ph": "X", "ts": 13659.935, "dur": 11.09900000000016, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::_cat", "ph": "X", "ts": 13661.084, "dur": 9.350999999998749, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 13662.038, "dur": 4.897999999999229, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::resize_", "ph": "X", "ts": 13668.442, "dur": 0.9010000000016589, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::zeros", "ph": "X", "ts": 13688.96, "dur": 3.4250000000010914, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 13689.955, "dur": 0.9750000000003638, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::zero_", "ph": "X", "ts": 13691.781, "dur": 0.3129999999982829, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "predict", "ph": "X", "ts": 13697.228, "dur": 97.23300000000017, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 13698.04, "dur": 0.8289999999997235, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::to", "ph": "X", "ts": 13724.748, "dur": 0.41700000000128057, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::linear", "ph": "X", "ts": 13747.986, "dur": 22.938999999998487, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::t", "ph": "X", "ts": 13749.011, "dur": 5.6819999999988795, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::transpose", "ph": "X", "ts": 13750.511, "dur": 2.57799999999952, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 13751.453, "dur": 1.077000000001135, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::addmm", "ph": "X", "ts": 13755.465, "dur": 14.566000000000713, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 13756.972, "dur": 0.6450000000004366, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::expand", "ph": "X", "ts": 13758.652, "dur": 4.225000000000364, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 13759.717, "dur": 2.6970000000001164, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::copy_", "ph": "X", "ts": 13764.638, "dur": 3.0829999999987194, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::zeros", "ph": "X", "ts": 13802.476, "dur": 3.9659999999985303, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 13803.474, "dur": 1.396999999999025, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::zero_", "ph": "X", "ts": 13805.746, "dur": 0.3890000000010332, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "enumerate(DataLoader)#_SingleProcessDataLoaderIter.__next__", "ph": "X", "ts": 13811.809, "dur": 55.63000000000102, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 13812.683, "dur": 1.0569999999988795, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::select", "ph": "X", "ts": 13824.932, "dur": 4.0569999999988795, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 13826.625, "dur": 0.6880000000001019, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::stack", "ph": "X", "ts": 13835.056, "dur": 25.26800000000003, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::unsqueeze", "ph": "X", "ts": 13836.824, "dur": 1.5679999999993015, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 13837.571, "dur": 0.5149999999994179, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::cat", "ph": "X", "ts": 13839.12, "dur": 19.922999999998865, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::_cat", "ph": "X", "ts": 13840.036, "dur": 18.432999999999083, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 13852.355, "dur": 0.6430000000000291, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::resize_", "ph": "X", "ts": 13854.522, "dur": 2.9839999999985594, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::zeros", "ph": "X", "ts": 13877.081, "dur": 3.3510000000005675, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 13878.004, "dur": 0.9899999999997817, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::zero_", "ph": "X", "ts": 13879.823, "dur": 0.2999999999992724, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "predict", "ph": "X", "ts": 13885.23, "dur": 93.53900000000067, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 13885.989, "dur": 0.8950000000004366, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::to", "ph": "X", "ts": 13908.665, "dur": 0.4289999999982683, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::linear", "ph": "X", "ts": 13933.401, "dur": 22.036000000000058, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::t", "ph": "X", "ts": 13934.361, "dur": 5.274999999999636, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::transpose", "ph": "X", "ts": 13935.675, "dur": 2.5310000000008586, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 13936.598, "dur": 1.0229999999992287, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::addmm", "ph": "X", "ts": 13940.381, "dur": 14.26300000000083, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 13941.784, "dur": 0.7049999999999272, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::expand", "ph": "X", "ts": 13943.373, "dur": 2.015000000001237, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::as_strided", "ph": "X", "ts": 13944.484, "dur": 0.4709999999995489, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::copy_", "ph": "X", "ts": 13949.232, "dur": 3.105999999999767, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::zeros", "ph": "X", "ts": 13986.665, "dur": 3.580999999998312, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 13987.536, "dur": 1.1559999999990396, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::zero_", "ph": "X", "ts": 13989.544, "dur": 0.3850000000002183, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "enumerate(DataLoader)#_SingleProcessDataLoaderIter.__next__", "ph": "X", "ts": 13995.88, "dur": 10.150000000001455, "tid": 1, "pid": "CPU functions", "args": {}}, {"name": "aten::empty", "ph": "X", "ts": 13996.686, "dur": 0.9040000000004511, "tid": 1, "pid": "CPU functions", "args": {}}]

From 59c941b7a15db0afdc0fa35b104b908a088772ef Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Mon, 22 Mar 2021 14:32:02 +0100
Subject: [PATCH 49/87] Undo code that should be in 3/4

---
 pytorch_lightning/profiler/pytorch.py | 9 ---------
 1 file changed, 9 deletions(-)

diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index db89e34bac913..bb961ca452697 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -155,7 +155,6 @@ def __init__(
         self.context_names = {}
         self.running_stack = []
         self.profiler = None
-        self._parent_profiler = None
 
         super().__init__(dirpath=dirpath, filename=filename, output_filename=output_filename)
 
@@ -263,11 +262,3 @@ def summary(self) -> str:
 
         return self._stats_to_str(recorded_stats)
 
-    def teardown(self) -> None:
-        if self.profiler is not None:
-            self.profiler.__exit__(None, None, None)
-
-        if self._parent_profiler is not None:
-            self._parent_profiler.__exit__(None, None, None)
-
-        return super().teardown()

From da0f310684f8987cf09a1b85100a08cde90e14bd Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Mon, 22 Mar 2021 19:13:33 +0100
Subject: [PATCH 50/87] Multi-stage multi-rank

---
 CHANGELOG.md                            |  3 +
 pytorch_lightning/profiler/profilers.py | 92 ++++++++++++++++---------
 pytorch_lightning/profiler/pytorch.py   | 16 +++--
 pytorch_lightning/trainer/trainer.py    |  4 +-
 tests/deprecated_api/test_remove_1-5.py |  2 +-
 tests/test_profiler.py                  | 22 +++---
 6 files changed, 85 insertions(+), 54 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index c5f2896004a10..fe656ed46153d 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -71,6 +71,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Changed `setup()` and `teardown()` stage argument to take any of `{fit,validate,test,predict}` ([#6386](https://github.com/PyTorchLightning/pytorch-lightning/pull/6386))
 
 
+- Changed profilers to save separate report files per state and rank ([#6621](https://github.com/PyTorchLightning/pytorch-lightning/pull/6621))
+
+
 ### Deprecated
 
 - `period` has been deprecated in favor of `every_n_val_epochs` in the `ModelCheckpoint` callback ([#6146](https://github.com/PyTorchLightning/pytorch-lightning/pull/6146))
diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index 334f121c9c084..bd889c24c2bf4 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -22,7 +22,7 @@
 from collections import defaultdict
 from contextlib import contextmanager
 from pathlib import Path
-from typing import Dict, Optional, Tuple, Union
+from typing import Dict, Optional, Tuple, Union, TextIO, Callable
 
 import numpy as np
 
@@ -77,12 +77,13 @@ def __init__(
             )
             filepath = Path(output_filename)
             self.dirpath = filepath.parent
-            self.filename = filepath.name
-        self.output_file = None
-        self.local_rank = None
-        self.log_dir = None
-        self.write_streams = []
-        self._file_prepared = False
+            self.filename = filepath.stem
+
+        self._output_file: Optional[TextIO] = None
+        self._write_stream: Optional[Callable] = None
+        self._local_rank: Optional[int] = None
+        self._log_dir: Optional[str] = None
+        self._stage: Optional[str] = None
 
     @contextmanager
     def profile(self, action_name: str) -> None:
@@ -116,51 +117,72 @@ def profile_iterable(self, iterable, action_name: str) -> None:
                 break
 
     def _rank_zero_info(self, *args, **kwargs) -> None:
-        if self.local_rank in (None, 0):
+        if self._local_rank in (None, 0):
             log.info(*args, **kwargs)
 
-    def _prepare_file(self) -> None:
-        if not self._file_prepared:
-            if self.filename and self.output_file is None:
-                dirpath = self.dirpath or self.log_dir
-                filepath = os.path.join(dirpath, self.filename)
-                fs = get_filesystem(filepath)
-                self.output_file = fs.open(filepath, "a")
-            self.write_streams = [self.output_file.write] if self.output_file else [self._rank_zero_info]
-        self._file_prepared = True
+    def _prepare_filename(self) -> str:
+        filename = ""
+        if self._stage is not None:
+            filename += f"{self._stage}-"
+        filename += self.filename
+        if self._local_rank is not None:
+            filename += f"-{self._local_rank}"
+        filename += ".txt"
+        return filename
+
+    def _prepare_streams(self) -> None:
+        if self._write_stream is not None:
+            return
+        if self.filename:
+            dirpath = self.dirpath or self._log_dir
+            filepath = os.path.join(dirpath, self._prepare_filename())
+            fs = get_filesystem(filepath)
+            file = fs.open(filepath, "a")
+            self._output_file = file
+            self._write_stream = file.write
+        else:
+            self._write_stream = self._rank_zero_info
 
     def describe(self) -> None:
         """Logs a profile report after the conclusion of run."""
-        self._prepare_file()
-        for write in self.write_streams:
-            write(self.summary())
-        if self.output_file:
-            self.output_file.flush()
-        self.teardown()
+        # there are pickling issues with open file handles in Python 3.6
+        # so to avoid them, we open and close the files within this function
+        # by calling `_prepare_streams` and `teardown`
+        self._prepare_streams()
+        self._write_stream(self.summary())
+        if self._output_file is not None:
+            self._output_file.flush()
+        self.teardown(stage=self._stage)
 
     def _stats_to_str(self, stats: Dict[str, str]) -> str:
         output = ["Profiler Report"]
         for action, value in stats.items():
             header = f"Profile stats for: {action}"
-            if getattr(self, "local_rank", None) is not None:
-                header += f" rank: {self.local_rank}"
+            if self._local_rank is not None:
+                header += f" rank: {self._local_rank}"
             output.append(header)
             output.append(value)
         return os.linesep.join(output)
 
-    def setup(self, local_rank: Optional[int] = None, log_dir: Optional[str] = None) -> None:
+    def setup(
+        self,
+        stage: Optional[str] = None,
+        local_rank: Optional[int] = None,
+        log_dir: Optional[str] = None,
+    ) -> None:
         """
         This function is used by the Trainer to inject the local_rank on distributed and `TensorBoardLogger.log_dir`.
         """
-        self.local_rank = local_rank
-        self.log_dir = log_dir
+        self._stage = stage
+        self._local_rank = local_rank
+        self._log_dir = log_dir
 
-    def teardown(self) -> None:
-        """Close profiler's stream."""
-        if self.output_file:
-            self.output_file.close()
-        self.write_streams = []
-        self._file_prepared = False
+    def teardown(self, stage: Optional[str] = None) -> None:
+        """Close a stage's file and streams."""
+        assert stage == self._stage
+        self._write_stream = None
+        if self._output_file is not None:
+            self._output_file.close()
 
     def __del__(self) -> None:
         self.teardown()
@@ -211,6 +233,7 @@ def __init__(
                 will be used.
 
             filename: If present, filename where the profiler results will be saved instead of printing to stdout.
+                The ``.txt`` extension will be used automatically.
 
         Raises:
             ValueError:
@@ -305,6 +328,7 @@ def __init__(
                 will be used.
 
             filename: If present, filename where the profiler results will be saved instead of printing to stdout.
+                The ``.txt`` extension will be used automatically.
 
             line_count_restriction: this can be used to limit the number of functions
                 reported for each action. either an integer (to select a count of lines),
diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index bb961ca452697..85b3ec7d8d2ed 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -73,6 +73,7 @@ def __init__(
                 will be used.
 
             filename: If present, filename where the profiler results will be saved instead of printing to stdout.
+                The ``.txt`` extension will be used automatically.
 
             enabled: Setting this to False makes this context manager a no-op.
 
@@ -118,8 +119,7 @@ def __init__(
 
         Raises:
             MisconfigurationException:
-                If arg ``sort_by_key`` is not present in ``AVAILABLE_SORT_KEYS``, or
-                if log file is not a ``.txt`` file.
+                If arg ``sort_by_key`` is not present in ``AVAILABLE_SORT_KEYS``.
             ValueError:
                 If you attempt to stop recording an action which was never started.
         """
@@ -158,8 +158,13 @@ def __init__(
 
         super().__init__(dirpath=dirpath, filename=filename, output_filename=output_filename)
 
-    def setup(self, local_rank: Optional[int] = None, log_dir: Optional[str] = None) -> None:
-        super().setup(local_rank=local_rank, log_dir=log_dir)
+    def setup(
+        self,
+        stage: Optional[str] = None,
+        local_rank: Optional[int] = None,
+        log_dir: Optional[str] = None
+    ) -> None:
+        super().setup(stage=stage, local_rank=local_rank, log_dir=log_dir)
 
         # if the user didn't provide `path_to_export_trace`,
         # set it as TensorBoardLogger log_dir if exists
@@ -234,7 +239,7 @@ def stop(self, action_name: str) -> None:
     def summary(self) -> str:
         recorded_stats = {}
         output_string = ''
-        local_rank = '0' if self.local_rank is None else self.local_rank
+        local_rank = '0' if self._local_rank is None else self._local_rank
 
         if not self.enabled:
             return output_string
@@ -261,4 +266,3 @@ def summary(self) -> str:
                 recorded_stats[action_name] = table
 
         return self._stats_to_str(recorded_stats)
-
diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index 22f2966a54e0b..710f28d113438 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -519,7 +519,7 @@ def dispatch(self):
             self.accelerator.start_training(self)
 
     def _on_run_stage_setup(self):
-        self.profiler.setup(local_rank=self.local_rank if self.world_size > 1 else None, log_dir=self.log_dir)
+        self.profiler.setup(self.state, local_rank=self.local_rank if self.world_size > 1 else None, log_dir=self.log_dir)
 
     def run_stage(self):
         results = None
@@ -1085,7 +1085,7 @@ def call_teardown_hook(self, model: LightningModule) -> None:
         else:
             state = None
 
-        self.profiler.teardown()
+        self.profiler.teardown(stage=state)
         self.teardown(stage=state)
         model.teardown(stage=state)
 
diff --git a/tests/deprecated_api/test_remove_1-5.py b/tests/deprecated_api/test_remove_1-5.py
index 6f2c65c7a1171..0c5f581d7775c 100644
--- a/tests/deprecated_api/test_remove_1-5.py
+++ b/tests/deprecated_api/test_remove_1-5.py
@@ -208,7 +208,7 @@ def on_test_epoch_end(self, outputs):
 
 @pytest.mark.parametrize("cls", (BaseProfiler, SimpleProfiler, AdvancedProfiler, PyTorchProfiler))
 def test_v1_5_0_profiler_output_filename(tmpdir, cls):
-    filepath = str(tmpdir / "test")
+    filepath = str(tmpdir / "test.txt")
     with pytest.deprecated_call(match="`output_filename` parameter has been removed"):
         profiler = cls(output_filename=filepath)
     assert profiler.dirpath == tmpdir
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 696d45ca81a43..2ebf1c2845fdd 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -115,8 +115,8 @@ def test_simple_profiler_value_errors(simple_profiler):
 
 def test_simple_profiler_log_dir(tmpdir):
     """Ensure the profiler dirpath defaults to `trainer.log_dir` when not present"""
-    profiler = SimpleProfiler(filename="profiler.txt")
-    assert profiler.log_dir is None
+    profiler = SimpleProfiler(filename="profiler")
+    assert profiler._log_dir is None
 
     model = BoringModel()
     trainer = Trainer(
@@ -128,13 +128,13 @@ def test_simple_profiler_log_dir(tmpdir):
 
     expected = tmpdir / "lightning_logs" / "version_0"
     assert trainer.log_dir == expected
-    assert profiler.log_dir == trainer.log_dir
-    assert expected.join("profiler.txt").exists()
+    assert profiler._log_dir == trainer.log_dir
+    assert expected.join("fit-profiler.txt").exists()
 
 
 @pytest.fixture
 def advanced_profiler(tmpdir):
-    return AdvancedProfiler(dirpath=tmpdir, filename="profiler.txt")
+    return AdvancedProfiler(dirpath=tmpdir, filename="profiler")
 
 
 @pytest.mark.parametrize(["action", "expected"], [
@@ -195,7 +195,7 @@ def test_advanced_profiler_describe(tmpdir, advanced_profiler):
         pass
     # log to stdout and print to file
     advanced_profiler.describe()
-    path = advanced_profiler.dirpath / advanced_profiler.filename
+    path = advanced_profiler.dirpath / f"{advanced_profiler.filename}.txt"
     data = path.read_text("utf-8")
     assert len(data) > 0
 
@@ -213,7 +213,7 @@ def test_advanced_profiler_value_errors(advanced_profiler):
 
 @pytest.fixture
 def pytorch_profiler(tmpdir):
-    return PyTorchProfiler(dirpath=tmpdir, filename="profiler.txt")
+    return PyTorchProfiler(dirpath=tmpdir, filename="profiler")
 
 
 def test_pytorch_profiler_describe(pytorch_profiler):
@@ -223,7 +223,7 @@ def test_pytorch_profiler_describe(pytorch_profiler):
 
     # log to stdout and print to file
     pytorch_profiler.describe()
-    path = pytorch_profiler.dirpath / pytorch_profiler.filename
+    path = pytorch_profiler.dirpath / f"{pytorch_profiler.filename}.txt"
     data = path.read_text("utf-8")
     assert len(data) > 0
 
@@ -266,7 +266,7 @@ def test_pytorch_profiler_nested(tmpdir):
     """Ensure that the profiler handles nested context"""
 
     pytorch_profiler = PyTorchProfiler(
-        profiled_functions=["a", "b", "c"], use_cuda=False, dirpath=tmpdir, filename="profiler.txt"
+        profiled_functions=["a", "b", "c"], use_cuda=False, dirpath=tmpdir, filename="profiler"
     )
 
     with pytorch_profiler.profile("a"):
@@ -327,7 +327,7 @@ def test_profiler_teardown(tmpdir, cls):
     """
     This test checks if profiler teardown method is called when trainer is exiting.
     """
-    profiler = cls(dirpath=tmpdir, filename="profiler.txt")
+    profiler = cls(dirpath=tmpdir, filename="profiler")
 
     model = BoringModel()
     trainer = Trainer(
@@ -337,4 +337,4 @@ def test_profiler_teardown(tmpdir, cls):
     )
     trainer.fit(model)
 
-    assert profiler.output_file.closed
+    assert profiler._output_file.closed

From 59c1b4c7cc5ddbb8d9d019d6e746e93abf749aa5 Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Mon, 22 Mar 2021 19:26:12 +0100
Subject: [PATCH 51/87] 2/5 changes

---
 .../plugins/training_type/horovod.py           |  1 +
 .../trainer/connectors/profiler_connector.py   |  5 +++++
 pytorch_lightning/trainer/properties.py        | 10 ++++++++++
 pytorch_lightning/trainer/trainer.py           | 18 +++++-------------
 tests/test_profiler.py                         | 13 +++++++------
 5 files changed, 28 insertions(+), 19 deletions(-)

diff --git a/pytorch_lightning/plugins/training_type/horovod.py b/pytorch_lightning/plugins/training_type/horovod.py
index 06ab7500dacc8..8d0add27cbb29 100644
--- a/pytorch_lightning/plugins/training_type/horovod.py
+++ b/pytorch_lightning/plugins/training_type/horovod.py
@@ -110,6 +110,7 @@ def start_evaluating(self, trainer):
 
     def start_predicting(self, trainer):
         with ExitStack():
+            # set up training routine
             self._results = trainer.run_stage()
 
         # Make sure all workers have finished training before returning to the user
diff --git a/pytorch_lightning/trainer/connectors/profiler_connector.py b/pytorch_lightning/trainer/connectors/profiler_connector.py
index efb58fc844696..e628d6d96bd19 100644
--- a/pytorch_lightning/trainer/connectors/profiler_connector.py
+++ b/pytorch_lightning/trainer/connectors/profiler_connector.py
@@ -53,3 +53,8 @@ def on_trainer_init(self, profiler: Union[BaseProfiler, str]):
                     " `Trainer`, it can only be 'simple' or 'advanced'"
                 )
         self.trainer.profiler = profiler or PassThroughProfiler()
+
+    def setup(self) -> None:
+        trainer = self.trainer
+        local_rank = trainer.local_rank if trainer.world_size > 1 else None
+        trainer.profiler.setup(stage=trainer._setup_state, local_rank=local_rank, log_dir=trainer.log_dir)
diff --git a/pytorch_lightning/trainer/properties.py b/pytorch_lightning/trainer/properties.py
index b5654b148afc6..315e3c60c0557 100644
--- a/pytorch_lightning/trainer/properties.py
+++ b/pytorch_lightning/trainer/properties.py
@@ -491,6 +491,16 @@ def sanity_checking(self, val: bool) -> None:
         elif self.sanity_checking:
             self._running_stage = None
 
+    @property
+    def _setup_state(self) -> TrainerState:
+        # 'fit' is passed for `trainer.tune()` as there aren't "tune_dataloaders"
+        return TrainerState.FITTING if self.state == TrainerState.TUNING else self.state
+
+    @property
+    def _teardown_state(self) -> Optional[TrainerState]:
+        if self.state.running:
+            return self._setup_state
+
 
 # Used to represent the concrete type TrainerProperties class methods are called on.
 _T = TypeVar('_T', bound=TrainerProperties)
diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index 710f28d113438..f7bd1757b9bc2 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -445,7 +445,7 @@ def fit(
                                 |                             ||
                          {self.dispatch}                      ||
                                 |                             ||  LIGHTNING
-                {self.accelerator.start_training}             ||
+                  {self.accelerator.start_training}           ||
                 or {self.accelerator.start_evaluating}        ||
                 or {self.accelerator.start_predicting}        ||  FLOW
                                 |                             ||
@@ -453,7 +453,7 @@ def fit(
                                 |                             ||  DIRECTION
                         {self.run_train}                      ||
                      or {self.run_evaluation}                 ||
-                     or  {self.run_predict}                   ||
+                     or {self.run_predict}                    ||
                                 |                             ||
                              results                          \/
         This is used to guide readers to the core loops: train, test, predict.
@@ -518,13 +518,10 @@ def dispatch(self):
         else:
             self.accelerator.start_training(self)
 
-    def _on_run_stage_setup(self):
-        self.profiler.setup(self.state, local_rank=self.local_rank if self.world_size > 1 else None, log_dir=self.log_dir)
-
     def run_stage(self):
         results = None
 
-        self._on_run_stage_setup()
+        self.profile_connector.setup()
 
         if self.evaluating:
             results = self.run_evaluate()
@@ -1068,8 +1065,7 @@ def tune(
 
     def call_setup_hook(self, model: LightningModule) -> None:
         assert self.state.running, f"TrainerState: {self.state}"
-        # 'fit' is passed for `trainer.tune()` as there aren't "tune_dataloaders"
-        state = TrainerState.FITTING if self.state == TrainerState.TUNING else self.state
+        state = self._setup_state
 
         if self.datamodule is not None:
             called = getattr(self.datamodule, f'has_setup_{state}')
@@ -1080,11 +1076,7 @@ def call_setup_hook(self, model: LightningModule) -> None:
         model.setup(stage=state)
 
     def call_teardown_hook(self, model: LightningModule) -> None:
-        if self.state.running:
-            state = TrainerState.FITTING if self.state == TrainerState.TUNING else self.state
-        else:
-            state = None
-
+        state = self._teardown_state
         self.profiler.teardown(stage=state)
         self.teardown(stage=state)
         model.teardown(stage=state)
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 2ebf1c2845fdd..89ed2004af7ae 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -20,7 +20,7 @@
 import pytest
 import torch
 
-from pytorch_lightning import Trainer
+from pytorch_lightning import Trainer, Callback
 from pytorch_lightning.profiler import AdvancedProfiler, PyTorchProfiler, SimpleProfiler
 from tests.helpers import BoringModel
 from tests.helpers.runif import RunIf
@@ -327,14 +327,15 @@ def test_profiler_teardown(tmpdir, cls):
     """
     This test checks if profiler teardown method is called when trainer is exiting.
     """
+    class TestCallback(Callback):
+
+        def on_fit_end(self, trainer, *args, **kwargs) -> None:
+            assert trainer.profiler._output_file is not None
+
     profiler = cls(dirpath=tmpdir, filename="profiler")
 
     model = BoringModel()
-    trainer = Trainer(
-        default_root_dir=tmpdir,
-        fast_dev_run=True,
-        profiler=profiler,
-    )
+    trainer = Trainer(default_root_dir=tmpdir, fast_dev_run=True, profiler=profiler, callbacks=[TestCallback()])
     trainer.fit(model)
 
     assert profiler._output_file.closed

From dd1dce067da0208e1a54a01505f65fe3b5850d30 Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Mon, 22 Mar 2021 19:28:30 +0100
Subject: [PATCH 52/87] Pass stage in __del__

---
 pytorch_lightning/profiler/profilers.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index bd889c24c2bf4..14a354020b0cb 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -185,7 +185,7 @@ def teardown(self, stage: Optional[str] = None) -> None:
             self._output_file.close()
 
     def __del__(self) -> None:
-        self.teardown()
+        self.teardown(stage=self._stage)
 
     def start(self, action_name: str) -> None:
         raise NotImplementedError

From 097a42644aeca82026a78a4aca8b86507d6f5d68 Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Mon, 22 Mar 2021 19:56:20 +0100
Subject: [PATCH 53/87] Remove TODOs

---
 pytorch_lightning/profiler/profilers.py    | 2 +-
 pytorch_lightning/trainer/training_loop.py | 4 +---
 tests/test_profiler.py                     | 8 +++-----
 3 files changed, 5 insertions(+), 9 deletions(-)

diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index 18d5a317739ff..99a898f78e557 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -179,7 +179,7 @@ def teardown(self, stage: Optional[str] = None) -> None:
         """
         Execute arbitrary post-profiling tear-down steps.
         
-        Closes currently open file and stream.
+        Closes the currently open file and stream.
         """
         assert stage == self._stage
         self._write_stream = None
diff --git a/pytorch_lightning/trainer/training_loop.py b/pytorch_lightning/trainer/training_loop.py
index 384a1b67a64f8..cc471f76b6033 100644
--- a/pytorch_lightning/trainer/training_loop.py
+++ b/pytorch_lightning/trainer/training_loop.py
@@ -137,9 +137,7 @@ def on_train_end(self):
             self.trainer.logger.finalize("success")
 
         # summarize profile results
-        # todo (tchaton) All ranks should call describe.
-        if self.trainer.global_rank == 0:
-            self.trainer.profiler.describe()
+        self.trainer.profiler.describe()
 
         # give accelerators a chance to finish
         self.trainer.accelerator.on_train_end()
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 89ed2004af7ae..431358064c7ab 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -255,11 +255,9 @@ def test_pytorch_profiler_trainer_ddp(tmpdir, pytorch_profiler):
     assert len(pytorch_profiler.summary()) > 0
     assert set(pytorch_profiler.profiled_actions.keys()) == {'training_step_and_backward', 'validation_step'}
 
-    # todo (tchaton) add support for all ranks
-    if os.getenv("LOCAL_RANK") == "0":
-        path = pytorch_profiler.dirpath / pytorch_profiler.filename
-        data = path.read_text("utf-8")
-        assert len(data) > 0
+    path = pytorch_profiler.dirpath / pytorch_profiler.filename
+    data = path.read_text("utf-8")
+    assert len(data) > 0
 
 
 def test_pytorch_profiler_nested(tmpdir):

From 4d529fa90f64d9da205011c2b42abe741f6e6f89 Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Mon, 22 Mar 2021 20:34:10 +0100
Subject: [PATCH 54/87] Describe on_evaluation_end. Add tests

---
 pytorch_lightning/profiler/profilers.py      |  8 ++--
 pytorch_lightning/trainer/evaluation_loop.py |  5 +++
 tests/test_profiler.py                       | 47 ++++++++++++++++----
 3 files changed, 49 insertions(+), 11 deletions(-)

diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index 99a898f78e557..481f107dbf1b9 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -155,7 +155,7 @@ def describe(self) -> None:
         self.teardown(stage=self._stage)
 
     def _stats_to_str(self, stats: Dict[str, str]) -> str:
-        output = ["Profiler Report"]
+        output = [f"{self._stage} " if self._stage is not None else "" + "Profiler report"]
         for action, value in stats.items():
             header = f"Profile stats for: {action}"
             if self._local_rank is not None:
@@ -181,7 +181,6 @@ def teardown(self, stage: Optional[str] = None) -> None:
         
         Closes the currently open file and stream.
         """
-        assert stage == self._stage
         self._write_stream = None
         if self._output_file is not None:
             self._output_file.close()
@@ -269,7 +268,10 @@ def _make_report(self) -> Tuple[list, float]:
 
     def summary(self) -> str:
         sep = os.linesep
-        output_string = f"Profiler Report{sep}"
+        output_string = ""
+        if self._stage is not None:
+            output_string += f"{self._stage.upper()} "
+        output_string += f"Profiler Report{sep}"
 
         if self.extended:
 
diff --git a/pytorch_lightning/trainer/evaluation_loop.py b/pytorch_lightning/trainer/evaluation_loop.py
index 20c842939fe17..da41b9855b44a 100644
--- a/pytorch_lightning/trainer/evaluation_loop.py
+++ b/pytorch_lightning/trainer/evaluation_loop.py
@@ -15,6 +15,7 @@
 import torch
 
 from pytorch_lightning.core.step_result import Result
+from pytorch_lightning.trainer.states import TrainerState
 from pytorch_lightning.trainer.supporters import PredictionCollection
 from pytorch_lightning.utilities.apply_func import apply_to_collection
 from pytorch_lightning.utilities.model_helpers import is_overridden
@@ -99,6 +100,10 @@ def on_evaluation_end(self, *args, **kwargs):
         else:
             self.trainer.call_hook('on_validation_end', *args, **kwargs)
 
+        if self.trainer.state != TrainerState.FITTING:
+            # summarize profile results
+            self.trainer.profiler.describe()
+
     def reload_evaluation_dataloaders(self):
         model = self.trainer.lightning_module
         if self.trainer.testing:
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 431358064c7ab..8104745dddcab 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -90,14 +90,6 @@ def test_simple_profiler_overhead(simple_profiler, n_iter=5):
     assert all(durations < PROFILER_OVERHEAD_MAX_TOLERANCE)
 
 
-def test_simple_profiler_describe(caplog, simple_profiler):
-    """Ensure the profiler won't fail when reporting the summary."""
-    with caplog.at_level(logging.INFO):
-        simple_profiler.describe()
-
-    assert "Profiler Report" in caplog.text
-
-
 def test_simple_profiler_value_errors(simple_profiler):
     """Ensure errors are raised where expected."""
 
@@ -132,6 +124,45 @@ def test_simple_profiler_log_dir(tmpdir):
     assert expected.join("fit-profiler.txt").exists()
 
 
+def test_simple_profiler_distributed_files(tmpdir):
+    """Ensure the proper files are saved in distributed"""
+    profiler = SimpleProfiler(dirpath=tmpdir, filename='profiler')
+    model = BoringModel()
+    trainer = Trainer(
+        default_root_dir=tmpdir,
+        fast_dev_run=2,
+        accelerator="ddp_cpu",
+        num_processes=2,
+        profiler=profiler,
+        logger=False,
+    )
+    trainer.fit(model)
+    trainer.test(model)
+
+    actual = set(os.listdir(profiler.dirpath))
+    expected = {'fit-profiler-0.txt', 'fit-profiler-1.txt', 'test-profiler-0.txt', 'test-profiler-1.txt'}
+    assert actual == expected
+
+    for f in profiler.dirpath.listdir():
+        assert f.read_text('utf-8')
+
+
+def test_simple_profiler_logs(tmpdir, caplog, simple_profiler):
+    """Ensure that the number of printed logs is correct"""
+    model = BoringModel()
+    trainer = Trainer(
+        default_root_dir=tmpdir,
+        fast_dev_run=2,
+        profiler=simple_profiler,
+        logger=False,
+    )
+    with caplog.at_level(logging.INFO, logger="pytorch_lightning.profiler.profilers"):
+        trainer.fit(model)
+        trainer.test(model)
+
+    assert caplog.text.count("Profiler Report") == 2
+
+
 @pytest.fixture
 def advanced_profiler(tmpdir):
     return AdvancedProfiler(dirpath=tmpdir, filename="profiler")

From 58dcd4e4a9ecc52325ec6739f386a55a2dfb3e73 Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Mon, 22 Mar 2021 20:35:42 +0100
Subject: [PATCH 55/87] Typo

---
 pytorch_lightning/profiler/profilers.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index 481f107dbf1b9..ac12be5c5897a 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -155,7 +155,7 @@ def describe(self) -> None:
         self.teardown(stage=self._stage)
 
     def _stats_to_str(self, stats: Dict[str, str]) -> str:
-        output = [f"{self._stage} " if self._stage is not None else "" + "Profiler report"]
+        output = [f"{self._stage} " if self._stage is not None else "" + "Profiler Report"]
         for action, value in stats.items():
             header = f"Profile stats for: {action}"
             if self._local_rank is not None:

From c37162f1cc22a444a5ee629e080b4da1fc633bfd Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Mon, 22 Mar 2021 20:45:05 +0100
Subject: [PATCH 56/87] Address comments

---
 pytorch_lightning/profiler/profilers.py | 6 +++---
 tests/test_profiler.py                  | 3 ++-
 2 files changed, 5 insertions(+), 4 deletions(-)

diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index ac12be5c5897a..9754ffb3122d1 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -22,7 +22,7 @@
 from collections import defaultdict
 from contextlib import contextmanager
 from pathlib import Path
-from typing import Dict, Optional, Tuple, Union, TextIO, Callable
+from typing import Dict, Optional, Tuple, Union, TextIO, Callable, Any
 
 import numpy as np
 
@@ -48,11 +48,11 @@ def summary(self) -> str:
         """Create profiler summary in text format."""
 
     @abstractmethod
-    def setup(self) -> None:
+    def setup(self, **kwargs: Any) -> None:
         """Execute arbitrary pre-profiling set-up steps as defined by subclass."""
 
     @abstractmethod
-    def teardown(self) -> None:
+    def teardown(self, **kwargs: Any) -> None:
         """Execute arbitrary post-profiling tear-down steps as defined by subclass."""
 
 
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 8104745dddcab..c8d68ef66cf4a 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -137,10 +137,11 @@ def test_simple_profiler_distributed_files(tmpdir):
         logger=False,
     )
     trainer.fit(model)
+    trainer.validate(model)
     trainer.test(model)
 
     actual = set(os.listdir(profiler.dirpath))
-    expected = {'fit-profiler-0.txt', 'fit-profiler-1.txt', 'test-profiler-0.txt', 'test-profiler-1.txt'}
+    expected = {f"{stage}-profiler-{rank}.txt" for stage in ("fit", "validate", "test") for rank in (0, 1)}
     assert actual == expected
 
     for f in profiler.dirpath.listdir():

From 4c5f1f3aacb483a6a0216ebf5995242fbe78426a Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Mon, 22 Mar 2021 21:03:24 +0100
Subject: [PATCH 57/87] deepcopy tests

---
 pytorch_lightning/profiler/profilers.py |  3 ++-
 tests/test_profiler.py                  | 17 +++++++++++++++++
 2 files changed, 19 insertions(+), 1 deletion(-)

diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index 9754ffb3122d1..a1be0bf4d5885 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -178,12 +178,13 @@ def setup(
     def teardown(self, stage: Optional[str] = None) -> None:
         """
         Execute arbitrary post-profiling tear-down steps.
-        
+
         Closes the currently open file and stream.
         """
         self._write_stream = None
         if self._output_file is not None:
             self._output_file.close()
+            self._output_file = None  # can't pickle TextIOWrapper
 
     def __del__(self) -> None:
         self.teardown(stage=self._stage)
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index c8d68ef66cf4a..e1bdc67938ec0 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -14,6 +14,7 @@
 import logging
 import os
 import time
+from copy import deepcopy
 from distutils.version import LooseVersion
 
 import numpy as np
@@ -105,6 +106,12 @@ def test_simple_profiler_value_errors(simple_profiler):
     simple_profiler.stop(action)
 
 
+def test_simple_profiler_deepcopy(tmpdir):
+    simple_profiler = SimpleProfiler(dirpath=tmpdir, filename="test")
+    simple_profiler.describe()
+    assert deepcopy(simple_profiler)
+
+
 def test_simple_profiler_log_dir(tmpdir):
     """Ensure the profiler dirpath defaults to `trainer.log_dir` when not present"""
     profiler = SimpleProfiler(filename="profiler")
@@ -243,6 +250,11 @@ def test_advanced_profiler_value_errors(advanced_profiler):
     advanced_profiler.stop(action)
 
 
+def test_advanced_profiler_deepcopy(advanced_profiler):
+    advanced_profiler.describe()
+    assert deepcopy(advanced_profiler)
+
+
 @pytest.fixture
 def pytorch_profiler(tmpdir):
     return PyTorchProfiler(dirpath=tmpdir, filename="profiler")
@@ -369,3 +381,8 @@ def on_fit_end(self, trainer, *args, **kwargs) -> None:
     trainer.fit(model)
 
     assert profiler._output_file.closed
+
+
+def test_pytorch_profiler_deepcopy(pytorch_profiler):
+    pytorch_profiler.describe()
+    assert deepcopy(pytorch_profiler)

From 5ed73fbeafd107bd4573ae21a056abd1b8c8d0f4 Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Mon, 22 Mar 2021 21:16:29 +0100
Subject: [PATCH 58/87] Advanced teardown

---
 pytorch_lightning/profiler/profilers.py | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index a1be0bf4d5885..766dd94ff93d9 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -344,7 +344,7 @@ def __init__(
                 If you attempt to stop recording an action which was never started.
         """
         super().__init__(dirpath=dirpath, filename=filename, output_filename=output_filename)
-        self.profiled_actions = {}
+        self.profiled_actions: Dict[str, cProfile.Profile] = {}
         self.line_count_restriction = line_count_restriction
 
     def start(self, action_name: str) -> None:
@@ -366,3 +366,7 @@ def summary(self) -> str:
             ps.print_stats(self.line_count_restriction)
             recorded_stats[action_name] = s.getvalue()
         return self._stats_to_str(recorded_stats)
+
+    def teardown(self, stage: Optional[str] = None) -> None:
+        super().teardown(stage=stage)
+        self.profiled_actions = {}

From 897f8e52247bc022a59b632a38621d31d05896c5 Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Mon, 22 Mar 2021 21:19:57 +0100
Subject: [PATCH 59/87] Fix teardown test

---
 tests/test_profiler.py | 7 +++----
 1 file changed, 3 insertions(+), 4 deletions(-)

diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index e1bdc67938ec0..29455e4d532b1 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -370,17 +370,16 @@ def test_profiler_teardown(tmpdir, cls):
     This test checks if profiler teardown method is called when trainer is exiting.
     """
     class TestCallback(Callback):
-
         def on_fit_end(self, trainer, *args, **kwargs) -> None:
-            assert trainer.profiler._output_file is not None
+            # describe sets it to None
+            assert trainer.profiler._output_file is None
 
     profiler = cls(dirpath=tmpdir, filename="profiler")
-
     model = BoringModel()
     trainer = Trainer(default_root_dir=tmpdir, fast_dev_run=True, profiler=profiler, callbacks=[TestCallback()])
     trainer.fit(model)
 
-    assert profiler._output_file.closed
+    assert profiler._output_file is None
 
 
 def test_pytorch_profiler_deepcopy(pytorch_profiler):

From e42be2a5afd920dcc9178c3b6dfaed80a2f67df0 Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Mon, 22 Mar 2021 22:10:49 +0100
Subject: [PATCH 60/87] Fix tests

---
 tests/test_profiler.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 29455e4d532b1..12f6526fb217e 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -131,6 +131,7 @@ def test_simple_profiler_log_dir(tmpdir):
     assert expected.join("fit-profiler.txt").exists()
 
 
+@RunIf(skip_windows=True)
 def test_simple_profiler_distributed_files(tmpdir):
     """Ensure the proper files are saved in distributed"""
     profiler = SimpleProfiler(dirpath=tmpdir, filename='profiler')
@@ -299,7 +300,7 @@ def test_pytorch_profiler_trainer_ddp(tmpdir, pytorch_profiler):
     assert len(pytorch_profiler.summary()) > 0
     assert set(pytorch_profiler.profiled_actions.keys()) == {'training_step_and_backward', 'validation_step'}
 
-    path = pytorch_profiler.dirpath / pytorch_profiler.filename
+    path = pytorch_profiler.dirpath / f"{pytorch_profiler.filename}.txt"
     data = path.read_text("utf-8")
     assert len(data) > 0
 

From 32c301cd575d828cc9decec95b43c7e31c234e35 Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Mon, 22 Mar 2021 22:12:06 +0100
Subject: [PATCH 61/87] Minor change

---
 tests/test_profiler.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 12f6526fb217e..3b9f96350d891 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -301,8 +301,7 @@ def test_pytorch_profiler_trainer_ddp(tmpdir, pytorch_profiler):
     assert set(pytorch_profiler.profiled_actions.keys()) == {'training_step_and_backward', 'validation_step'}
 
     path = pytorch_profiler.dirpath / f"{pytorch_profiler.filename}.txt"
-    data = path.read_text("utf-8")
-    assert len(data) > 0
+    assert path.read_text("utf-8")
 
 
 def test_pytorch_profiler_nested(tmpdir):

From af0c8adce8a734ddbddb6ea5cf3f8658e2979d74 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Carlos=20Mochol=C3=AD?= <carlossmocholi@gmail.com>
Date: Mon, 22 Mar 2021 22:17:19 +0100
Subject: [PATCH 62/87] Update CHANGELOG.md

---
 CHANGELOG.md | 3 ---
 1 file changed, 3 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index e188d5968cf77..1c0dfd5a482b7 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -54,9 +54,6 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Added `AbstractProfiler` interface ([#6621](https://github.com/PyTorchLightning/pytorch-lightning/pull/6621))
 
 
-- Added `setup` method to `BaseProfiler` to enable subclasses defining pre-profiling steps ([#6621](https://github.com/PyTorchLightning/pytorch-lightning/pull/6621))
-
-
 - Added `outputs` parameter to callback's `on_validation_epoch_end` & `on_test_epoch_end` hooks ([#6120](https://github.com/PyTorchLightning/pytorch-lightning/pull/6120))
 
 

From 29a73c57c1e5d437be54a040f890f8c3288a4778 Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Mon, 22 Mar 2021 22:43:33 +0100
Subject: [PATCH 63/87] Fix test

---
 tests/test_profiler.py | 10 +++++++---
 1 file changed, 7 insertions(+), 3 deletions(-)

diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 3b9f96350d891..dca14f9a02736 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -298,10 +298,14 @@ def test_pytorch_profiler_trainer_ddp(tmpdir, pytorch_profiler):
     trainer.fit(model)
 
     assert len(pytorch_profiler.summary()) > 0
-    assert set(pytorch_profiler.profiled_actions.keys()) == {'training_step_and_backward', 'validation_step'}
+    assert set(pytorch_profiler.profiled_actions) == {'training_step_and_backward', 'validation_step'}
 
-    path = pytorch_profiler.dirpath / f"{pytorch_profiler.filename}.txt"
-    assert path.read_text("utf-8")
+    actual = set(os.listdir(pytorch_profiler.dirpath))
+    expected = {f"fit-profiler-{rank}.txt" for rank in (0, 1)}
+    assert actual == expected
+
+    for f in pytorch_profiler.dirpath.listdir():
+        assert f.read_text('utf-8')
 
 
 def test_pytorch_profiler_nested(tmpdir):

From 0dc1e065f4b03747ae907ecd4fd242b2df6ef3d0 Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Mon, 22 Mar 2021 23:42:54 +0100
Subject: [PATCH 64/87] Quick fixes

---
 .gitignore                                    |  2 +-
 pytorch_lightning/profiler/pytorch.py         | 12 +++++-----
 .../trainer/connectors/profiler_connector.py  |  3 ++-
 tests/test_profiler.py                        | 23 ++-----------------
 4 files changed, 11 insertions(+), 29 deletions(-)

diff --git a/.gitignore b/.gitignore
index c007140257188..99939ff7fce0c 100644
--- a/.gitignore
+++ b/.gitignore
@@ -157,4 +157,4 @@ tags
 data
 MNIST
 runs
-*traces*
+*trace*
diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index f72dcba802612..4cb62c26ea4db 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -235,8 +235,8 @@ def setup(
 
         # if the user didn't provide `path_to_export_trace`,
         # set it as TensorBoardLogger log_dir if exists
-        if self.path_to_export_trace is None:
-            self.path_to_export_trace = log_dir
+        if self._path_to_export_trace is None:
+            self._path_to_export_trace = log_dir
 
     def start(self, action_name: str) -> None:
         if not self._profiler_instantiated and action_name in (
@@ -278,7 +278,7 @@ def summary(self) -> str:
         if not self._profiler_kwargs.get("enabled", True):
             return ""
 
-        local_rank = 0 if self.local_rank is None else self.local_rank
+        local_rank = 0 if self._local_rank is None else self._local_rank
 
         self.profiler.__exit__(None, None, None)
         if not self._emit_nvtx:
@@ -309,7 +309,7 @@ def summary(self) -> str:
         recorded_stats = {}
         recorded_stats["records"] = table
 
-        return self.stats_to_str(recorded_stats)
+        return self._stats_to_str(recorded_stats)
 
     def _create_profilers(self) -> None:
         if self._emit_nvtx:
@@ -321,10 +321,10 @@ def _create_profilers(self) -> None:
 
     def _create_profiler(self, profiler: Type[_PROFILER]) -> _PROFILER:
         init_parameters = inspect.signature(profiler.__init__).parameters
-        kwargs = {k: v for k, v in vars(self).items() if k in init_parameters}
+        kwargs = {k: v for k, v in self._profiler_kwargs.items() if k in init_parameters}
         return profiler(**kwargs)
 
-    def teardown(self):
+    def teardown(self, stage: Optional[str] = None) -> None:
         if self.profiler is not None:
             self.profiler.__exit__(None, None, None)
 
diff --git a/pytorch_lightning/trainer/connectors/profiler_connector.py b/pytorch_lightning/trainer/connectors/profiler_connector.py
index e628d6d96bd19..191e8711463ab 100644
--- a/pytorch_lightning/trainer/connectors/profiler_connector.py
+++ b/pytorch_lightning/trainer/connectors/profiler_connector.py
@@ -11,8 +11,8 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License
-
 from typing import Union
+from weakref import proxy
 
 from pytorch_lightning.profiler import (
     AdvancedProfiler,
@@ -57,4 +57,5 @@ def on_trainer_init(self, profiler: Union[BaseProfiler, str]):
     def setup(self) -> None:
         trainer = self.trainer
         local_rank = trainer.local_rank if trainer.world_size > 1 else None
+        trainer.profiler.lightning_module = proxy(trainer.lightning_module)
         trainer.profiler.setup(stage=trainer._setup_state, local_rank=local_rank, log_dir=trainer.log_dir)
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index f275dc7c0e08e..423ab3e9ecb7b 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -289,25 +289,6 @@ def test_pytorch_profiler_value_errors(pytorch_profiler):
 
 
 @RunIf(min_gpus=2, special=True)
-def test_pytorch_profiler_trainer_ddp(tmpdir, pytorch_profiler):
-    """Ensure that the profiler can be given to the training and default step are properly recorded. """
-    model = BoringModel()
-    trainer = Trainer(
-        max_epochs=1,
-        default_root_dir=tmpdir,
-        limit_train_batches=6,
-        limit_val_batches=6,
-        profiler=pytorch_profiler,
-        accelerator="ddp",
-        gpus=2,
-        logger=TensorBoardLogger(tmpdir)
-    )
-    trainer.fit(model)
-
-    path = pytorch_profiler.dirpath / f"{pytorch_profiler.filename}.txt"
-    assert path.read_text("utf-8")
-
-
 def test_pytorch_profiler_trainer_fit(tmpdir, pytorch_profiler):
     """Ensure that the profiler can be given to the trainer and training, validation steps are properly recorded. """
 
@@ -349,7 +330,7 @@ def test_pytorch_profiler_trainer_test(tmpdir, pytorch_profiler):
 
     assert len([e for e in pytorch_profiler.function_events if 'test_step' == e.name]) > 0
 
-    path = pytorch_profiler.dirpath / f"{pytorch_profiler.filename}.txt"
+    path = pytorch_profiler.dirpath / f"test-{pytorch_profiler.filename}.txt"
     assert path.read_text("utf-8")
 
 
@@ -367,7 +348,7 @@ def test_pytorch_profiler_trainer_predict(tmpdir, pytorch_profiler):
 
     assert len([e for e in pytorch_profiler.function_events if 'predict' == e.name]) > 0
 
-    path = pytorch_profiler.dirpath / f"{pytorch_profiler.filename}.txt"
+    path = pytorch_profiler.dirpath / f"predict-{pytorch_profiler.filename}.txt"
     assert path.read_text("utf-8")
 
 

From cb756b813573c8619936c32cdf528d623c4794d8 Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Tue, 23 Mar 2021 00:32:52 +0100
Subject: [PATCH 65/87] Fix 6522

---
 .gitignore                              |  2 +-
 pytorch_lightning/profiler/profilers.py | 13 +++++++++++--
 tests/test_profiler.py                  | 16 +++++++++++++++-
 3 files changed, 27 insertions(+), 4 deletions(-)

diff --git a/.gitignore b/.gitignore
index c007140257188..99939ff7fce0c 100644
--- a/.gitignore
+++ b/.gitignore
@@ -157,4 +157,4 @@ tags
 data
 MNIST
 runs
-*traces*
+*trace*
diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index 766dd94ff93d9..3875514621025 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -22,7 +22,7 @@
 from collections import defaultdict
 from contextlib import contextmanager
 from pathlib import Path
-from typing import Dict, Optional, Tuple, Union, TextIO, Callable, Any
+from typing import Any, Callable, Dict, Optional, TextIO, Tuple, Union
 
 import numpy as np
 
@@ -155,7 +155,8 @@ def describe(self) -> None:
         self.teardown(stage=self._stage)
 
     def _stats_to_str(self, stats: Dict[str, str]) -> str:
-        output = [f"{self._stage} " if self._stage is not None else "" + "Profiler Report"]
+        stage = f"{self._stage.upper()} " if self._stage is not None else ""
+        output = [stage + "Profiler Report"]
         for action, value in stats.items():
             header = f"Profile stats for: {action}"
             if self._local_rank is not None:
@@ -370,3 +371,11 @@ def summary(self) -> str:
     def teardown(self, stage: Optional[str] = None) -> None:
         super().teardown(stage=stage)
         self.profiled_actions = {}
+
+    def __reduce__(self):
+        # avoids `TypeError: cannot pickle 'cProfile.Profile' object`
+        return (
+            self.__class__,
+            tuple(),
+            dict(dirpath=self.dirpath, filename=self.filename, line_count_restriction=self.line_count_restriction),
+        )
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index dca14f9a02736..4ec259101dc4a 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -21,7 +21,7 @@
 import pytest
 import torch
 
-from pytorch_lightning import Trainer, Callback
+from pytorch_lightning import Callback, Trainer
 from pytorch_lightning.profiler import AdvancedProfiler, PyTorchProfiler, SimpleProfiler
 from tests.helpers import BoringModel
 from tests.helpers.runif import RunIf
@@ -284,6 +284,18 @@ def test_pytorch_profiler_value_errors(pytorch_profiler):
     pytorch_profiler.stop(action)
 
 
+def test_advanced_profiler_cprofile_deepcopy(tmpdir):
+    """Checks for pickle issue reported in #6522"""
+    model = BoringModel()
+    trainer = Trainer(
+        default_root_dir=tmpdir,
+        fast_dev_run=True,
+        profiler="advanced",
+        stochastic_weight_avg=True,
+    )
+    trainer.fit(model)
+
+
 @RunIf(min_gpus=2, special=True)
 def test_pytorch_profiler_trainer_ddp(tmpdir, pytorch_profiler):
     """Ensure that the profiler can be given to the training and default step are properly recorded. """
@@ -373,7 +385,9 @@ def test_profiler_teardown(tmpdir, cls):
     """
     This test checks if profiler teardown method is called when trainer is exiting.
     """
+
     class TestCallback(Callback):
+
         def on_fit_end(self, trainer, *args, **kwargs) -> None:
             # describe sets it to None
             assert trainer.profiler._output_file is None

From 758b9420499daa7824efe94cee5369323a09967b Mon Sep 17 00:00:00 2001
From: thomas chaton <thomas@grid.ai>
Date: Tue, 23 Mar 2021 08:41:11 +0000
Subject: [PATCH 66/87] resolve ddp tests

---
 pytorch_lightning/profiler/profilers.py | 11 ++++++++---
 pytorch_lightning/profiler/pytorch.py   |  4 +---
 tests/test_profiler.py                  | 22 ++++++++++++++--------
 3 files changed, 23 insertions(+), 14 deletions(-)

diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index 3875514621025..42c9539185fc9 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -124,9 +124,8 @@ def _prepare_filename(self) -> str:
         filename = ""
         if self._stage is not None:
             filename += f"{self._stage}-"
-        filename += self.filename
-        if self._local_rank is not None:
-            filename += f"-{self._local_rank}"
+        filename += str(self.filename)
+        filename += f"-{self.local_rank}"
         filename += ".txt"
         return filename
 
@@ -175,6 +174,8 @@ def setup(
         self._stage = stage
         self._local_rank = local_rank
         self._log_dir = log_dir
+        if self.dirpath is None:
+            self.dirpath = self._log_dir
 
     def teardown(self, stage: Optional[str] = None) -> None:
         """
@@ -199,6 +200,10 @@ def stop(self, action_name: str) -> None:
     def summary(self) -> str:
         raise NotImplementedError
 
+    @property
+    def local_rank(self):
+        return '0' if self._local_rank is None else self._local_rank
+
 
 class PassThroughProfiler(BaseProfiler):
     """
diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index 85b3ec7d8d2ed..55b1c286789f4 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -239,7 +239,6 @@ def stop(self, action_name: str) -> None:
     def summary(self) -> str:
         recorded_stats = {}
         output_string = ''
-        local_rank = '0' if self._local_rank is None else self._local_rank
 
         if not self.enabled:
             return output_string
@@ -252,7 +251,7 @@ def summary(self) -> str:
             function_events.populate_cpu_children = lambda: None
 
             if self.export_to_chrome:
-                filename = f"{action_name}_{local_rank}_trace.json"
+                filename = f"{action_name}_{self.local_rank}_trace.json"
                 path_to_trace = filename if self.path_to_export_trace is None \
                     else os.path.join(self.path_to_export_trace, filename)
                 function_events.export_chrome_trace(path_to_trace)
@@ -264,5 +263,4 @@ def summary(self) -> str:
                 data = function_events.key_averages(group_by_input_shapes=self.group_by_input_shapes)
                 table = data.table(sort_by=self.sort_by_key, row_limit=self.row_limit)
                 recorded_stats[action_name] = table
-
         return self._stats_to_str(recorded_stats)
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 4ec259101dc4a..5114d39d209ea 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -13,6 +13,7 @@
 # limitations under the License.
 import logging
 import os
+from pathlib import Path
 import time
 from copy import deepcopy
 from distutils.version import LooseVersion
@@ -297,12 +298,15 @@ def test_advanced_profiler_cprofile_deepcopy(tmpdir):
 
 
 @RunIf(min_gpus=2, special=True)
-def test_pytorch_profiler_trainer_ddp(tmpdir, pytorch_profiler):
+def test_pytorch_profiler_trainer_ddp(tmpdir):
     """Ensure that the profiler can be given to the training and default step are properly recorded. """
+    pytorch_profiler = PyTorchProfiler(dirpath=None, filename="profiler")
     model = BoringModel()
     trainer = Trainer(
+        max_epochs=1,
         default_root_dir=tmpdir,
-        fast_dev_run=True,
+        limit_train_batches=2,
+        limit_val_batches=2,
         profiler=pytorch_profiler,
         accelerator="ddp",
         gpus=2,
@@ -312,12 +316,14 @@ def test_pytorch_profiler_trainer_ddp(tmpdir, pytorch_profiler):
     assert len(pytorch_profiler.summary()) > 0
     assert set(pytorch_profiler.profiled_actions) == {'training_step_and_backward', 'validation_step'}
 
-    actual = set(os.listdir(pytorch_profiler.dirpath))
-    expected = {f"fit-profiler-{rank}.txt" for rank in (0, 1)}
-    assert actual == expected
-
-    for f in pytorch_profiler.dirpath.listdir():
-        assert f.read_text('utf-8')
+    files = sorted(f for f in os.listdir(pytorch_profiler.dirpath) if "fit" in f)
+    rank = int(os.getenv("LOCAL_RANK", "0"))
+    expected = f"fit-profiler-{rank}.txt"
+    assert files[rank] == expected
+    
+    path = os.path.join(pytorch_profiler.dirpath, expected)
+    data = Path(path).read_text("utf-8")
+    assert len(data) > 0
 
 
 def test_pytorch_profiler_nested(tmpdir):

From fca4eb2d2753e75721a4a089d48d5d8250ebaacc Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Tue, 23 Mar 2021 08:44:24 +0000
Subject: [PATCH 67/87] resolve tests

---
 tests/test_profiler.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 5114d39d209ea..b6728a8b0ac1f 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -13,10 +13,10 @@
 # limitations under the License.
 import logging
 import os
-from pathlib import Path
 import time
 from copy import deepcopy
 from distutils.version import LooseVersion
+from pathlib import Path
 
 import numpy as np
 import pytest
@@ -285,6 +285,7 @@ def test_pytorch_profiler_value_errors(pytorch_profiler):
     pytorch_profiler.stop(action)
 
 
+@RunIf(min_torch="1.6.0")
 def test_advanced_profiler_cprofile_deepcopy(tmpdir):
     """Checks for pickle issue reported in #6522"""
     model = BoringModel()
@@ -320,7 +321,7 @@ def test_pytorch_profiler_trainer_ddp(tmpdir):
     rank = int(os.getenv("LOCAL_RANK", "0"))
     expected = f"fit-profiler-{rank}.txt"
     assert files[rank] == expected
-    
+
     path = os.path.join(pytorch_profiler.dirpath, expected)
     data = Path(path).read_text("utf-8")
     assert len(data) > 0

From 2919a392610e5f474b1434c8a3160172722b9a71 Mon Sep 17 00:00:00 2001
From: thomas chaton <thomas@grid.ai>
Date: Tue, 23 Mar 2021 09:14:06 +0000
Subject: [PATCH 68/87] resolve some tests

---
 pytorch_lightning/profiler/profilers.py | 3 ++-
 tests/test_profiler.py                  | 4 ++--
 2 files changed, 4 insertions(+), 3 deletions(-)

diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index 42c9539185fc9..54bc5cdf0122c 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -125,7 +125,8 @@ def _prepare_filename(self) -> str:
         if self._stage is not None:
             filename += f"{self._stage}-"
         filename += str(self.filename)
-        filename += f"-{self.local_rank}"
+        if self._local_rank is not None:
+            filename += f"-{self.local_rank}"
         filename += ".txt"
         return filename
 
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index b6728a8b0ac1f..cf6afcc9b626c 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -126,10 +126,10 @@ def test_simple_profiler_log_dir(tmpdir):
     )
     trainer.fit(model)
 
-    expected = tmpdir / "lightning_logs" / "version_0"
+    expected = profiler.dirpath
     assert trainer.log_dir == expected
     assert profiler._log_dir == trainer.log_dir
-    assert expected.join("fit-profiler.txt").exists()
+    assert Path(os.path.join(profiler.dirpath, "fit-profiler.txt")).exists()
 
 
 @RunIf(skip_windows=True)

From d7ca5fa8563b559fc20b32e4d0334b7d8ace15e1 Mon Sep 17 00:00:00 2001
From: thomas chaton <thomas@grid.ai>
Date: Tue, 23 Mar 2021 09:31:51 +0000
Subject: [PATCH 69/87] update tests

---
 tests/trainer/properties/test_get_model.py | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/tests/trainer/properties/test_get_model.py b/tests/trainer/properties/test_get_model.py
index 4dc5b5f34b50c..af0cc291154c0 100644
--- a/tests/trainer/properties/test_get_model.py
+++ b/tests/trainer/properties/test_get_model.py
@@ -84,8 +84,7 @@ def test_get_model_gpu(tmpdir):
 
 
 @RunIf(min_gpus=1, skip_windows=True)
-@DDPLauncher.run("--accelerator [accelerator]", max_epochs=["1"], accelerator=["ddp", "ddp_spawn"])
-def test_get_model_ddp_gpu(tmpdir, args=None):
+def test_get_model_ddp_gpu(tmpdir):
     """
     Tests that `trainer.lightning_module` extracts the model correctly when using GPU + ddp accelerators
     """
@@ -99,7 +98,6 @@ def test_get_model_ddp_gpu(tmpdir, args=None):
         limit_val_batches=2,
         max_epochs=1,
         gpus=1,
-        accelerator=args.accelerator
     )
     trainer.fit(model)
     return 1

From b3ffe64ebc28bfb104d05954063efb57974dcd62 Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Tue, 23 Mar 2021 10:01:41 +0000
Subject: [PATCH 70/87] resolve tests

---
 tests/test_profiler.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index dcb66449b7398..038346277bc1b 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -27,6 +27,7 @@
 from pytorch_lightning.profiler import AdvancedProfiler, PyTorchProfiler, SimpleProfiler
 from pytorch_lightning.profiler.pytorch import RegisterRecordFunction
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
+from pytorch_lightning.utilities.imports import _TORCH_GREATER_EQUAL_1_8
 from tests.helpers import BoringModel
 from tests.helpers.runif import RunIf
 
@@ -504,6 +505,7 @@ def on_fit_end(self, trainer, *args, **kwargs) -> None:
     assert profiler._output_file is None
 
 
+@pytest.mark.skipif(_TORCH_GREATER_EQUAL_1_8, reason="currently not supported for PyTorch 1.8")
 def test_pytorch_profiler_deepcopy(pytorch_profiler):
     pytorch_profiler.start("on_train_start")
     pytorch_profiler.describe()

From 97c87d37a7bb8d65af3e35c645edc998981e6b6d Mon Sep 17 00:00:00 2001
From: thomas chaton <thomas@grid.ai>
Date: Tue, 23 Mar 2021 11:59:20 +0000
Subject: [PATCH 71/87] resolve tests

---
 tests/test_profiler.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index e901a76450106..5719c79d7a1b9 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -504,5 +504,6 @@ def on_fit_end(self, trainer, *args, **kwargs) -> None:
 @pytest.mark.skipif(_TORCH_GREATER_EQUAL_1_8, reason="currently not supported for PyTorch 1.8")
 def test_pytorch_profiler_deepcopy(pytorch_profiler):
     pytorch_profiler.start("on_train_start")
+    torch.tensor(1)
     pytorch_profiler.describe()
     assert deepcopy(pytorch_profiler)

From ae31f00a33d023aefef890e3c9cabf49cf13a565 Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Tue, 23 Mar 2021 13:38:25 +0100
Subject: [PATCH 72/87] Missed fixes from 3/5

---
 pytorch_lightning/profiler/profilers.py    | 12 +++++------
 pytorch_lightning/profiler/pytorch.py      |  4 +---
 tests/checkpointing/test_torch_saving.py   |  3 +--
 tests/test_profiler.py                     | 25 ++++++++--------------
 tests/trainer/properties/test_get_model.py | 20 -----------------
 5 files changed, 16 insertions(+), 48 deletions(-)

diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index 54bc5cdf0122c..1cd49a223af65 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -126,7 +126,7 @@ def _prepare_filename(self) -> str:
             filename += f"{self._stage}-"
         filename += str(self.filename)
         if self._local_rank is not None:
-            filename += f"-{self.local_rank}"
+            filename += f"-{self._local_rank}"
         filename += ".txt"
         return filename
 
@@ -134,8 +134,7 @@ def _prepare_streams(self) -> None:
         if self._write_stream is not None:
             return
         if self.filename:
-            dirpath = self.dirpath or self._log_dir
-            filepath = os.path.join(dirpath, self._prepare_filename())
+            filepath = os.path.join(self.dirpath, self._prepare_filename())
             fs = get_filesystem(filepath)
             file = fs.open(filepath, "a")
             self._output_file = file
@@ -175,8 +174,7 @@ def setup(
         self._stage = stage
         self._local_rank = local_rank
         self._log_dir = log_dir
-        if self.dirpath is None:
-            self.dirpath = self._log_dir
+        self.dirpath = self.dirpath or local_rank
 
     def teardown(self, stage: Optional[str] = None) -> None:
         """
@@ -202,8 +200,8 @@ def summary(self) -> str:
         raise NotImplementedError
 
     @property
-    def local_rank(self):
-        return '0' if self._local_rank is None else self._local_rank
+    def local_rank(self) -> int:
+        return 0 if self._local_rank is None else self._local_rank
 
 
 class PassThroughProfiler(BaseProfiler):
diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index fe4ec89a5dd2c..9aa0ff3d5c925 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -275,8 +275,6 @@ def summary(self) -> str:
         if not self._profiler_kwargs.get("enabled", True):
             return ""
 
-        local_rank = 0 if self._local_rank is None else self._local_rank
-
         self.profiler.__exit__(None, None, None)
         if not self._emit_nvtx:
             self.function_events = self.profiler.function_events
@@ -294,7 +292,7 @@ def summary(self) -> str:
             return ""
 
         if self._export_to_chrome:
-            filename = f"{local_rank}_trace.json"
+            filename = f"{self.local_rank}_trace.json"
             path_to_trace = (
                 filename if self._path_to_export_trace is None else os.path.join(self._path_to_export_trace, filename)
             )
diff --git a/tests/checkpointing/test_torch_saving.py b/tests/checkpointing/test_torch_saving.py
index 0c703a58d57a4..8eabc4640046f 100644
--- a/tests/checkpointing/test_torch_saving.py
+++ b/tests/checkpointing/test_torch_saving.py
@@ -47,8 +47,7 @@ def test_model_torch_save_ddp_cpu(tmpdir):
         max_epochs=num_epochs,
         accelerator="ddp_cpu",
         num_processes=2,
-        profiler=None,
-        logger=None,
+        logger=False,
     )
     temp_path = os.path.join(tmpdir, 'temp.pt')
     trainer.fit(model)
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 5719c79d7a1b9..99f1d74905a5c 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -130,10 +130,10 @@ def test_simple_profiler_log_dir(tmpdir):
     )
     trainer.fit(model)
 
-    expected = profiler.dirpath
+    expected = tmpdir / "lightning_logs" / "version_0"
     assert trainer.log_dir == expected
     assert profiler._log_dir == trainer.log_dir
-    assert Path(os.path.join(profiler.dirpath, "fit-profiler.txt")).exists()
+    assert expected.join("fit-profiler.txt").exists()
 
 
 @RunIf(skip_windows=True)
@@ -278,15 +278,10 @@ def test_pytorch_profiler_describe(pytorch_profiler):
     assert len(data) > 0
 
 
-def test_pytorch_profiler_value_errors(pytorch_profiler):
+def test_pytorch_profiler_raises(pytorch_profiler):
     """Ensure errors are raised where expected."""
-    action = "test_step"
-    pytorch_profiler.start(action)
-    pytorch_profiler.stop(action)
-
     with pytest.raises(MisconfigurationException, match="profiled_functions` and `PyTorchProfiler.record"):
         PyTorchProfiler(profiled_functions=["a"], record_functions=["b"])
-    pytorch_profiler.teardown()
 
 
 @RunIf(min_torch="1.6.0")
@@ -303,9 +298,8 @@ def test_advanced_profiler_cprofile_deepcopy(tmpdir):
 
 
 @RunIf(min_gpus=2, special=True)
-def test_pytorch_profiler_trainer_ddp(tmpdir):
+def test_pytorch_profiler_trainer_ddp(tmpdir, pytorch_profiler):
     """Ensure that the profiler can be given to the training and default step are properly recorded. """
-    pytorch_profiler = PyTorchProfiler(dirpath=None, filename="profiler")
     model = BoringModel()
     trainer = Trainer(
         max_epochs=1,
@@ -320,19 +314,18 @@ def test_pytorch_profiler_trainer_ddp(tmpdir):
 
     expected = ('validation_step', 'training_step_and_backward', 'training_step', 'backward')
     for name in expected:
-        assert len([e for e in pytorch_profiler.function_events if name == e.name]) > 0
+        assert sum(e.name == name for e in pytorch_profiler.function_events)
 
     assert len(pytorch_profiler.summary()) > 0
     assert set(pytorch_profiler.profiled_actions) == {'training_step_and_backward', 'validation_step'}
 
-    files = sorted(f for f in os.listdir(pytorch_profiler.dirpath) if "fit" in f)
-    rank = int(os.getenv("LOCAL_RANK", "0"))
+    files = set(os.listdir(pytorch_profiler.dirpath))
+    rank = int(os.getenv("LOCAL_RANK", 0))
     expected = f"fit-profiler-{rank}.txt"
-    assert files[rank] == expected
+    assert expected in files
 
     path = os.path.join(pytorch_profiler.dirpath, expected)
-    data = Path(path).read_text("utf-8")
-    assert len(data) > 0
+    assert Path(path).read_text()
 
 
 def test_pytorch_profiler_trainer_test(tmpdir, pytorch_profiler):
diff --git a/tests/trainer/properties/test_get_model.py b/tests/trainer/properties/test_get_model.py
index 3eb0596b55fc4..5dc1ea5de4e8a 100644
--- a/tests/trainer/properties/test_get_model.py
+++ b/tests/trainer/properties/test_get_model.py
@@ -80,23 +80,3 @@ def test_get_model_gpu(tmpdir):
         gpus=1,
     )
     trainer.fit(model)
-
-
-@RunIf(min_gpus=1, skip_windows=True)
-def test_get_model_ddp_gpu(tmpdir):
-    """
-    Tests that `trainer.lightning_module` extracts the model correctly when using GPU + ddp accelerators
-    """
-
-    model = TrainerGetModel()
-
-    limit_train_batches = 2
-    trainer = Trainer(
-        default_root_dir=tmpdir,
-        limit_train_batches=limit_train_batches,
-        limit_val_batches=2,
-        max_epochs=1,
-        gpus=1,
-    )
-    trainer.fit(model)
-    return 1

From 78970d55b8c14d3a02a518e25f1fadb911c7ad47 Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Tue, 23 Mar 2021 14:03:16 +0100
Subject: [PATCH 73/87] Fixes

---
 pytorch_lightning/profiler/profilers.py   |  2 +-
 pytorch_lightning/profiler/pytorch.py     | 74 +++++++++++++----------
 pytorch_lightning/trainer/predict_loop.py |  3 +-
 3 files changed, 44 insertions(+), 35 deletions(-)

diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index 1cd49a223af65..46d72583fb466 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -174,7 +174,7 @@ def setup(
         self._stage = stage
         self._local_rank = local_rank
         self._log_dir = log_dir
-        self.dirpath = self.dirpath or local_rank
+        self.dirpath = self.dirpath or log_dir
 
     def teardown(self, stage: Optional[str] = None) -> None:
         """
diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index 9aa0ff3d5c925..bfcd08146aeab 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -17,16 +17,22 @@
 import os
 from functools import partial
 from pathlib import Path
-from typing import Any, Dict, List, Optional, Type, Union
+from typing import Any, Dict, List, Optional, Type, TYPE_CHECKING, Union
 
 import torch
 from torch import nn, Tensor
-from torch.autograd.profiler import EventList, record_function
+from torch.autograd.profiler import record_function
 
 from pytorch_lightning.profiler.profilers import BaseProfiler
 from pytorch_lightning.utilities.distributed import rank_zero_warn
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 
+if TYPE_CHECKING:
+    from torch.autograd.profiler import EventList
+    from torch.utils.hooks import RemovableHandle
+
+    from pytorch_lightning.core.lightning import LightningModule
+
 log = logging.getLogger(__name__)
 
 _PROFILER = Union[torch.autograd.profiler.profile, torch.cuda.profiler.profile, torch.autograd.profiler.emit_nvtx]
@@ -34,40 +40,42 @@
 
 class RegisterRecordFunction:
     """
-    While profiling autograd operations, this class will add label with module name
-    around the forward function.
-    The Lightning PyTorch Profiler will activate this feature automatically.
-    It can be deactivated as follows:
+    While profiling autograd operations, this class will add labels for module names around the forward function.
+
+    The Lightning PyTorch Profiler will activate this feature automatically. It can be deactivated as follows:
+
     Example::
         from pytorch_lightning.profilers import PyTorchProfiler
         profiler = PyTorchProfiler(record_module_names=False)
         Trainer(profiler=profiler)
+
     It can be used outside of Lightning as follows:
+
     Example::
         from pytorch_lightning import Trainer, seed_everything
         with RegisterRecordFunction(model):
             out = model(batch)
     """
 
-    def __init__(self, model: nn.Module):
+    def __init__(self, model: nn.Module) -> None:
         self._model = model
-        self._records = {}
-        self.handles = {}
+        self._records: Dict[str, record_function] = {}
+        self._handles: Dict[str, List['RemovableHandle']] = {}
 
-    def _start_recording_forward(self, module: nn.Module, input: Tensor, record_name: str):
+    def _start_recording_forward(self, _: nn.Module, input: Tensor, record_name: str) -> Tensor:
         record = record_function(record_name)
         record.__enter__()
         self._records[record_name] = record
         return input
 
-    def _stop_recording_forward(self, module: nn.Module, input: Tensor, output: Tensor, record_name: str):
+    def _stop_recording_forward(self, _: nn.Module, __: Tensor, output: Tensor, record_name: str) -> Tensor:
         self._records[record_name].__exit__(None, None, None)
         return output
 
-    def __enter__(self):
+    def __enter__(self) -> None:
         for module_name, module in self._model.named_modules():
-            if module_name != '':
-                full_name = type(module).__module__ + '.' + type(module).__name__
+            if module_name:
+                full_name = f"{type(module).__module__}.{type(module).__name__}"
                 record_name = f"{full_name}: {module_name}"
                 pre_forward_handle = module.register_forward_pre_hook(
                     partial(self._start_recording_forward, record_name=record_name)
@@ -76,12 +84,13 @@ def __enter__(self):
                     partial(self._stop_recording_forward, record_name=record_name)
                 )
 
-                self.handles[module_name] = [pre_forward_handle, post_forward_handle]
+                self._handles[module_name] = [pre_forward_handle, post_forward_handle]
 
-    def __exit__(self, exc_type: Any, exc_value: Any, traceback: Any):
-        for handles in self.handles.values():
+    def __exit__(self, exc_type: Any, exc_value: Any, traceback: Any) -> None:
+        for handles in self._handles.values():
             for h in handles:
                 h.remove()
+        self._handles = {}
 
 
 class PyTorchProfiler(BaseProfiler):
@@ -174,23 +183,23 @@ def __init__(
 
         record_functions = self.__deprecation_check(profiled_functions, record_functions)
 
-        self.profiler: Optional[_PROFILER] = None
-        self.function_events: Optional[EventList] = None
-
-        self._record_functions = set(record_functions + list(self.RECORD_FUNCTIONS))
-        self._sort_by_key = sort_by_key or f"{'cuda' if profiler_kwargs.get('use_cuda', False) else 'cpu'}_time_total"
         self._group_by_input_shapes = group_by_input_shapes and profiler_kwargs.get("record_shapes", False)
-        self._row_limit = row_limit
         self._emit_nvtx = emit_nvtx
         self._export_to_chrome = export_to_chrome
         self._path_to_export_trace = path_to_export_trace
+        self._row_limit = row_limit
+        self._sort_by_key = sort_by_key or f"{'cuda' if profiler_kwargs.get('use_cuda', False) else 'cpu'}_time_total"
+        self._record_functions = set(record_functions + list(self.RECORD_FUNCTIONS))
         self._record_module_names = record_module_names
-        self._lightning_module = None  # set by ProfilerConnector
-        self._register = None
         self._profiler_kwargs = profiler_kwargs
-        self._parent_profiler = None
+
+        self.profiler: Optional[_PROFILER] = None
+        self.function_events: Optional['EventList'] = None
+        self._lightning_module: Optional['LightningModule'] = None  # set by ProfilerConnector
+        self._register: Optional[RegisterRecordFunction] = None
+        self._parent_profiler: Optional[_PROFILER] = None
         self._recording_map: Dict[str, record_function] = {}
-        self._profiler_instantiated: bool = False
+        self._profiler_instantiated = False
 
         if self._export_to_chrome and self._path_to_export_trace is None:
             rank_zero_warn(
@@ -203,8 +212,11 @@ def __init__(
                 f"Found sort_by_key: {self._sort_by_key}. Should be within {self.AVAILABLE_SORT_KEYS}. "
             )
 
-    def __deprecation_check(self, profiled_functions: Optional[List[str]],
-                            record_functions: Optional[List[str]]) -> List[str]:
+    def __deprecation_check(
+        self,
+        profiled_functions: Optional[List[str]],
+        record_functions: Optional[List[str]],
+    ) -> List[str]:
         if record_functions is None:
             record_functions = []
 
@@ -213,15 +225,13 @@ def __deprecation_check(self, profiled_functions: Optional[List[str]],
                 "`PyTorchProfiler.profiled_functions` has been renamed to"
                 " `record_functions` in v1.3 and will be removed in v1.5", DeprecationWarning
             )
-            if (len(record_functions) == 0 or len(profiled_functions) == 0):
+            if not record_functions:
                 record_functions += profiled_functions
             else:
                 raise MisconfigurationException(
                     "You set `PytorchProfiler.profiled_functions` and `PyTorchProfiler.record_functions`."
                     "  Please use only the later."
                 )
-        if record_functions is None:
-            record_functions = []
 
         return record_functions
 
diff --git a/pytorch_lightning/trainer/predict_loop.py b/pytorch_lightning/trainer/predict_loop.py
index fe0719aa14da9..97f8da1e41368 100644
--- a/pytorch_lightning/trainer/predict_loop.py
+++ b/pytorch_lightning/trainer/predict_loop.py
@@ -88,8 +88,7 @@ def predict(self, batch, batch_idx, dataloader_idx):
         return
 
     def on_predict_epoch_end(self):
-        if self.trainer.profiler is not None:
-            self.trainer.profiler.describe()
+        self.trainer.profiler.describe()
 
         self.trainer._progress_bar_callback.on_predict_end(self.trainer, self.trainer.lightning_module)
 

From ba067fdcfe75eaa5a3325328546d27777eef623c Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Tue, 23 Mar 2021 14:31:45 +0100
Subject: [PATCH 74/87] Broken refactor

---
 pytorch_lightning/profiler/pytorch.py | 56 ++++++++++-----------------
 1 file changed, 21 insertions(+), 35 deletions(-)

diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index bfcd08146aeab..dcf7e4696bd0e 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -176,8 +176,6 @@ def __init__(
         Raises:
             MisconfigurationException:
                 If arg ``sort_by_key`` is not present in ``AVAILABLE_SORT_KEYS``.
-            ValueError:
-                If you attempt to stop recording an action which was never started.
         """
         super().__init__(dirpath=dirpath, filename=filename, output_filename=output_filename)
 
@@ -199,7 +197,6 @@ def __init__(
         self._register: Optional[RegisterRecordFunction] = None
         self._parent_profiler: Optional[_PROFILER] = None
         self._recording_map: Dict[str, record_function] = {}
-        self._profiler_instantiated = False
 
         if self._export_to_chrome and self._path_to_export_trace is None:
             rank_zero_warn(
@@ -246,13 +243,12 @@ def setup(
             self._path_to_export_trace = log_dir
 
     def start(self, action_name: str) -> None:
-        if not self._profiler_instantiated and action_name in (
-            list(self.START_RECORD_FUNCTIONS) + list(self._record_functions)
-        ):
+        if self.profiler is None and action_name in self._record_functions:
 
-            # close profiler if it is already opened
+            # close profiler if it is already opened. might happen if 2 profilers
+            # are created and the first one did not call `describe`
             try:
-                torch.autograd._disable_profiler()
+                torch.autograd._disable_profiler()  # noqa
             except (AttributeError, RuntimeError):
                 pass
 
@@ -261,15 +257,11 @@ def start(self, action_name: str) -> None:
             self.profiler.__enter__()
             if self._parent_profiler is not None:
                 self._parent_profiler.__enter__()
-
-            self._profiler_instantiated = True
-
-            if self._record_module_names and self._lightning_module is not None:
-                self._register = RegisterRecordFunction(self._lightning_module)
+            if self._register is not None:
                 self._register.__enter__()
 
         if (
-            self._profiler_instantiated and action_name in self._record_functions
+            self.profiler is not None and action_name in self._record_functions
             and action_name not in self._recording_map
         ):
             recording = record_function(action_name)
@@ -282,24 +274,11 @@ def stop(self, action_name: str) -> None:
             del self._recording_map[action_name]
 
     def summary(self) -> str:
-        if not self._profiler_kwargs.get("enabled", True):
+        if not self._profiler_kwargs.get("enabled", True) or self._emit_nvtx:
             return ""
 
-        self.profiler.__exit__(None, None, None)
-        if not self._emit_nvtx:
-            self.function_events = self.profiler.function_events
-        self.profiler = None
-        self._profiler_instantiated = False
-
-        if self._parent_profiler is not None:
-            self._parent_profiler.__exit__(None, None, None)
-            self._parent_profiler = None
-
-        if self._register is not None:
-            self._register.__exit__(None, None, None)
-
-        if self._emit_nvtx:
-            return ""
+        self.function_events = self.profiler.function_events
+        self._delete_profilers()
 
         if self._export_to_chrome:
             filename = f"{self.local_rank}_trace.json"
@@ -311,8 +290,7 @@ def summary(self) -> str:
         data = self.function_events.key_averages(group_by_input_shapes=self._group_by_input_shapes)
         table = data.table(sort_by=self._sort_by_key, row_limit=self._row_limit)
 
-        recorded_stats = {}
-        recorded_stats["records"] = table
+        recorded_stats = {"records": table}
         return self._stats_to_str(recorded_stats)
 
     def _create_profilers(self) -> None:
@@ -322,15 +300,18 @@ def _create_profilers(self) -> None:
         else:
             self._parent_profiler = None
             self.profiler = self._create_profiler(torch.autograd.profiler.profile)
+        if self._record_module_names and self._lightning_module is not None:
+            self._register = RegisterRecordFunction(self._lightning_module)
 
     def _create_profiler(self, profiler: Type[_PROFILER]) -> _PROFILER:
         init_parameters = inspect.signature(profiler.__init__).parameters
         kwargs = {k: v for k, v in self._profiler_kwargs.items() if k in init_parameters}
         return profiler(**kwargs)
 
-    def teardown(self, stage: Optional[str] = None) -> None:
+    def _delete_profilers(self) -> None:
         if self.profiler is not None:
             self.profiler.__exit__(None, None, None)
+            self.profiler = None
 
         if self._parent_profiler is not None:
             self._parent_profiler.__exit__(None, None, None)
@@ -338,8 +319,13 @@ def teardown(self, stage: Optional[str] = None) -> None:
 
         if self._register is not None:
             self._register.__exit__(None, None, None)
+            self._register = None
+
+    def teardown(self, stage: Optional[str] = None) -> None:
+        self._delete_profilers()
 
-        for record in self._recording_map.values():
-            record.__exit__(None, None, None)
+        for k in self._recording_map:
+            self.stop(k)
+        self._recording_map = {}
 
         super().teardown()

From f916013a60d7f7b1b238575b6d4dc7bc10acea0a Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Tue, 23 Mar 2021 14:36:28 +0100
Subject: [PATCH 75/87] Missed stage

---
 pytorch_lightning/profiler/pytorch.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index dcf7e4696bd0e..9a34ef41cab5e 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -328,4 +328,4 @@ def teardown(self, stage: Optional[str] = None) -> None:
             self.stop(k)
         self._recording_map = {}
 
-        super().teardown()
+        super().teardown(stage=stage)

From 9a1b1b649d120f91bf21a2070b2cb930bb774712 Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Tue, 23 Mar 2021 14:42:10 +0100
Subject: [PATCH 76/87] Minor changes

---
 tests/test_profiler.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 99f1d74905a5c..60b4c0ece8a66 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -339,7 +339,7 @@ def test_pytorch_profiler_trainer_test(tmpdir, pytorch_profiler):
     )
     trainer.test(model)
 
-    assert len([e for e in pytorch_profiler.function_events if 'test_step' == e.name]) > 0
+    assert sum(e.name == 'test_step' for e in pytorch_profiler.function_events)
 
     path = pytorch_profiler.dirpath / f"test-{pytorch_profiler.filename}.txt"
     assert path.read_text("utf-8")
@@ -357,7 +357,7 @@ def test_pytorch_profiler_trainer_predict(tmpdir, pytorch_profiler):
     )
     trainer.predict(model)
 
-    assert len([e for e in pytorch_profiler.function_events if 'predict' == e.name]) > 0
+    assert sum(e.name == 'predict_step' for e in pytorch_profiler.function_events)
 
     path = pytorch_profiler.dirpath / f"predict-{pytorch_profiler.filename}.txt"
     assert path.read_text("utf-8")
@@ -374,7 +374,7 @@ def test_pytorch_profiler_trainer_validate(tmpdir, pytorch_profiler):
     )
     trainer.validate(model)
 
-    assert len([e for e in pytorch_profiler.function_events if 'validation_step' == e.name]) > 0
+    assert sum(e.name == 'validation_step' for e in pytorch_profiler.function_events)
 
     path = pytorch_profiler.dirpath / f"validate-{pytorch_profiler.filename}.txt"
     assert path.read_text("utf-8")

From 04abd0a716f6c34694d7fc71ee1a295a90bf8b41 Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Tue, 23 Mar 2021 13:52:25 +0000
Subject: [PATCH 77/87] resolve tests

---
 pytorch_lightning/profiler/pytorch.py | 8 ++++++--
 1 file changed, 6 insertions(+), 2 deletions(-)

diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index dcf7e4696bd0e..1ea030cd2998e 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -187,6 +187,7 @@ def __init__(
         self._path_to_export_trace = path_to_export_trace
         self._row_limit = row_limit
         self._sort_by_key = sort_by_key or f"{'cuda' if profiler_kwargs.get('use_cuda', False) else 'cpu'}_time_total"
+        self._record_functions_start = set(record_functions + list(self.START_RECORD_FUNCTIONS))
         self._record_functions = set(record_functions + list(self.RECORD_FUNCTIONS))
         self._record_module_names = record_module_names
         self._profiler_kwargs = profiler_kwargs
@@ -243,7 +244,7 @@ def setup(
             self._path_to_export_trace = log_dir
 
     def start(self, action_name: str) -> None:
-        if self.profiler is None and action_name in self._record_functions:
+        if self.profiler is None and action_name in self._record_functions_start:
 
             # close profiler if it is already opened. might happen if 2 profilers
             # are created and the first one did not call `describe`
@@ -277,7 +278,6 @@ def summary(self) -> str:
         if not self._profiler_kwargs.get("enabled", True) or self._emit_nvtx:
             return ""
 
-        self.function_events = self.profiler.function_events
         self._delete_profilers()
 
         if self._export_to_chrome:
@@ -308,9 +308,13 @@ def _create_profiler(self, profiler: Type[_PROFILER]) -> _PROFILER:
         kwargs = {k: v for k, v in self._profiler_kwargs.items() if k in init_parameters}
         return profiler(**kwargs)
 
+    def _cache_functions_events(self):
+        self.function_events = self.profiler.function_events
+
     def _delete_profilers(self) -> None:
         if self.profiler is not None:
             self.profiler.__exit__(None, None, None)
+            self._cache_functions_events()
             self.profiler = None
 
         if self._parent_profiler is not None:

From 0230330d2ed551ccfbe7d133347c21fd7b332926 Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Tue, 23 Mar 2021 14:59:39 +0100
Subject: [PATCH 78/87] Update CHANGELOG

---
 CHANGELOG.md | 9 +++++++++
 1 file changed, 9 insertions(+)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 32cf9122efe34..2dc0ba3e227e9 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -54,6 +54,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Added `AbstractProfiler` interface ([#6621](https://github.com/PyTorchLightning/pytorch-lightning/pull/6621))
 
 
+- Added support for including module names for forward in the autograd trace of `PyTorchProfiler` ([#6349](https://github.com/PyTorchLightning/pytorch-lightning/pull/6349))
+
+
 - Added `outputs` parameter to callback's `on_validation_epoch_end` & `on_test_epoch_end` hooks ([#6120](https://github.com/PyTorchLightning/pytorch-lightning/pull/6120))
 
 
@@ -74,6 +77,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Changed profilers to save separate report files per state and rank ([#6621](https://github.com/PyTorchLightning/pytorch-lightning/pull/6621))
 
 
+- Changed `PyTorchProfiler` to use `torch.autograd.profiler.record_function` to record functions ([#6349](https://github.com/PyTorchLightning/pytorch-lightning/pull/6349))
+
+
 ### Deprecated
 
 - `period` has been deprecated in favor of `every_n_val_epochs` in the `ModelCheckpoint` callback ([#6146](https://github.com/PyTorchLightning/pytorch-lightning/pull/6146))
@@ -85,6 +91,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Deprecated `Profiler(output_filename)` in favor of `dirpath` and `filename` ([#6621](https://github.com/PyTorchLightning/pytorch-lightning/pull/6621))
 
 
+- Deprecated `PytorchProfiler(profiled_functions)` in favor of `record_functions` ([#6349](https://github.com/PyTorchLightning/pytorch-lightning/pull/6349))
+
+
 - Deprecated metrics in favor of `torchmetrics` ([#6505](https://github.com/PyTorchLightning/pytorch-lightning/pull/6505),
 
     [#6530](https://github.com/PyTorchLightning/pytorch-lightning/pull/6530),

From cba643b514e076377d918c67e1a1dbb3beeb4090 Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Tue, 23 Mar 2021 14:04:26 +0000
Subject: [PATCH 79/87] resolve bug

---
 pytorch_lightning/profiler/profilers.py | 1 +
 pytorch_lightning/profiler/pytorch.py   | 8 ++++++--
 tests/test_profiler.py                  | 5 +++--
 3 files changed, 10 insertions(+), 4 deletions(-)

diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index 46d72583fb466..53577b8e46fa5 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -99,6 +99,7 @@ def profile(self, action_name: str) -> None:
         stop once you exit the code block.
         """
         try:
+            print(action_name)
             self.start(action_name)
             yield action_name
         finally:
diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index 3da7eb5763b10..219238593c9b2 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -109,7 +109,7 @@ class PyTorchProfiler(BaseProfiler):
         "self_cuda_memory_usage",
         "count",
     )
-    START_RECORD_FUNCTIONS = ('on_train_start', 'on_validation_step', 'on_test_start', 'on_predict_start')
+    START_RECORD_FUNCTIONS = ('on_train_start', 'on_validation_start', 'on_test_start', 'on_predict_start')
 
     def __init__(
         self,
@@ -285,7 +285,11 @@ def summary(self) -> str:
             path_to_trace = (
                 filename if self._path_to_export_trace is None else os.path.join(self._path_to_export_trace, filename)
             )
-            self.function_events.export_chrome_trace(path_to_trace)
+            if self.function_events is not None and len(self.function_events) > 0:
+                self.function_events.export_chrome_trace(path_to_trace)
+
+        if self.function_events is None or len(self.function_events) > 0:
+            return ""
 
         data = self.function_events.key_averages(group_by_input_shapes=self._group_by_input_shapes)
         table = data.table(sort_by=self._sort_by_key, row_limit=self._row_limit)
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 60b4c0ece8a66..3afa641aeca79 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -268,7 +268,7 @@ def pytorch_profiler(tmpdir):
 
 def test_pytorch_profiler_describe(pytorch_profiler):
     """Ensure the profiler won't fail when reporting the summary."""
-    with pytorch_profiler.profile("test_step"):
+    with pytorch_profiler.profile("on_test_start"):
         pass
 
     # log to stdout and print to file
@@ -366,10 +366,11 @@ def test_pytorch_profiler_trainer_predict(tmpdir, pytorch_profiler):
 def test_pytorch_profiler_trainer_validate(tmpdir, pytorch_profiler):
     """Ensure that the profiler can be given to the trainer and validate function are properly recorded. """
     model = BoringModel()
+    model.val_dataloader = model.train_dataloader
     trainer = Trainer(
         default_root_dir=tmpdir,
         max_epochs=1,
-        limit_test_batches=2,
+        limit_val_batches=2,
         profiler=pytorch_profiler,
     )
     trainer.validate(model)

From af209f55e4ad2577b4c3bd960cd35d263035bdd8 Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Tue, 23 Mar 2021 14:05:34 +0000
Subject: [PATCH 80/87] remove print

---
 pytorch_lightning/profiler/profilers.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/pytorch_lightning/profiler/profilers.py b/pytorch_lightning/profiler/profilers.py
index 53577b8e46fa5..46d72583fb466 100644
--- a/pytorch_lightning/profiler/profilers.py
+++ b/pytorch_lightning/profiler/profilers.py
@@ -99,7 +99,6 @@ def profile(self, action_name: str) -> None:
         stop once you exit the code block.
         """
         try:
-            print(action_name)
             self.start(action_name)
             yield action_name
         finally:

From bb813bbd8398fedf172b5fe77fb5efbc344f7b10 Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Tue, 23 Mar 2021 15:05:48 +0100
Subject: [PATCH 81/87] Typo

---
 tests/test_profiler.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 3afa641aeca79..1594f080a747f 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -357,7 +357,7 @@ def test_pytorch_profiler_trainer_predict(tmpdir, pytorch_profiler):
     )
     trainer.predict(model)
 
-    assert sum(e.name == 'predict_step' for e in pytorch_profiler.function_events)
+    assert sum(e.name == 'predict' for e in pytorch_profiler.function_events)
 
     path = pytorch_profiler.dirpath / f"predict-{pytorch_profiler.filename}.txt"
     assert path.read_text("utf-8")

From 624a85f6045463eac42d53d4138586d81a7f4839 Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Tue, 23 Mar 2021 15:11:32 +0100
Subject: [PATCH 82/87] Cleanup

---
 pytorch_lightning/profiler/pytorch.py | 9 ++++-----
 tests/test_profiler.py                | 3 +--
 2 files changed, 5 insertions(+), 7 deletions(-)

diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index 219238593c9b2..39b740c538829 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -280,16 +280,15 @@ def summary(self) -> str:
 
         self._delete_profilers()
 
+        if not self.function_events:
+            return ""
+
         if self._export_to_chrome:
             filename = f"{self.local_rank}_trace.json"
             path_to_trace = (
                 filename if self._path_to_export_trace is None else os.path.join(self._path_to_export_trace, filename)
             )
-            if self.function_events is not None and len(self.function_events) > 0:
-                self.function_events.export_chrome_trace(path_to_trace)
-
-        if self.function_events is None or len(self.function_events) > 0:
-            return ""
+            self.function_events.export_chrome_trace(path_to_trace)
 
         data = self.function_events.key_averages(group_by_input_shapes=self._group_by_input_shapes)
         table = data.table(sort_by=self._sort_by_key, row_limit=self._row_limit)
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 1594f080a747f..512797f2c646a 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -269,7 +269,7 @@ def pytorch_profiler(tmpdir):
 def test_pytorch_profiler_describe(pytorch_profiler):
     """Ensure the profiler won't fail when reporting the summary."""
     with pytorch_profiler.profile("on_test_start"):
-        pass
+        torch.tensor(0)
 
     # log to stdout and print to file
     pytorch_profiler.describe()
@@ -366,7 +366,6 @@ def test_pytorch_profiler_trainer_predict(tmpdir, pytorch_profiler):
 def test_pytorch_profiler_trainer_validate(tmpdir, pytorch_profiler):
     """Ensure that the profiler can be given to the trainer and validate function are properly recorded. """
     model = BoringModel()
-    model.val_dataloader = model.train_dataloader
     trainer = Trainer(
         default_root_dir=tmpdir,
         max_epochs=1,

From 1732ece5e095f7e7cc6cf3168f91f1dba0823512 Mon Sep 17 00:00:00 2001
From: thomas chaton <thomas@grid.ai>
Date: Tue, 23 Mar 2021 14:24:54 +0000
Subject: [PATCH 83/87] resolve ddp test

---
 tests/test_profiler.py | 6 ++----
 1 file changed, 2 insertions(+), 4 deletions(-)

diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 512797f2c646a..ef12f70ceafba 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -316,12 +316,10 @@ def test_pytorch_profiler_trainer_ddp(tmpdir, pytorch_profiler):
     for name in expected:
         assert sum(e.name == name for e in pytorch_profiler.function_events)
 
-    assert len(pytorch_profiler.summary()) > 0
-    assert set(pytorch_profiler.profiled_actions) == {'training_step_and_backward', 'validation_step'}
+    trainer.accelerator.barrier()
 
     files = set(os.listdir(pytorch_profiler.dirpath))
-    rank = int(os.getenv("LOCAL_RANK", 0))
-    expected = f"fit-profiler-{rank}.txt"
+    expected = f"fit-profiler-{trainer.local_rank}.txt"
     assert expected in files
 
     path = os.path.join(pytorch_profiler.dirpath, expected)

From f0c167508da50f918f4447010d1ca274b2c98d65 Mon Sep 17 00:00:00 2001
From: thomas chaton <thomas@grid.ai>
Date: Tue, 23 Mar 2021 14:27:32 +0000
Subject: [PATCH 84/87] remove barrier

---
 tests/test_profiler.py | 2 --
 1 file changed, 2 deletions(-)

diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index ef12f70ceafba..8cf6d96e7a328 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -316,8 +316,6 @@ def test_pytorch_profiler_trainer_ddp(tmpdir, pytorch_profiler):
     for name in expected:
         assert sum(e.name == name for e in pytorch_profiler.function_events)
 
-    trainer.accelerator.barrier()
-
     files = set(os.listdir(pytorch_profiler.dirpath))
     expected = f"fit-profiler-{trainer.local_rank}.txt"
     assert expected in files

From 374f0da4bbd09b2c4bfba5e5b8ef88ab67c19544 Mon Sep 17 00:00:00 2001
From: tchaton <thomas@grid.ai>
Date: Tue, 23 Mar 2021 15:17:18 +0000
Subject: [PATCH 85/87] update

---
 pytorch_lightning/profiler/pytorch.py | 2 +-
 tests/test_profiler.py                | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index 39b740c538829..3a1ead8ee771b 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -96,7 +96,7 @@ def __exit__(self, exc_type: Any, exc_value: Any, traceback: Any) -> None:
 class PyTorchProfiler(BaseProfiler):
 
     RECORD_FUNCTIONS = (
-        "training_step_and_backward", "training_step", "backward", "validation_step", "test_step", "predict"
+        "training_step_and_backward", "training_step", "backward", "validation_step", "test_step", "predict_step"
     )
     AVAILABLE_SORT_KEYS = (
         "cpu_time",
diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 8cf6d96e7a328..5114d02cfd816 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -353,7 +353,7 @@ def test_pytorch_profiler_trainer_predict(tmpdir, pytorch_profiler):
     )
     trainer.predict(model)
 
-    assert sum(e.name == 'predict' for e in pytorch_profiler.function_events)
+    assert sum(e.name == 'predict_step' for e in pytorch_profiler.function_events)
 
     path = pytorch_profiler.dirpath / f"predict-{pytorch_profiler.filename}.txt"
     assert path.read_text("utf-8")

From 6e948ca2d13e8904a5e11de75a9ce5c9d9170a05 Mon Sep 17 00:00:00 2001
From: Carlos Mocholi <carlossmocholi@gmail.com>
Date: Tue, 23 Mar 2021 16:47:47 +0100
Subject: [PATCH 86/87] Smaller model

---
 tests/test_profiler.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/tests/test_profiler.py b/tests/test_profiler.py
index 5114d02cfd816..5d144aef36573 100644
--- a/tests/test_profiler.py
+++ b/tests/test_profiler.py
@@ -437,22 +437,22 @@ def test_pytorch_profiler_nested_emit_nvtx(tmpdir):
 def test_register_record_function(tmpdir):
 
     use_cuda = torch.cuda.is_available()
-
     pytorch_profiler = PyTorchProfiler(
         export_to_chrome=False,
         record_functions=["a"],
         use_cuda=use_cuda,
-        output_filename=os.path.join(tmpdir, "profiler.txt")
+        dirpath=tmpdir,
+        filename="profiler",
     )
 
     class TestModel(BoringModel):
 
         def __init__(self):
             super().__init__()
-            self.layer = torch.nn.Sequential(torch.nn.Linear(32, 32), torch.nn.ReLU(), torch.nn.Linear(32, 2))
+            self.layer = torch.nn.Sequential(torch.nn.Linear(8, 8), torch.nn.ReLU(), torch.nn.Linear(8, 2))
 
     model = TestModel()
-    input = torch.rand((1, 32))
+    input = torch.rand((1, 8))
 
     if use_cuda:
         model = model.cuda()

From e0d8623ca50bee8c03c2412005e86034d424ef1a Mon Sep 17 00:00:00 2001
From: thomas chaton <thomas@grid.ai>
Date: Tue, 23 Mar 2021 16:47:12 +0000
Subject: [PATCH 87/87] add check for emit_nvtx

---
 pytorch_lightning/profiler/pytorch.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/pytorch_lightning/profiler/pytorch.py b/pytorch_lightning/profiler/pytorch.py
index 3a1ead8ee771b..974883a4724c6 100644
--- a/pytorch_lightning/profiler/pytorch.py
+++ b/pytorch_lightning/profiler/pytorch.py
@@ -312,7 +312,8 @@ def _create_profiler(self, profiler: Type[_PROFILER]) -> _PROFILER:
         return profiler(**kwargs)
 
     def _cache_functions_events(self):
-        self.function_events = self.profiler.function_events
+        if not self._emit_nvtx:
+            self.function_events = self.profiler.function_events
 
     def _delete_profilers(self) -> None:
         if self.profiler is not None: