From 401c07f861b4f4145489ee5fa51c56dd7e546172 Mon Sep 17 00:00:00 2001
From: rohitgr7 <rohitgr1998@gmail.com>
Date: Thu, 12 Nov 2020 01:23:47 +0530
Subject: [PATCH 01/11] fast_dev_run can be int

---
 .../trainer/connectors/debugging_connector.py | 21 ++++++--
 pytorch_lightning/trainer/properties.py       |  2 +-
 pytorch_lightning/trainer/trainer.py          |  4 +-
 pytorch_lightning/tuner/batch_size_scaling.py |  2 +-
 pytorch_lightning/tuner/lr_finder.py          |  2 +-
 tests/trainer/test_dataloaders.py             | 49 ++++++++++++-------
 6 files changed, 53 insertions(+), 27 deletions(-)

diff --git a/pytorch_lightning/trainer/connectors/debugging_connector.py b/pytorch_lightning/trainer/connectors/debugging_connector.py
index 580d13a6df9fd..0f5e00ad58899 100644
--- a/pytorch_lightning/trainer/connectors/debugging_connector.py
+++ b/pytorch_lightning/trainer/connectors/debugging_connector.py
@@ -32,15 +32,26 @@ def on_init_start(
             fast_dev_run
     ):
 
+        if isinstance(fast_dev_run, int) and fast_dev_run < 0:
+            raise MisconfigurationException(
+                f'fast_dev_run={fast_dev_run} is not a'
+                ' valid configuration. It should be >= 0.'
+            )
+
         self.trainer.fast_dev_run = fast_dev_run
-        if self.trainer.fast_dev_run:
-            limit_train_batches = 1
-            limit_val_batches = 1
-            limit_test_batches = 1
+
+        if fast_dev_run is True:
+            fast_dev_run = 1
+
+        if fast_dev_run:
+            limit_train_batches = fast_dev_run
+            limit_val_batches = fast_dev_run
+            limit_test_batches = fast_dev_run
             self.trainer.num_sanity_val_steps = 0
             self.trainer.max_epochs = 1
             rank_zero_info(
-                'Running in fast_dev_run mode: will run a full train,' ' val and test loop using a single batch'
+                'Running in fast_dev_run mode: will run a full train,'
+                f' val and test loop using {fast_dev_run} batch(es)'
             )
 
         self.trainer.limit_train_batches = _determine_batch_limits(limit_train_batches, 'limit_train_batches')
diff --git a/pytorch_lightning/trainer/properties.py b/pytorch_lightning/trainer/properties.py
index af06b1bbc1352..c7aa616adfb64 100644
--- a/pytorch_lightning/trainer/properties.py
+++ b/pytorch_lightning/trainer/properties.py
@@ -37,7 +37,7 @@ class TrainerProperties(ABC):
     logger_connector: LoggerConnector
     _state: TrainerState
     global_rank: int
-    fast_dev_run: bool
+    fast_dev_run: Union[int, bool]
     use_dp: bool
     use_ddp: bool
     use_ddp2: bool
diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index 46e4abbe584ae..c3efca5dc3825 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -104,7 +104,7 @@ def __init__(
         overfit_batches: Union[int, float] = 0.0,
         track_grad_norm: Union[int, float, str] = -1,
         check_val_every_n_epoch: int = 1,
-        fast_dev_run: bool = False,
+        fast_dev_run: Union[int, bool] = False,
         accumulate_grad_batches: Union[int, Dict[int, int], List[list]] = 1,
         max_epochs: int = 1000,
         min_epochs: int = 1,
@@ -191,7 +191,7 @@ def __init__(
 
             distributed_backend: deprecated. Please use 'accelerator'
 
-            fast_dev_run: runs 1 batch of train, test and val to find any bugs (ie: a sort of unit test).
+            fast_dev_run: runs n if set to n(int) else 1 batch(es) of train, test and val to find any bugs (ie: a sort of unit test).
 
             flush_logs_every_n_steps: How often to flush logs to disk (defaults to every 100 steps).
 
diff --git a/pytorch_lightning/tuner/batch_size_scaling.py b/pytorch_lightning/tuner/batch_size_scaling.py
index 67a4704b628fc..936efded09bd5 100644
--- a/pytorch_lightning/tuner/batch_size_scaling.py
+++ b/pytorch_lightning/tuner/batch_size_scaling.py
@@ -70,7 +70,7 @@ def scale_batch_size(trainer,
             or datamodule.
     """
     if trainer.fast_dev_run:
-        rank_zero_warn('Skipping batch size scaler since `fast_dev_run=True`', UserWarning)
+        rank_zero_warn(f'Skipping batch size scaler since `fast_dev_run={trainer.fast_dev_run}`', UserWarning)
         return
 
     if not lightning_hasattr(model, batch_arg_name):
diff --git a/pytorch_lightning/tuner/lr_finder.py b/pytorch_lightning/tuner/lr_finder.py
index b6d8c8178093b..79335c7bce774 100644
--- a/pytorch_lightning/tuner/lr_finder.py
+++ b/pytorch_lightning/tuner/lr_finder.py
@@ -137,7 +137,7 @@ def lr_find(
 
     """
     if trainer.fast_dev_run:
-        rank_zero_warn('Skipping learning rate finder since `fast_dev_run=True`', UserWarning)
+        rank_zero_warn(f'Skipping learning rate finder since `fast_dev_run={trainer.fast_dev_run}`', UserWarning)
         return
 
     save_path = os.path.join(trainer.default_root_dir, 'lr_find_temp_model.ckpt')
diff --git a/tests/trainer/test_dataloaders.py b/tests/trainer/test_dataloaders.py
index 1ca34101a9141..4f0ff84214a16 100644
--- a/tests/trainer/test_dataloaders.py
+++ b/tests/trainer/test_dataloaders.py
@@ -434,9 +434,11 @@ def test_dataloaders_with_limit_num_batches(tmpdir, limit_train_batches, limit_v
 
 
 @mock.patch.dict(os.environ, {"PL_DEV_DEBUG": "1"})
-def test_dataloaders_with_fast_dev_run(tmpdir):
-    """Verify num_batches for train, val & test dataloaders passed with fast_dev_run = True"""
-
+@pytest.mark.parametrize('fast_dev_run', [True, 3, -1])
+def test_dataloaders_with_fast_dev_run(tmpdir, fast_dev_run):
+    """
+    Verify num_batches for train, val & test dataloaders passed with fast_dev_run
+    """
     model = EvalModelTemplate()
     model.val_dataloader = model.val_dataloader__multiple_mixed_length
     model.test_dataloader = model.test_dataloader__multiple_mixed_length
@@ -445,26 +447,39 @@ def test_dataloaders_with_fast_dev_run(tmpdir):
     model.test_step = model.test_step__multiple_dataloaders
     model.test_epoch_end = model.test_epoch_end__multiple_dataloaders
 
-    # train, multiple val and multiple test dataloaders passed with fast_dev_run = True
-    trainer = Trainer(
+    trainer_options = dict(
         default_root_dir=tmpdir,
         max_epochs=2,
-        fast_dev_run=True,
+        fast_dev_run=fast_dev_run,
     )
-    assert trainer.max_epochs == 1
-    assert trainer.num_sanity_val_steps == 0
 
-    trainer.fit(model)
-    assert not trainer.disable_validation
-    assert trainer.num_training_batches == 1
-    assert trainer.num_val_batches == [1] * len(trainer.val_dataloaders)
+    if fast_dev_run == -1:
+        with pytest.raises(MisconfigurationException, match='should be >= 0'):
+            trainer = Trainer(**trainer_options)
+            return
+    else:
+        trainer = Trainer(**trainer_options)
 
-    trainer.test(ckpt_path=None)
-    assert trainer.num_test_batches == [1] * len(trainer.test_dataloaders)
+        if fast_dev_run is True:
+            fast_dev_run = 1
 
-    # verify sanity check batches match as expected
-    num_val_dataloaders = len(model.val_dataloader())
-    assert trainer.dev_debugger.num_seen_sanity_check_batches == trainer.num_sanity_val_steps * num_val_dataloaders
+        assert trainer.limit_train_batches == fast_dev_run
+        assert trainer.limit_val_batches == fast_dev_run
+        assert trainer.limit_test_batches == fast_dev_run
+        assert trainer.num_sanity_val_steps == 0
+        assert trainer.max_epochs == 1
+
+        trainer.fit(model)
+        assert not trainer.disable_validation
+        assert trainer.num_training_batches == fast_dev_run
+        assert trainer.num_val_batches == [fast_dev_run] * len(trainer.val_dataloaders)
+
+        trainer.test(ckpt_path=None)
+        assert trainer.num_test_batches == [fast_dev_run] * len(trainer.test_dataloaders)
+
+        # verify sanity check batches match as expected
+        num_val_dataloaders = len(model.val_dataloader())
+        assert trainer.dev_debugger.num_seen_sanity_check_batches == trainer.num_sanity_val_steps * num_val_dataloaders
 
 
 @pytest.mark.parametrize('ckpt_path', [None, 'best', 'specific'])

From b9ecf4410abe0992554ece428600d14c6df45897 Mon Sep 17 00:00:00 2001
From: rohitgr7 <rohitgr1998@gmail.com>
Date: Thu, 12 Nov 2020 01:27:11 +0530
Subject: [PATCH 02/11] pep

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

diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index c3efca5dc3825..ee77b2c0fe85e 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -191,7 +191,8 @@ def __init__(
 
             distributed_backend: deprecated. Please use 'accelerator'
 
-            fast_dev_run: runs n if set to n(int) else 1 batch(es) of train, test and val to find any bugs (ie: a sort of unit test).
+            fast_dev_run: runs n if set to n(int) else 1 batch(es) of train, val
+                and test to find any bugs (ie: a sort of unit test).
 
             flush_logs_every_n_steps: How often to flush logs to disk (defaults to every 100 steps).
 

From 638f8b4e5967101040768d9a959e295cf1d0bd78 Mon Sep 17 00:00:00 2001
From: rohitgr7 <rohitgr1998@gmail.com>
Date: Thu, 12 Nov 2020 01:30:34 +0530
Subject: [PATCH 03/11] chlog

---
 CHANGELOG.md | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 797569f71128b..f111401327aac 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -39,6 +39,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Added ability for DDP plugin to modify optimizer state saving ([#4675](https://github.com/PyTorchLightning/pytorch-lightning/pull/4675))
 
 
+- Updated `fast_dev_run` to accept integer representing num_batches ([#4629](https://github.com/PyTorchLightning/pytorch-lightning/pull/4629))
+
+
 ### Changed
 
 - Tuner algorithms will be skipped if `fast_dev_run=True` ([#3903](https://github.com/PyTorchLightning/pytorch-lightning/pull/3903))
@@ -63,6 +66,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Added lambda closure to `manual_optimizer_step` ([#4618](https://github.com/PyTorchLightning/pytorch-lightning/pull/4618))
 
+
 ### Changed
 
 - Change Metrics `persistent` default mode to `False` ([#4685](https://github.com/PyTorchLightning/pytorch-lightning/pull/4685))

From 2a36cefa02dd53bef84176d04d8b8fe48e573ecc Mon Sep 17 00:00:00 2001
From: rohitgr7 <rohitgr1998@gmail.com>
Date: Fri, 13 Nov 2020 00:07:57 +0530
Subject: [PATCH 04/11] add check and update docs

---
 .../trainer/connectors/debugging_connector.py             | 7 ++++++-
 pytorch_lightning/trainer/trainer.py                      | 4 ++--
 tests/trainer/test_dataloaders.py                         | 8 +++++---
 3 files changed, 13 insertions(+), 6 deletions(-)

diff --git a/pytorch_lightning/trainer/connectors/debugging_connector.py b/pytorch_lightning/trainer/connectors/debugging_connector.py
index 0f5e00ad58899..1ea4f733a2a2f 100644
--- a/pytorch_lightning/trainer/connectors/debugging_connector.py
+++ b/pytorch_lightning/trainer/connectors/debugging_connector.py
@@ -31,8 +31,13 @@ def on_init_start(
             overfit_batches,
             fast_dev_run
     ):
+        if not isinstance(fast_dev_run, (bool, int)):
+            raise MisconfigurationException(
+                f'fast_dev_run={fast_dev_run} is not a valid configuration.'
+                ' It should be either a bool or an int >= 0'
+            )
 
-        if isinstance(fast_dev_run, int) and fast_dev_run < 0:
+        if isinstance(fast_dev_run, int) and (fast_dev_run < 0):
             raise MisconfigurationException(
                 f'fast_dev_run={fast_dev_run} is not a'
                 ' valid configuration. It should be >= 0.'
diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index ee77b2c0fe85e..028494e37edf2 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -191,8 +191,8 @@ def __init__(
 
             distributed_backend: deprecated. Please use 'accelerator'
 
-            fast_dev_run: runs n if set to n(int) else 1 batch(es) of train, val
-                and test to find any bugs (ie: a sort of unit test).
+            fast_dev_run: runs n if set to n(int) else 1 if set to ``True`` batch(es)
+                of train, val and test to find any bugs (ie: a sort of unit test).
 
             flush_logs_every_n_steps: How often to flush logs to disk (defaults to every 100 steps).
 
diff --git a/tests/trainer/test_dataloaders.py b/tests/trainer/test_dataloaders.py
index 4f0ff84214a16..844dc31f745b6 100644
--- a/tests/trainer/test_dataloaders.py
+++ b/tests/trainer/test_dataloaders.py
@@ -434,7 +434,7 @@ def test_dataloaders_with_limit_num_batches(tmpdir, limit_train_batches, limit_v
 
 
 @mock.patch.dict(os.environ, {"PL_DEV_DEBUG": "1"})
-@pytest.mark.parametrize('fast_dev_run', [True, 3, -1])
+@pytest.mark.parametrize('fast_dev_run', [True, 3, -1, 'temp'])
 def test_dataloaders_with_fast_dev_run(tmpdir, fast_dev_run):
     """
     Verify num_batches for train, val & test dataloaders passed with fast_dev_run
@@ -453,10 +453,12 @@ def test_dataloaders_with_fast_dev_run(tmpdir, fast_dev_run):
         fast_dev_run=fast_dev_run,
     )
 
-    if fast_dev_run == -1:
+    if fast_dev_run == 'temp':
+        with pytest.raises(MisconfigurationException, match='either a bool or an int'):
+            trainer = Trainer(**trainer_options)
+    elif fast_dev_run == -1:
         with pytest.raises(MisconfigurationException, match='should be >= 0'):
             trainer = Trainer(**trainer_options)
-            return
     else:
         trainer = Trainer(**trainer_options)
 

From df664377672acea3ec6b1f23ce46cee009c06608 Mon Sep 17 00:00:00 2001
From: rohitgr7 <rohitgr1998@gmail.com>
Date: Mon, 16 Nov 2020 01:10:38 +0530
Subject: [PATCH 05/11] logging with fdr

---
 pytorch_lightning/trainer/connectors/debugging_connector.py   | 4 +---
 .../trainer/connectors/logger_connector/logger_connector.py   | 2 +-
 2 files changed, 2 insertions(+), 4 deletions(-)

diff --git a/pytorch_lightning/trainer/connectors/debugging_connector.py b/pytorch_lightning/trainer/connectors/debugging_connector.py
index 1ea4f733a2a2f..b8703d28e9ba7 100644
--- a/pytorch_lightning/trainer/connectors/debugging_connector.py
+++ b/pytorch_lightning/trainer/connectors/debugging_connector.py
@@ -44,9 +44,7 @@ def on_init_start(
             )
 
         self.trainer.fast_dev_run = fast_dev_run
-
-        if fast_dev_run is True:
-            fast_dev_run = 1
+        fast_dev_run = int(fast_dev_run)
 
         if fast_dev_run:
             limit_train_batches = fast_dev_run
diff --git a/pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py b/pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py
index 9386d428b1f07..bcc1122451ceb 100644
--- a/pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py
+++ b/pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py
@@ -614,7 +614,7 @@ def __gather_result_across_time_and_optimizers(self, epoch_output):
 
     def log_train_step_metrics(self, batch_output):
         # when metrics should be logged
-        if self.should_update_logs or self.trainer.fast_dev_run:
+        if self.should_update_logs or (int(self.trainer.fast_dev_run) == 1):
             # logs user requested information to logger
             metrics = self.cached_results.get_latest_batch_log_metrics()
             grad_norm_dic = batch_output.grad_norm_dic

From 4271d2f6be952c3d12ab711b0c0250615e6eb50f Mon Sep 17 00:00:00 2001
From: rohitgr7 <rohitgr1998@gmail.com>
Date: Mon, 16 Nov 2020 03:08:36 +0530
Subject: [PATCH 06/11] update docs

---
 docs/source/debugging.rst            | 11 +++++++----
 docs/source/trainer.rst              | 28 +++++++++++++++-------------
 pytorch_lightning/trainer/trainer.py |  2 +-
 3 files changed, 23 insertions(+), 18 deletions(-)

diff --git a/docs/source/debugging.rst b/docs/source/debugging.rst
index 845f86a52b231..01de6de613a68 100644
--- a/docs/source/debugging.rst
+++ b/docs/source/debugging.rst
@@ -21,17 +21,20 @@ The following are flags that make debugging much easier.
 
 fast_dev_run
 ------------
-This flag runs a "unit test" by running 1 training batch and 1 validation batch.
-The point is to detect any bugs in the training/validation loop without having to wait for
-a full epoch to crash.
+This flag runs a "unit test" by running n if set to ``n`` (int) else 1 if set to ``True`` training and validation batch(es).
+The point is to detect any bugs in the training/validation loop without having to wait for a full epoch to crash.
 
 (See: :paramref:`~pytorch_lightning.trainer.trainer.Trainer.fast_dev_run`
 argument of :class:`~pytorch_lightning.trainer.trainer.Trainer`)
 
 .. testcode::
-
+    
+    # runs 1 train, val, test batch and program ends
     trainer = Trainer(fast_dev_run=True)
 
+    # runs 7 train, val, test batches and program ends
+    trainer = Trainer(fast_dev_run=7)
+
 ----------------
 
 Inspect gradient norms
diff --git a/docs/source/trainer.rst b/docs/source/trainer.rst
index 0f9fc1fd42572..f6859d2b3d2e5 100644
--- a/docs/source/trainer.rst
+++ b/docs/source/trainer.rst
@@ -245,7 +245,7 @@ Example::
     # ddp2 = DistributedDataParallel + dp
     trainer = Trainer(gpus=2, num_nodes=2, accelerator='ddp2')
 
-.. note:: this option does not apply to TPU. TPUs use ```ddp``` by default (over each core)
+.. note:: This option does not apply to TPU. TPUs use ```ddp``` by default (over each core)
 
 You can also modify hardware behavior by subclassing an existing accelerator to adjust for your needs.
 
@@ -623,17 +623,10 @@ fast_dev_run
 
 |
 
-.. raw:: html
-
-    <video width="50%" max-width="400px" controls
-    poster="https://pl-bolts-doc-images.s3.us-east-2.amazonaws.com/pl_docs/trainer_flags/thumb/fast_dev_run.jpg"
-    src="https://pl-bolts-doc-images.s3.us-east-2.amazonaws.com/pl_docs/trainer_flags/fast_dev_run.mp4"></video>
-
-|
+Runs n if set to ``n`` (int) else 1 if set to ``True`` batch(es) of train, val and test
+to find any bugs (ie: a sort of unit test).
 
-Runs 1 batch of train, test  and val to find any bugs (ie: a sort of unit test).
-
-Under the hood the pseudocode looks like this:
+Under the hood the pseudocode looks like this when running *fast_dev_run* with a single batch:
 
 .. code-block:: python
 
@@ -658,6 +651,16 @@ Under the hood the pseudocode looks like this:
     # runs 1 train, val, test batch and program ends
     trainer = Trainer(fast_dev_run=True)
 
+    # runs 7 train, val, test batches and program ends
+    trainer = Trainer(fast_dev_run=7)
+
+.. note::
+
+    This argument is a bit different from ``limit_train/val/test_batches``. Setting this argument will
+    disable tuner, logger callbacks like ``LearningRateLogger`` and runs for only 1 epoch. This must be
+    used only for debugging purpose. ``limit_train/val/test_batches`` serves their own purpose and won't
+    disable anything.
+
 gpus
 ^^^^
 
@@ -1199,8 +1202,7 @@ Orders the progress bar. Useful when running multiple trainers on the same node.
     # default used by the Trainer
     trainer = Trainer(process_position=0)
 
-Note:
-    This argument is ignored if a custom callback is passed to :paramref:`~Trainer.callbacks`.
+.. note:: This argument is ignored if a custom callback is passed to :paramref:`~Trainer.callbacks`.
 
 profiler
 ^^^^^^^^
diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index 028494e37edf2..d124e39352798 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -191,7 +191,7 @@ def __init__(
 
             distributed_backend: deprecated. Please use 'accelerator'
 
-            fast_dev_run: runs n if set to n(int) else 1 if set to ``True`` batch(es)
+            fast_dev_run: runs n if set to ``n`` (int) else 1 if set to ``True`` batch(es)
                 of train, val and test to find any bugs (ie: a sort of unit test).
 
             flush_logs_every_n_steps: How often to flush logs to disk (defaults to every 100 steps).

From 938fe0863a8460825cc0b32c6fa1f6f0eee3778d Mon Sep 17 00:00:00 2001
From: Rohit Gupta <rohitgr1998@gmail.com>
Date: Tue, 17 Nov 2020 22:55:57 +0530
Subject: [PATCH 07/11] suggestions
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Co-authored-by: Carlos Mocholí <carlossmocholi@gmail.com>
---
 docs/source/trainer.rst | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/docs/source/trainer.rst b/docs/source/trainer.rst
index f6859d2b3d2e5..bfc0e41d2b097 100644
--- a/docs/source/trainer.rst
+++ b/docs/source/trainer.rst
@@ -658,7 +658,7 @@ Under the hood the pseudocode looks like this when running *fast_dev_run* with a
 
     This argument is a bit different from ``limit_train/val/test_batches``. Setting this argument will
     disable tuner, logger callbacks like ``LearningRateLogger`` and runs for only 1 epoch. This must be
-    used only for debugging purpose. ``limit_train/val/test_batches`` serves their own purpose and won't
+    used only for debugging purposes. ``limit_train/val/test_batches`` only limits the number of batches and won't
     disable anything.
 
 gpus
@@ -1704,4 +1704,3 @@ The metrics sent to the progress bar.
 
     progress_bar_metrics = trainer.progress_bar_metrics
     assert progress_bar_metrics['a_val'] == 2
-

From 0ea9a6727ee43f703dda02957c4024fe5dfbf692 Mon Sep 17 00:00:00 2001
From: rohitgr7 <rohitgr1998@gmail.com>
Date: Wed, 18 Nov 2020 00:45:19 +0530
Subject: [PATCH 08/11] fdr flush logs

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

diff --git a/pytorch_lightning/trainer/training_loop.py b/pytorch_lightning/trainer/training_loop.py
index 8af55f64715f2..4c5eafb904972 100644
--- a/pytorch_lightning/trainer/training_loop.py
+++ b/pytorch_lightning/trainer/training_loop.py
@@ -873,7 +873,7 @@ def build_train_args(self, batch, batch_idx, opt_idx, hiddens):
     def save_loggers_on_train_batch_end(self):
         # when loggers should save to disk
         should_flush_logs = self.trainer.logger_connector.should_flush_logs
-        if should_flush_logs or self.trainer.fast_dev_run:
+        if should_flush_logs or (int(self.trainer.fast_dev_run) == 1):
             if self.trainer.is_global_zero and self.trainer.logger is not None:
                 self.trainer.logger.save()
 

From 4951bfd69c48b8c88fe037e02abfbde564bc4f1d Mon Sep 17 00:00:00 2001
From: rohitgr7 <rohitgr1998@gmail.com>
Date: Thu, 19 Nov 2020 01:19:44 +0530
Subject: [PATCH 09/11] update trainer.fast_dev_run

---
 .../trainer/connectors/debugging_connector.py             | 4 ++++
 .../connectors/logger_connector/logger_connector.py       | 2 +-
 pytorch_lightning/trainer/training_loop.py                | 2 +-
 pytorch_lightning/tuner/batch_size_scaling.py             | 2 +-
 pytorch_lightning/tuner/lr_finder.py                      | 2 +-
 tests/trainer/flags/test_fast_dev_run.py                  | 4 ++--
 tests/trainer/test_dataloaders.py                         | 8 +++++++-
 7 files changed, 17 insertions(+), 7 deletions(-)

diff --git a/pytorch_lightning/trainer/connectors/debugging_connector.py b/pytorch_lightning/trainer/connectors/debugging_connector.py
index b8703d28e9ba7..61d7cbd189fde 100644
--- a/pytorch_lightning/trainer/connectors/debugging_connector.py
+++ b/pytorch_lightning/trainer/connectors/debugging_connector.py
@@ -46,6 +46,10 @@ def on_init_start(
         self.trainer.fast_dev_run = fast_dev_run
         fast_dev_run = int(fast_dev_run)
 
+        # set fast_dev_run=True when it is 1, used while logging
+        if fast_dev_run == 1:
+            self.trainer.fast_dev_run = True
+
         if fast_dev_run:
             limit_train_batches = fast_dev_run
             limit_val_batches = fast_dev_run
diff --git a/pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py b/pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py
index bcc1122451ceb..4a35c8f0c1268 100644
--- a/pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py
+++ b/pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py
@@ -614,7 +614,7 @@ def __gather_result_across_time_and_optimizers(self, epoch_output):
 
     def log_train_step_metrics(self, batch_output):
         # when metrics should be logged
-        if self.should_update_logs or (int(self.trainer.fast_dev_run) == 1):
+        if self.should_update_logs or self.trainer.fast_dev_run is True:
             # logs user requested information to logger
             metrics = self.cached_results.get_latest_batch_log_metrics()
             grad_norm_dic = batch_output.grad_norm_dic
diff --git a/pytorch_lightning/trainer/training_loop.py b/pytorch_lightning/trainer/training_loop.py
index 4c5eafb904972..f46279a1e04c4 100644
--- a/pytorch_lightning/trainer/training_loop.py
+++ b/pytorch_lightning/trainer/training_loop.py
@@ -873,7 +873,7 @@ def build_train_args(self, batch, batch_idx, opt_idx, hiddens):
     def save_loggers_on_train_batch_end(self):
         # when loggers should save to disk
         should_flush_logs = self.trainer.logger_connector.should_flush_logs
-        if should_flush_logs or (int(self.trainer.fast_dev_run) == 1):
+        if should_flush_logs or self.trainer.fast_dev_run is True:
             if self.trainer.is_global_zero and self.trainer.logger is not None:
                 self.trainer.logger.save()
 
diff --git a/pytorch_lightning/tuner/batch_size_scaling.py b/pytorch_lightning/tuner/batch_size_scaling.py
index 936efded09bd5..4d182e7180dc0 100644
--- a/pytorch_lightning/tuner/batch_size_scaling.py
+++ b/pytorch_lightning/tuner/batch_size_scaling.py
@@ -70,7 +70,7 @@ def scale_batch_size(trainer,
             or datamodule.
     """
     if trainer.fast_dev_run:
-        rank_zero_warn(f'Skipping batch size scaler since `fast_dev_run={trainer.fast_dev_run}`', UserWarning)
+        rank_zero_warn('Skipping batch size scaler since fast_dev_run is enabled.', UserWarning)
         return
 
     if not lightning_hasattr(model, batch_arg_name):
diff --git a/pytorch_lightning/tuner/lr_finder.py b/pytorch_lightning/tuner/lr_finder.py
index 79335c7bce774..2982454d02f70 100644
--- a/pytorch_lightning/tuner/lr_finder.py
+++ b/pytorch_lightning/tuner/lr_finder.py
@@ -137,7 +137,7 @@ def lr_find(
 
     """
     if trainer.fast_dev_run:
-        rank_zero_warn(f'Skipping learning rate finder since `fast_dev_run={trainer.fast_dev_run}`', UserWarning)
+        rank_zero_warn('Skipping learning rate finder since fast_dev_run is enabled.', UserWarning)
         return
 
     save_path = os.path.join(trainer.default_root_dir, 'lr_find_temp_model.ckpt')
diff --git a/tests/trainer/flags/test_fast_dev_run.py b/tests/trainer/flags/test_fast_dev_run.py
index cbe4d4012227a..00c62cdf48fce 100644
--- a/tests/trainer/flags/test_fast_dev_run.py
+++ b/tests/trainer/flags/test_fast_dev_run.py
@@ -4,7 +4,7 @@
 
 
 @pytest.mark.parametrize('tuner_alg', ['batch size scaler', 'learning rate finder'])
-def test_skip_on_fast_dev_run_batch_scaler(tmpdir, tuner_alg):
+def test_skip_on_fast_dev_run_tuner(tmpdir, tuner_alg):
     """ Test that tuner algorithms are skipped if fast dev run is enabled """
 
     hparams = EvalModelTemplate.get_default_hparams()
@@ -16,6 +16,6 @@ def test_skip_on_fast_dev_run_batch_scaler(tmpdir, tuner_alg):
         auto_lr_find=True if tuner_alg == 'learning rate finder' else False,
         fast_dev_run=True
     )
-    expected_message = f'Skipping {tuner_alg} since `fast_dev_run=True`'
+    expected_message = f'Skipping {tuner_alg} since fast_dev_run is enabled.'
     with pytest.warns(UserWarning, match=expected_message):
         trainer.tune(model)
diff --git a/tests/trainer/test_dataloaders.py b/tests/trainer/test_dataloaders.py
index 844dc31f745b6..75799914404d3 100644
--- a/tests/trainer/test_dataloaders.py
+++ b/tests/trainer/test_dataloaders.py
@@ -434,7 +434,7 @@ def test_dataloaders_with_limit_num_batches(tmpdir, limit_train_batches, limit_v
 
 
 @mock.patch.dict(os.environ, {"PL_DEV_DEBUG": "1"})
-@pytest.mark.parametrize('fast_dev_run', [True, 3, -1, 'temp'])
+@pytest.mark.parametrize('fast_dev_run', [True, 1, 3, -1, 'temp'])
 def test_dataloaders_with_fast_dev_run(tmpdir, fast_dev_run):
     """
     Verify num_batches for train, val & test dataloaders passed with fast_dev_run
@@ -462,6 +462,12 @@ def test_dataloaders_with_fast_dev_run(tmpdir, fast_dev_run):
     else:
         trainer = Trainer(**trainer_options)
 
+        # fast_dev_run is set to True when it is 1
+        if fast_dev_run == 1:
+            fast_dev_run = True
+
+        assert trainer.fast_dev_run is fast_dev_run
+
         if fast_dev_run is True:
             fast_dev_run = 1
 

From 29807f6c963f6a7bb598c2e32dc7d1d8e0298894 Mon Sep 17 00:00:00 2001
From: rohitgr7 <rohitgr1998@gmail.com>
Date: Tue, 8 Dec 2020 23:43:31 +0530
Subject: [PATCH 10/11] codefactor and pre-commit isort

---
 pytorch_lightning/trainer/properties.py    | 14 +++++++-------
 pytorch_lightning/trainer/training_loop.py |  6 +++++-
 2 files changed, 12 insertions(+), 8 deletions(-)

diff --git a/pytorch_lightning/trainer/properties.py b/pytorch_lightning/trainer/properties.py
index 1c1cf66ba2f47..f315bf9df819c 100644
--- a/pytorch_lightning/trainer/properties.py
+++ b/pytorch_lightning/trainer/properties.py
@@ -57,19 +57,19 @@ class TrainerProperties(ABC):
     @property
     def log_dir(self):
         if self.checkpoint_callback is not None:
-            dir = self.checkpoint_callback.dirpath
-            dir = os.path.split(dir)[0]
+            dirpath = self.checkpoint_callback.dirpath
+            dirpath = os.path.split(dirpath)[0]
         elif self.logger is not None:
             if isinstance(self.logger, TensorBoardLogger):
-                dir = self.logger.log_dir
+                dirpath = self.logger.log_dir
             else:
-                dir = self.logger.save_dir
+                dirpath = self.logger.save_dir
         else:
-            dir = self._default_root_dir
+            dirpath = self._default_root_dir
 
         if self.accelerator_backend is not None:
-            dir = self.accelerator_backend.broadcast(dir)
-        return dir
+            dirpath = self.accelerator_backend.broadcast(dirpath)
+        return dirpath
 
     @property
     def use_amp(self) -> bool:
diff --git a/pytorch_lightning/trainer/training_loop.py b/pytorch_lightning/trainer/training_loop.py
index 5e0877ccfa8f6..20dfb0f4b380f 100644
--- a/pytorch_lightning/trainer/training_loop.py
+++ b/pytorch_lightning/trainer/training_loop.py
@@ -215,10 +215,14 @@ def check_checkpoint_callback(self, should_save, is_last=False):
         # TODO bake this logic into the checkpoint callback
         if should_save and self.trainer.checkpoint_connector.has_trained:
             checkpoint_callbacks = [c for c in self.trainer.callbacks if isinstance(c, ModelCheckpoint)]
+
             if is_last and any(c.save_last for c in checkpoint_callbacks):
                 rank_zero_info("Saving latest checkpoint...")
+
             model = self.trainer.get_model()
-            [cb.on_validation_end(self.trainer, model) for cb in checkpoint_callbacks]
+
+            for callback in checkpoint_callbacks:
+                callback.on_validation_end(self.trainer, model)
 
     def on_train_epoch_start(self, epoch):
 

From f8248e3f14de3af02d082cdbef31ac5e9abc89f9 Mon Sep 17 00:00:00 2001
From: rohitgr7 <rohitgr1998@gmail.com>
Date: Tue, 8 Dec 2020 23:47:28 +0530
Subject: [PATCH 11/11] tmp