[Meta Schedule][M4a] Local runner (apache#9153)

* [Meta Schedule][M3a]Local runner (apache#479)

* localrunner

* localrunner init

* linting

* address comments

* exception handling

* single run testcase

* two more cases added

* add exception case

* one case with AddModule added

* address comments

* address comments

* remove unused dependency

* optional arguments

* linting

* add utils

* linting

* address comments

* remove non-ascii commennt

* add sanity check

* address comments

python/tvm/meta_schedule/runner/__init__.py

@@ -20,4 +20,5 @@
 """
 from .config import EvaluatorConfig, RPCConfig
 from .rpc_runner import RPCRunner
+from .local_runner import LocalRunner, LocalRunnerFuture
 from .runner import PyRunner, Runner, RunnerFuture, RunnerInput, RunnerResult

python/tvm/meta_schedule/runner/local_runner.py

@@ -0,0 +1,359 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, 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.
+"""Local Runner"""
+from contextlib import contextmanager
+from typing import Callable, List, Optional, Union
+import tvm
+
+from ...contrib.popen_pool import PopenPoolExecutor
+from ...runtime import Device, Module
+from ..utils import get_global_func_with_default_on_worker
+from .config import EvaluatorConfig
+from .runner import PyRunner, RunnerFuture, RunnerInput, RunnerResult
+from .utils import (
+    T_ARG_INFO_JSON_OBJ_LIST,
+    T_ARGUMENT_LIST,
+    alloc_argument_common,
+    run_evaluator_common,
+)
+
+
+class LocalRunnerFuture(RunnerFuture):
+    """Local based runner future
+
+    Parameters
+    ----------
+    res: Optional[List[float]]
+        The optional result as a list of float.
+    error_message: Optional[str]
+        The optional error message.
+
+    Note
+    ----
+    Only one of the parameters should be None upon the creation
+    of LocalRunnerFuture object
+    """
+
+    res: Optional[List[float]]
+    error_message: Optional[str]
+
+    def __init__(
+        self, res: Optional[List[float]] = None, error_message: Optional[str] = None
+    ) -> None:
+        """Constructor
+
+        Parameters
+        ----------
+        res: Optional[List[float]]
+            The result of this LocalRunnerFuture
+        error_message: Optional[str]
+            The stringfied error message of any exception during execution
+
+        """
+        super().__init__()
+        self.res = res
+        self.error_message = error_message
+
+        # sanity check upon the creation of LocalRunnerFuture object
+        if (res is None and error_message is None) or (
+            res is not None and error_message is not None
+        ):
+            raise AttributeError(
+                "Only one of the two parameters should be None upon the creation"
+                "of LocalRunnerFuture object."
+            )
+
+    def done(self) -> bool:
+        return True
+
+    def result(self) -> RunnerResult:
+        return RunnerResult(self.res, self.error_message)
+
+
+class LocalRunner(PyRunner):
+    """Local runner
+
+    Parameters
+    ----------
+    evaluator_config: EvaluatorConfig
+        The evaluator configuration.
+    cooldown_sec: float
+        The cooldown in seconds.
+    alloc_repeat: int
+        The number of times to repeat the allocation.
+    f_alloc_argument: Optional[str, Callable]
+        The function name to allocate the arguments or the function itself.
+    f_run_evaluator: Optional[str, Callable]
+        The function name to run the evaluator or the function itself.
+    f_cleanup: Optional[str, Callable]
+        The function name to cleanup the session or the function itself.
+    pool: PopenPoolExecutor
+        The popen pool executor.
+
+    Attributes
+    ----------
+    T_ALLOC_ARGUMENT : typing._GenericAlias
+        The signature of the function `f_alloc_argument`, which is:
+
+        .. code-block:: python
+
+        def default_alloc_argument(
+            device: Device,
+            args_info: T_ARG_INFO_JSON_OBJ_LIST,
+            alloc_repeat: int,
+        ) -> List[T_ARGUMENT_LIST]:
+            ...
+
+    T_RUN_EVALUATOR : typing._GenericAlias
+        The signature of the function `f_run_evaluator`, which is:
+
+        .. code-block:: python
+
+        def default_run_evaluator(
+            rt_mod: Module,
+            device: Device,
+            evaluator_config: EvaluatorConfig,
+            repeated_args: List[T_ARGUMENT_LIST],
+        ) -> List[float]:
+            ...
+
+    T_CLEANUP : typing._GenericAlias
+        The signature of the function `f_cleanup`, which is:
+
+        .. code-block:: python
+
+        def default_cleanup() -> None:
+            ...
+    """
+
+    T_ALLOC_ARGUMENT = Callable[
+        [
+            Device,  # The device on the remote
+            T_ARG_INFO_JSON_OBJ_LIST,  # The metadata information of the arguments to be allocated
+            int,  # The number of repeated allocations to be done
+        ],
+        List[T_ARGUMENT_LIST],  # A list of argument lists
+    ]
+    T_RUN_EVALUATOR = Callable[
+        [
+            Module,  # The Module opened on the remote
+            Device,  # The device on the remote
+            EvaluatorConfig,  # The evaluator configuration
+            List[T_ARGUMENT_LIST],  # A list of argument lists
+        ],
+        List[float],  # A list of running time
+    ]
+    T_CLEANUP = Callable[
+        [],
+        None,
+    ]
+
+    timeout_sec: float
+    evaluator_config: EvaluatorConfig
+    cooldown_sec: float
+    alloc_repeat: int
+
+    f_alloc_argument: Union[T_ALLOC_ARGUMENT, str, None]
+    f_run_evaluator: Union[T_RUN_EVALUATOR, str, None]
+    f_cleanup: Union[T_CLEANUP, str, None]
+
+    pool: PopenPoolExecutor
+
+    def __init__(
+        self,
+        timeout_sec: float,
+        evaluator_config: Optional[EvaluatorConfig] = None,
+        cooldown_sec: float = 0.0,
+        alloc_repeat: int = 1,
+        f_alloc_argument: Optional[str] = None,
+        f_run_evaluator: Optional[str] = None,
+        f_cleanup: Optional[str] = None,
+        initializer: Optional[Callable[[], None]] = None,
+    ) -> None:
+        super().__init__()
+        self.timeout_sec = timeout_sec
+        self.evaluator_config = EvaluatorConfig._normalized(evaluator_config)
+        self.cooldown_sec = cooldown_sec
+        self.alloc_repeat = alloc_repeat
+        self.f_alloc_argument = f_alloc_argument
+        self.f_run_evaluator = f_run_evaluator
+        self.f_cleanup = f_cleanup
+
+        self.pool = PopenPoolExecutor(
+            max_workers=1,  # one local worker
+            timeout=timeout_sec,
+            initializer=initializer,
+        )
+        self._sanity_check()
+
+    def run(self, runner_inputs: List[RunnerInput]) -> List[RunnerFuture]:
+        results: List[RunnerFuture] = []
+        for runner_input in runner_inputs:
+            future = self.pool.submit(
+                LocalRunner._worker_func,
+                self.f_alloc_argument,
+                self.f_run_evaluator,
+                self.f_cleanup,
+                self.evaluator_config,
+                self.alloc_repeat,
+                str(runner_input.artifact_path),
+                str(runner_input.device_type),
+                tuple(arg_info.as_json() for arg_info in runner_input.args_info),
+            )
+            try:
+                result: List[float] = future.result()
+                error_message: str = None
+            except TimeoutError as exception:
+                result: List[float] = None
+                error_message: str = (
+                    f"LocalRunner: Timeout, killed after {self.timeout_sec} seconds\n"
+                )
+            except Exception as exception:  # pylint: disable=broad-except
+                result: List[float] = None
+                error_message: str = "LocalRunner: An exception occurred\n" + str(exception)
+            local_future = LocalRunnerFuture(res=result, error_message=error_message)
+            results.append(local_future)
+        return results
+
+    def _sanity_check(self) -> None:
+        def _check(
+            f_alloc_argument,
+            f_run_evaluator,
+            f_cleanup,
+        ) -> None:
+            get_global_func_with_default_on_worker(name=f_alloc_argument, default=None)
+            get_global_func_with_default_on_worker(name=f_run_evaluator, default=None)
+            get_global_func_with_default_on_worker(name=f_cleanup, default=None)
+            get_global_func_with_default_on_worker(
+                name="tvm.contrib.random.random_fill", default=None
+            )
+
+        value = self.pool.submit(
+            _check,
+            self.f_alloc_argument,
+            self.f_run_evaluator,
+            self.f_cleanup,
+        )
+        value.result()
+
+    @staticmethod
+    def _worker_func(
+        _f_alloc_argument: Optional[str],
+        _f_run_evaluator: Optional[str],
+        _f_cleanup: Optional[str],
+        evaluator_config: EvaluatorConfig,
+        alloc_repeat: int,
+        artifact_path: str,
+        device_type: str,
+        args_info: T_ARG_INFO_JSON_OBJ_LIST,
+    ) -> List[float]:
+        f_alloc_argument: LocalRunner.T_ALLOC_ARGUMENT = get_global_func_with_default_on_worker(
+            _f_alloc_argument, default_alloc_argument
+        )
+        f_run_evaluator: LocalRunner.T_RUN_EVALUATOR = get_global_func_with_default_on_worker(
+            _f_run_evaluator, default_run_evaluator
+        )
+        f_cleanup: LocalRunner.T_CLEANUP = get_global_func_with_default_on_worker(
+            _f_cleanup, default_cleanup
+        )
+
+        @contextmanager
+        def resource_handler():
+            try:
+                yield
+            finally:
+                # Final step. Always clean up
+                f_cleanup()
+
+        with resource_handler():
+            # Step 1: create the local runtime module
+            rt_mod = tvm.runtime.load_module(artifact_path)
+            # Step 2: create the local device
+            device = tvm.runtime.device(dev_type=device_type, dev_id=0)
+            # Step 3: Allocate input arguments
+            repeated_args: List[T_ARGUMENT_LIST] = f_alloc_argument(
+                device,
+                args_info,
+                alloc_repeat,
+            )
+            # Step 4: Run time_evaluator
+            costs: List[float] = f_run_evaluator(
+                rt_mod,
+                device,
+                evaluator_config,
+                repeated_args,
+            )
+        return costs
+
+
+def default_alloc_argument(
+    device: Device,
+    args_info: T_ARG_INFO_JSON_OBJ_LIST,
+    alloc_repeat: int,
+) -> List[T_ARGUMENT_LIST]:
+    """Default function to allocate the arguments
+
+    Parameters
+    ----------
+    device: Device
+        The device to allocate the arguments
+    args_info: T_ARG_INFO_JSON_OBJ_LIST
+        The arguments info
+    alloc_repeat: int
+        The number of times to repeat the allocation
+
+    Returns
+    -------
+    repeated_args: List[T_ARGUMENT_LIST]
+        The allocation args
+    """
+    f_random_fill = get_global_func_with_default_on_worker(
+        name="tvm.contrib.random.random_fill", default=None
+    )
+    return alloc_argument_common(f_random_fill, device, args_info, alloc_repeat)
+
+
+def default_run_evaluator(
+    rt_mod: Module,
+    device: Device,
+    evaluator_config: EvaluatorConfig,
+    repeated_args: List[T_ARGUMENT_LIST],
+) -> List[float]:
+    """Default function to run the evaluator
+
+    Parameters
+    ----------
+    rt_mod: Module
+        The runtime module
+    device: Device
+        The device to run the evaluator
+    evaluator_config: EvaluatorConfig
+        The evaluator config
+    repeated_args: List[T_ARGUMENT_LIST]
+        The repeated arguments
+
+    Returns
+    -------
+    costs: List[float]
+        The evaluator results
+    """
+    return run_evaluator_common(rt_mod, device, evaluator_config, repeated_args)
+
+
+def default_cleanup() -> None:
+    """Default function to clean up the session"""
+    pass  # pylint: disable=unnecessary-pass