Not a workable version

Author: ultmaster

qlib/rl/trainer/callbacks.py

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+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+
+"""Callbacks to insert customized recipes during the training.
+Mimicks the hooks of Keras / PyTorch-Lightning, but tailored for the context of RL.
+"""
+
+from typing import Any, Dict, List, Optional, TYPE_CHECKING
+
+if TYPE_CHECKING:
+    from .trainer import Trainer
+
+
+class Callback:
+    """Base class of all callbacks."""
+
+    def setup(self, trainer: "Trainer", pl_module: "pl.LightningModule", stage: Optional[str] = None) -> None:
+        """Called when fit, validate, test, predict, or tune begins."""
+
+    def teardown(self, trainer: "Trainer", pl_module: "pl.LightningModule", stage: Optional[str] = None) -> None:
+        """Called when fit, validate, test, predict, or tune ends."""
+
+    def on_init_start(self, trainer: "Trainer") -> None:
+        r"""
+        .. deprecated:: v1.6
+            This callback hook was deprecated in v1.6 and will be removed in v1.8.
+        Called when the trainer initialization begins, model has not yet been set.
+        """
+
+    def on_init_end(self, trainer: "Trainer") -> None:
+        r"""
+        .. deprecated:: v1.6
+            This callback hook was deprecated in v1.6 and will be removed in v1.8.
+        Called when the trainer initialization ends, model has not yet been set.
+        """
+
+    def on_fit_start(self, trainer: "Trainer", pl_module: "pl.LightningModule") -> None:
+        """Called when fit begins."""
+
+    def on_fit_end(self, trainer: "Trainer", pl_module: "pl.LightningModule") -> None:
+        """Called when fit ends."""
+
+    def on_sanity_check_start(self, trainer: "Trainer", pl_module: "pl.LightningModule") -> None:
+        """Called when the validation sanity check starts."""
+
+    def on_sanity_check_end(self, trainer: "Trainer", pl_module: "pl.LightningModule") -> None:
+        """Called when the validation sanity check ends."""
+
+    def on_train_batch_start(
+        self,
+        trainer: "Trainer",
+        pl_module: "pl.LightningModule",
+        batch: Any,
+        batch_idx: int,
+        unused: int = 0,
+    ) -> None:
+        """Called when the train batch begins."""
+
+    def on_train_batch_end(
+        self,
+        trainer: "Trainer",
+        pl_module: "pl.LightningModule",
+        outputs: STEP_OUTPUT,
+        batch: Any,
+        batch_idx: int,
+        unused: int = 0,
+    ) -> None:
+        """Called when the train batch ends."""
+
+    def on_train_epoch_start(self, trainer: "Trainer", pl_module: "pl.LightningModule") -> None:
+        """Called when the train epoch begins."""
+
+    def on_train_epoch_end(self, trainer: "Trainer", pl_module: "pl.LightningModule") -> None:
+        """Called when the train epoch ends.
+        To access all batch outputs at the end of the epoch, either:
+        1. Implement `training_epoch_end` in the `LightningModule` and access outputs via the module OR
+        2. Cache data across train batch hooks inside the callback implementation to post-process in this hook.
+        """
+
+    def on_validation_epoch_start(self, trainer: "Trainer", pl_module: "pl.LightningModule") -> None:
+        """Called when the val epoch begins."""
+
+    def on_validation_epoch_end(self, trainer: "Trainer", pl_module: "pl.LightningModule") -> None:
+        """Called when the val epoch ends."""
+
+    def on_test_epoch_start(self, trainer: "Trainer", pl_module: "pl.LightningModule") -> None:
+        """Called when the test epoch begins."""
+
+    def on_test_epoch_end(self, trainer: "Trainer", pl_module: "pl.LightningModule") -> None:
+        """Called when the test epoch ends."""
+
+    def on_predict_epoch_start(self, trainer: "Trainer", pl_module: "pl.LightningModule") -> None:
+        """Called when the predict epoch begins."""
+
+    def on_predict_epoch_end(self, trainer: "Trainer", pl_module: "pl.LightningModule", outputs: List[Any]) -> None:
+        """Called when the predict epoch ends."""
+
+    def on_epoch_start(self, trainer: "Trainer", pl_module: "pl.LightningModule") -> None:
+        r"""
+        .. deprecated:: v1.6
+            This callback hook was deprecated in v1.6 and will be removed in v1.8. Use
+            ``on_<train/validation/test>_epoch_start`` instead.
+        Called when either of train/val/test epoch begins.
+        """
+
+    def on_epoch_end(self, trainer: "Trainer", pl_module: "pl.LightningModule") -> None:
+        r"""
+        .. deprecated:: v1.6
+            This callback hook was deprecated in v1.6 and will be removed in v1.8. Use
+            ``on_<train/validation/test>_epoch_end`` instead.
+        Called when either of train/val/test epoch ends.
+        """
+
+    def on_batch_start(self, trainer: "Trainer", pl_module: "pl.LightningModule") -> None:
+        r"""
+        .. deprecated:: v1.6
+            This callback hook was deprecated in v1.6 and will be removed in v1.8. Use
+            ``on_train_batch_start`` instead.
+        Called when the training batch begins.
+        """
+
+    def on_batch_end(self, trainer: "Trainer", pl_module: "pl.LightningModule") -> None:
+        r"""
+        .. deprecated:: v1.6
+            This callback hook was deprecated in v1.6 and will be removed in v1.8. Use
+            ``on_train_batch_end`` instead.
+        Called when the training batch ends.
+        """
+
+    def on_validation_batch_start(
+        self, trainer: "Trainer", pl_module: "pl.LightningModule", batch: Any, batch_idx: int, dataloader_idx: int
+    ) -> None:
+        """Called when the validation batch begins."""
+
+    def on_validation_batch_end(
+        self,
+        trainer: "Trainer",
+        pl_module: "pl.LightningModule",
+        outputs: Optional[STEP_OUTPUT],
+        batch: Any,
+        batch_idx: int,
+        dataloader_idx: int,
+    ) -> None:
+        """Called when the validation batch ends."""
+
+    def on_test_batch_start(
+        self, trainer: "Trainer", pl_module: "pl.LightningModule", batch: Any, batch_idx: int, dataloader_idx: int
+    ) -> None:
+        """Called when the test batch begins."""
+
+    def on_test_batch_end(
+        self,
+        trainer: "Trainer",
+        pl_module: "pl.LightningModule",
+        outputs: Optional[STEP_OUTPUT],
+        batch: Any,
+        batch_idx: int,
+        dataloader_idx: int,
+    ) -> None:
+        """Called when the test batch ends."""
+
+    def on_predict_batch_start(
+        self, trainer: "Trainer", pl_module: "pl.LightningModule", batch: Any, batch_idx: int, dataloader_idx: int
+    ) -> None:
+        """Called when the predict batch begins."""
+
+    def on_predict_batch_end(
+        self,
+        trainer: "Trainer",
+        pl_module: "pl.LightningModule",
+        outputs: Any,
+        batch: Any,
+        batch_idx: int,
+        dataloader_idx: int,
+    ) -> None:
+        """Called when the predict batch ends."""
+
+    def on_train_start(self, trainer: "Trainer", pl_module: "pl.LightningModule") -> None:
+        """Called when the train begins."""
+
+    def on_train_end(self, trainer: "Trainer", pl_module: "pl.LightningModule") -> None:
+        """Called when the train ends."""
+
+    def on_pretrain_routine_start(self, trainer: "Trainer", pl_module: "pl.LightningModule") -> None:
+        r"""
+        .. deprecated:: v1.6
+            This callback hook was deprecated in v1.6 and will be removed in v1.8. Use ``on_fit_start`` instead.
+        Called when the pretrain routine begins.
+        """
+
+    def on_pretrain_routine_end(self, trainer: "Trainer", pl_module: "pl.LightningModule") -> None:
+        r"""
+        .. deprecated:: v1.6
+            This callback hook was deprecated in v1.6 and will be removed in v1.8. Use ``on_fit_start`` instead.
+        Called when the pretrain routine ends.
+        """
+
+    def on_validation_start(self, trainer: "Trainer", pl_module: "pl.LightningModule") -> None:
+        """Called when the validation loop begins."""
+
+    def on_validation_end(self, trainer: "Trainer", pl_module: "pl.LightningModule") -> None:
+        """Called when the validation loop ends."""
+
+    def on_test_start(self, trainer: "Trainer", pl_module: "pl.LightningModule") -> None:
+        """Called when the test begins."""
+
+    def on_test_end(self, trainer: "Trainer", pl_module: "pl.LightningModule") -> None:
+        """Called when the test ends."""
+
+    def on_predict_start(self, trainer: "Trainer", pl_module: "pl.LightningModule") -> None:
+        """Called when the predict begins."""
+
+    def on_predict_end(self, trainer: "Trainer", pl_module: "pl.LightningModule") -> None:
+        """Called when predict ends."""
+
+    def on_keyboard_interrupt(self, trainer: "Trainer", pl_module: "pl.LightningModule") -> None:
+        r"""
+        .. deprecated:: v1.5
+            This callback hook was deprecated in v1.5 in favor of `on_exception` and will be removed in v1.7.
+        Called when any trainer execution is interrupted by KeyboardInterrupt.
+        """
+
+    def on_exception(self, trainer: "Trainer", pl_module: "pl.LightningModule", exception: BaseException) -> None:
+        """Called when any trainer execution is interrupted by an exception."""
+
+    def state_dict(self) -> Dict[str, Any]:
+        """Called when saving a checkpoint, implement to generate callback's ``state_dict``.
+        Returns:
+            A dictionary containing callback state.
+        """
+        return {}
+
+    def load_state_dict(self, state_dict: Dict[str, Any]) -> None:
+        """Called when loading a checkpoint, implement to reload callback state given callback's ``state_dict``.
+        Args:
+            state_dict: the callback state returned by ``state_dict``.
+        """
+        pass
+
+    def on_save_checkpoint(
+        self, trainer: "Trainer", pl_module: "pl.LightningModule", checkpoint: Dict[str, Any]
+    ) -> Optional[dict]:
+        r"""
+        Called when saving a checkpoint to give you a chance to store anything else you might want to save.
+        Args:
+            trainer: the current :class:`~pytorch_lightning.trainer.Trainer` instance.
+            pl_module: the current :class:`~pytorch_lightning.core.lightning.LightningModule` instance.
+            checkpoint: the checkpoint dictionary that will be saved.
+        Returns:
+            None or the callback state. Support for returning callback state will be removed in v1.8.
+        .. deprecated:: v1.6
+            Returning a value from this method was deprecated in v1.6 and will be removed in v1.8.
+            Implement ``Callback.state_dict`` instead to return state.
+            In v1.8 ``Callback.on_save_checkpoint`` can only return None.
+        """
+
+    def on_load_checkpoint(
+        self, trainer: "Trainer", pl_module: "pl.LightningModule", callback_state: Dict[str, Any]
+    ) -> None:
+        r"""
+        Called when loading a model checkpoint, use to reload state.
+        Args:
+            trainer: the current :class:`~pytorch_lightning.trainer.Trainer` instance.
+            pl_module: the current :class:`~pytorch_lightning.core.lightning.LightningModule` instance.
+            callback_state: the callback state returned by ``on_save_checkpoint``.
+        Note:
+            The ``on_load_checkpoint`` won't be called with an undefined state.
+            If your ``on_load_checkpoint`` hook behavior doesn't rely on a state,
+            you will still need to override ``on_save_checkpoint`` to return a ``dummy state``.
+        .. deprecated:: v1.6
+            This callback hook will change its signature and behavior in v1.8.
+            If you wish to load the state of the callback, use ``Callback.load_state_dict`` instead.
+            In v1.8 ``Callback.on_load_checkpoint(checkpoint)`` will receive the entire loaded
+            checkpoint dictionary instead of only the callback state from the checkpoint.
+        """
+
+    def on_before_backward(self, trainer: "Trainer", pl_module: "pl.LightningModule", loss: torch.Tensor) -> None:
+        """Called before ``loss.backward()``."""
+
+    def on_after_backward(self, trainer: "Trainer", pl_module: "pl.LightningModule") -> None:
+        """Called after ``loss.backward()`` and before optimizers are stepped."""
+
+    def on_before_optimizer_step(
+        self, trainer: "Trainer", pl_module: "pl.LightningModule", optimizer: Optimizer, opt_idx: int
+    ) -> None:
+        """Called before ``optimizer.step()``."""
+
+    def on_before_zero_grad(self, trainer: "Trainer", pl_module: "pl.LightningModule", optimizer: Optimizer) -> None:
+        """Called before ``optimizer.zero_grad()``."""