lightning/pytorch_lightning/plugins/base_plugin.py

57 lines
2.0 KiB
Python

# Copyright The PyTorch Lightning team.
#
# Licensed 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.
import contextlib
from abc import ABC, abstractmethod
from typing import Any, Generator, Optional, overload, Sequence, Tuple
import torch
class Plugin(ABC):
"""Basic Plugin class to derive precision and training type plugins from."""
@abstractmethod
def connect(self, model: torch.nn.Module, *args: Sequence,
**kwargs: Sequence) -> Optional[Tuple[torch.nn.Module, Sequence, Sequence]]:
"""Connects the plugin with the accelerator (and thereby with trainer and model).
Will be called by the accelerator.
"""
def pre_optimizer_step(self, optimizer: torch.optim.Optimizer, optimizer_idx: int) -> None:
"""Hook to do something before each optimizer step."""
def post_optimizer_step(self, optimizer: torch.optim.Optimizer, optimizer_idx: int) -> None:
"""Hook to do something after each optimizer step."""
def pre_training(self) -> None:
"""Hook to do something before the training starts."""
def post_training(self) -> None:
"""Hook to do something after the training finishes."""
@contextlib.contextmanager
def train_step_context(self) -> Generator:
"""A contextmanager for the trainstep"""
yield
@contextlib.contextmanager
def val_step_context(self) -> Generator:
"""A contextmanager for the validation step"""
yield
@contextlib.contextmanager
def test_step_context(self) -> Generator:
"""A contextmanager for the teststep"""
yield