# 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 os from typing import Any, Dict, Optional from unittest.mock import MagicMock import torch from pytorch_lightning import Trainer from pytorch_lightning.callbacks import ModelCheckpoint from pytorch_lightning.plugins import CheckpointIO from pytorch_lightning.strategies import SingleDeviceStrategy from pytorch_lightning.utilities.types import _PATH from tests.helpers.boring_model import BoringModel class CustomCheckpointIO(CheckpointIO): def save_checkpoint(self, checkpoint: Dict[str, Any], path: _PATH, storage_options: Optional[Any] = None) -> None: torch.save(checkpoint, path) def load_checkpoint(self, path: _PATH, storage_options: Optional[Any] = None) -> Dict[str, Any]: return torch.load(path) def remove_checkpoint(self, path: _PATH) -> None: os.remove(path) def test_checkpoint_plugin_called(tmpdir): """Ensure that the custom checkpoint IO plugin and torch checkpoint IO plugin is called when saving/loading.""" checkpoint_plugin = CustomCheckpointIO() checkpoint_plugin = MagicMock(wraps=checkpoint_plugin, spec=CustomCheckpointIO) ck = ModelCheckpoint(dirpath=tmpdir, save_last=True) model = BoringModel() trainer = Trainer( default_root_dir=tmpdir, strategy=SingleDeviceStrategy("cpu", checkpoint_io=checkpoint_plugin), callbacks=ck, max_epochs=2, ) trainer.fit(model) assert checkpoint_plugin.save_checkpoint.call_count == 5 assert checkpoint_plugin.remove_checkpoint.call_count == 1 trainer.test(model, ckpt_path=ck.last_model_path) checkpoint_plugin.load_checkpoint.assert_called_with(tmpdir / "last.ckpt") checkpoint_plugin.reset_mock() ck = ModelCheckpoint(dirpath=tmpdir, save_last=True) model = BoringModel() trainer = Trainer( default_root_dir=tmpdir, strategy=SingleDeviceStrategy("cpu"), plugins=[checkpoint_plugin], callbacks=ck, max_epochs=2, ) trainer.fit(model) assert checkpoint_plugin.save_checkpoint.call_count == 5 assert checkpoint_plugin.remove_checkpoint.call_count == 1 trainer.test(model, ckpt_path=ck.last_model_path) checkpoint_plugin.load_checkpoint.assert_called_once() checkpoint_plugin.load_checkpoint.assert_called_with(tmpdir / "last.ckpt")