text: # 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 == 4
      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 == 4
      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")
  