89 lines
4.4 KiB
Python
89 lines
4.4 KiB
Python
# Copyright The PyTorch Lightning team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Test deprecated functionality which will be removed in v2.0.0."""
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from unittest import mock
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import pytest
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import pytorch_lightning
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from pytorch_lightning import Trainer
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from tests.callbacks.test_callbacks import OldStatefulCallback
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from tests.helpers import BoringModel
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def test_v2_0_0_deprecated_num_processes():
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with pytest.deprecated_call(match=r"is deprecated in v1.7 and will be removed in v2.0."):
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_ = Trainer(num_processes=2)
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@mock.patch("torch.cuda.is_available", return_value=True)
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@mock.patch("torch.cuda.device_count", return_value=2)
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def test_v2_0_0_deprecated_gpus(*_):
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with pytest.deprecated_call(match=r"is deprecated in v1.7 and will be removed in v2.0."):
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_ = Trainer(gpus=0)
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@mock.patch("pytorch_lightning.accelerators.tpu.TPUAccelerator.is_available", return_value=True)
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@mock.patch("pytorch_lightning.accelerators.tpu.TPUAccelerator.parse_devices", return_value=8)
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def test_v2_0_0_deprecated_tpu_cores(*_):
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with pytest.deprecated_call(match=r"is deprecated in v1.7 and will be removed in v2.0."):
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_ = Trainer(tpu_cores=8)
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@mock.patch("pytorch_lightning.accelerators.ipu.IPUAccelerator.is_available", return_value=True)
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def test_v2_0_0_deprecated_ipus(_, monkeypatch):
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monkeypatch.setattr(pytorch_lightning.strategies.ipu, "_IPU_AVAILABLE", True)
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with pytest.deprecated_call(match=r"is deprecated in v1.7 and will be removed in v2.0."):
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_ = Trainer(ipus=4)
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def test_v2_0_resume_from_checkpoint_trainer_constructor(tmpdir):
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# test resume_from_checkpoint still works until v2.0 deprecation
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model = BoringModel()
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callback = OldStatefulCallback(state=111)
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trainer = Trainer(default_root_dir=tmpdir, max_steps=1, callbacks=[callback])
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trainer.fit(model)
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ckpt_path = trainer.checkpoint_callback.best_model_path
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callback = OldStatefulCallback(state=222)
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with pytest.deprecated_call(match=r"Setting `Trainer\(resume_from_checkpoint=\)` is deprecated in v1.5"):
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trainer = Trainer(default_root_dir=tmpdir, max_steps=2, callbacks=[callback], resume_from_checkpoint=ckpt_path)
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with pytest.deprecated_call(match=r"trainer.resume_from_checkpoint` is deprecated in v1.5"):
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_ = trainer.resume_from_checkpoint
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assert trainer._checkpoint_connector.resume_checkpoint_path is None
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assert trainer._checkpoint_connector.resume_from_checkpoint_fit_path == ckpt_path
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trainer.validate(model=model, ckpt_path=ckpt_path)
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assert callback.state == 222
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assert trainer._checkpoint_connector.resume_checkpoint_path is None
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assert trainer._checkpoint_connector.resume_from_checkpoint_fit_path == ckpt_path
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with pytest.deprecated_call(match=r"trainer.resume_from_checkpoint` is deprecated in v1.5"):
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trainer.fit(model)
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ckpt_path = trainer.checkpoint_callback.best_model_path # last `fit` replaced the `best_model_path`
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assert callback.state == 111
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assert trainer._checkpoint_connector.resume_checkpoint_path is None
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assert trainer._checkpoint_connector.resume_from_checkpoint_fit_path is None
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trainer.predict(model=model, ckpt_path=ckpt_path)
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assert trainer._checkpoint_connector.resume_checkpoint_path is None
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assert trainer._checkpoint_connector.resume_from_checkpoint_fit_path is None
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trainer.fit(model)
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assert trainer._checkpoint_connector.resume_checkpoint_path is None
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assert trainer._checkpoint_connector.resume_from_checkpoint_fit_path is None
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# test fit(ckpt_path=) precedence over Trainer(resume_from_checkpoint=) path
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model = BoringModel()
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with pytest.deprecated_call(match=r"Setting `Trainer\(resume_from_checkpoint=\)` is deprecated in v1.5"):
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trainer = Trainer(resume_from_checkpoint="trainer_arg_path")
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with pytest.raises(FileNotFoundError, match="Checkpoint at fit_arg_ckpt_path not found. Aborting training."):
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trainer.fit(model, ckpt_path="fit_arg_ckpt_path")
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