88 lines
3.4 KiB
Python
88 lines
3.4 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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from typing import List, Union
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import pytest
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from pytorch_lightning import Trainer
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from pytorch_lightning.callbacks import ModelSummary
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from tests.helpers.boring_model import BoringModel
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def test_model_summary_callback_present_trainer():
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trainer = Trainer()
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assert any(isinstance(cb, ModelSummary) for cb in trainer.callbacks)
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trainer = Trainer(callbacks=ModelSummary())
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assert any(isinstance(cb, ModelSummary) for cb in trainer.callbacks)
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def test_model_summary_callback_with_weights_summary_none():
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with pytest.deprecated_call(match=r"weights_summary=None\)` is deprecated"):
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trainer = Trainer(weights_summary=None)
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assert not any(isinstance(cb, ModelSummary) for cb in trainer.callbacks)
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trainer = Trainer(enable_model_summary=False)
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assert not any(isinstance(cb, ModelSummary) for cb in trainer.callbacks)
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trainer = Trainer(enable_model_summary=False, weights_summary="full")
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assert not any(isinstance(cb, ModelSummary) for cb in trainer.callbacks)
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with pytest.deprecated_call(match=r"weights_summary=None\)` is deprecated"):
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trainer = Trainer(enable_model_summary=True, weights_summary=None)
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assert not any(isinstance(cb, ModelSummary) for cb in trainer.callbacks)
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def test_model_summary_callback_with_weights_summary():
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trainer = Trainer(weights_summary="top")
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model_summary_callback = list(filter(lambda cb: isinstance(cb, ModelSummary), trainer.callbacks))[0]
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assert model_summary_callback._max_depth == 1
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with pytest.deprecated_call(match=r"weights_summary=full\)` is deprecated"):
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trainer = Trainer(weights_summary="full")
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model_summary_callback = list(filter(lambda cb: isinstance(cb, ModelSummary), trainer.callbacks))[0]
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assert model_summary_callback._max_depth == -1
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def test_model_summary_callback_override_weights_summary_flag():
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with pytest.deprecated_call(match=r"weights_summary=None\)` is deprecated"):
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trainer = Trainer(callbacks=ModelSummary(), weights_summary=None)
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assert any(isinstance(cb, ModelSummary) for cb in trainer.callbacks)
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def test_custom_model_summary_callback_summarize(tmpdir):
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class CustomModelSummary(ModelSummary):
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@staticmethod
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def summarize(
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summary_data: List[List[Union[str, List[str]]]],
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total_parameters: int,
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trainable_parameters: int,
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model_size: float,
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) -> None:
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assert summary_data[1][0] == "Name"
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assert summary_data[1][1][0] == "layer"
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assert summary_data[2][0] == "Type"
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assert summary_data[2][1][0] == "Linear"
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assert summary_data[3][0] == "Params"
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assert total_parameters == 66
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assert trainable_parameters == 66
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model = BoringModel()
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trainer = Trainer(default_root_dir=tmpdir, callbacks=CustomModelSummary(), max_steps=1)
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trainer.fit(model)
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