142 lines
6.0 KiB
Python
142 lines
6.0 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 vX.Y.Z"""
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from argparse import ArgumentParser
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from unittest import mock
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import pytest
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import torch
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from pytorch_lightning import LightningModule, Trainer
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from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
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from pytorch_lightning.profiler.profilers import PassThroughProfiler, SimpleProfiler
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def test_v1_3_0_deprecated_arguments(tmpdir):
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with pytest.deprecated_call(match='will no longer be supported in v1.3'):
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callback = ModelCheckpoint()
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Trainer(checkpoint_callback=callback, callbacks=[], default_root_dir=tmpdir)
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# Deprecate prefix
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with pytest.deprecated_call(match='will be removed in v1.3'):
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ModelCheckpoint(prefix='temp')
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# Deprecate auto mode
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with pytest.deprecated_call(match='will be removed in v1.3'):
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ModelCheckpoint(mode='auto')
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with pytest.deprecated_call(match='will be removed in v1.3'):
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EarlyStopping(mode='auto')
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with pytest.deprecated_call(match="The setter for self.hparams in LightningModule is deprecated"):
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class DeprecatedHparamsModel(LightningModule):
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def __init__(self, hparams):
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super().__init__()
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self.hparams = hparams
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DeprecatedHparamsModel({})
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def test_v1_3_0_deprecated_metrics():
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from pytorch_lightning.metrics.functional.classification import to_onehot
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with pytest.deprecated_call(match='will be removed in v1.3'):
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to_onehot(torch.tensor([1, 2, 3]))
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from pytorch_lightning.metrics.functional.classification import to_categorical
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with pytest.deprecated_call(match='will be removed in v1.3'):
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to_categorical(torch.tensor([[0.2, 0.5], [0.9, 0.1]]))
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from pytorch_lightning.metrics.functional.classification import get_num_classes
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with pytest.deprecated_call(match='will be removed in v1.3'):
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get_num_classes(pred=torch.tensor([0, 1]), target=torch.tensor([1, 1]))
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x_binary = torch.tensor([0, 1, 2, 3])
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y_binary = torch.tensor([0, 1, 2, 3])
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from pytorch_lightning.metrics.functional.classification import roc
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with pytest.deprecated_call(match='will be removed in v1.3'):
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roc(pred=x_binary, target=y_binary)
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from pytorch_lightning.metrics.functional.classification import _roc
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with pytest.deprecated_call(match='will be removed in v1.3'):
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_roc(pred=x_binary, target=y_binary)
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x_multy = torch.tensor([[0.85, 0.05, 0.05, 0.05],
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[0.05, 0.85, 0.05, 0.05],
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[0.05, 0.05, 0.85, 0.05],
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[0.05, 0.05, 0.05, 0.85]])
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y_multy = torch.tensor([0, 1, 3, 2])
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from pytorch_lightning.metrics.functional.classification import multiclass_roc
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with pytest.deprecated_call(match='will be removed in v1.3'):
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multiclass_roc(pred=x_multy, target=y_multy)
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from pytorch_lightning.metrics.functional.classification import average_precision
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with pytest.deprecated_call(match='will be removed in v1.3'):
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average_precision(pred=x_binary, target=y_binary)
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from pytorch_lightning.metrics.functional.classification import precision_recall_curve
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with pytest.deprecated_call(match='will be removed in v1.3'):
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precision_recall_curve(pred=x_binary, target=y_binary)
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from pytorch_lightning.metrics.functional.classification import multiclass_precision_recall_curve
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with pytest.deprecated_call(match='will be removed in v1.3'):
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multiclass_precision_recall_curve(pred=x_multy, target=y_multy)
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from pytorch_lightning.metrics.functional.reduction import reduce
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with pytest.deprecated_call(match='will be removed in v1.3'):
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reduce(torch.tensor([0, 1, 1, 0]), 'sum')
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from pytorch_lightning.metrics.functional.reduction import class_reduce
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with pytest.deprecated_call(match='will be removed in v1.3'):
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class_reduce(torch.randint(1, 10, (50,)).float(),
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torch.randint(10, 20, (50,)).float(),
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torch.randint(1, 100, (50,)).float())
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# TODO: remove bool from Trainer.profiler param in v1.3.0, update profiler_connector.py
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@pytest.mark.parametrize(['profiler', 'expected'], [
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(True, SimpleProfiler),
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(False, PassThroughProfiler),
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])
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def test_trainer_profiler_remove_in_v1_3_0(profiler, expected):
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# remove bool from Trainer.profiler param in v1.3.0, update profiler_connector.py
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with pytest.deprecated_call(match='will be removed in v1.3'):
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trainer = Trainer(profiler=profiler)
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assert isinstance(trainer.profiler, expected)
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@pytest.mark.parametrize(
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['cli_args', 'expected_parsed_arg', 'expected_profiler'],
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[
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('--profiler', True, SimpleProfiler),
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('--profiler True', True, SimpleProfiler),
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('--profiler False', False, PassThroughProfiler),
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],
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)
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def test_v1_3_0_trainer_cli_profiler(cli_args, expected_parsed_arg, expected_profiler):
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cli_args = cli_args.split(' ')
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with mock.patch("argparse._sys.argv", ["any.py"] + cli_args):
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parser = ArgumentParser(add_help=False)
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parser = Trainer.add_argparse_args(parent_parser=parser)
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args = Trainer.parse_argparser(parser)
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assert getattr(args, "profiler") == expected_parsed_arg
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trainer = Trainer.from_argparse_args(args)
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assert isinstance(trainer.profiler, expected_profiler)
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def test_trainer_enable_pl_optimizer(tmpdir):
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with pytest.deprecated_call(match='will be removed in v1.3'):
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Trainer(enable_pl_optimizer=True)
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