90 lines
2.9 KiB
Python
90 lines
2.9 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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import pytest
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from pytorch_lightning import Callback, Trainer
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from pytorch_lightning.trainer.states import TrainerState
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from tests.helpers import BoringModel
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def test_initialize_state(tmpdir):
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""" Tests that state is INITIALIZE after Trainer creation """
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trainer = Trainer(default_root_dir=tmpdir)
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assert trainer.state == TrainerState.INITIALIZING
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@pytest.mark.parametrize(
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"extra_params", [
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pytest.param(dict(fast_dev_run=True), id='Fast-Run'),
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pytest.param(dict(max_steps=1), id='Single-Step'),
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]
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)
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def test_trainer_state_while_running(tmpdir, extra_params):
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trainer = Trainer(default_root_dir=tmpdir, **extra_params, auto_lr_find=True)
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class TestModel(BoringModel):
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def __init__(self, expected_state):
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super().__init__()
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self.expected_state = expected_state
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self.lr = 0.1
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def on_batch_start(self, *_):
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assert self.trainer.state == self.expected_state
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def on_train_batch_start(self, *_):
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assert self.trainer.training
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def on_sanity_check_start(self, *_):
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assert self.trainer.sanity_checking
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def on_validation_batch_start(self, *_):
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assert self.trainer.validating or self.trainer.sanity_checking
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def on_test_batch_start(self, *_):
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assert self.trainer.testing
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model = TestModel(TrainerState.TUNING)
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trainer.tune(model)
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assert trainer.state == TrainerState.FINISHED
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model = TestModel(TrainerState.FITTING)
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trainer.fit(model)
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assert trainer.state == TrainerState.FINISHED
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model = TestModel(TrainerState.TESTING)
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trainer.test(model)
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assert trainer.state == TrainerState.FINISHED
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@pytest.mark.parametrize(
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"extra_params", [
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pytest.param(dict(fast_dev_run=True), id='Fast-Run'),
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pytest.param(dict(max_steps=1), id='Single-Step'),
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]
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)
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def test_interrupt_state_on_keyboard_interrupt(tmpdir, extra_params):
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""" Tests that state is set to INTERRUPTED on KeyboardInterrupt """
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model = BoringModel()
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class InterruptCallback(Callback):
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def on_batch_start(self, trainer, pl_module):
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raise KeyboardInterrupt
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trainer = Trainer(callbacks=[InterruptCallback()], default_root_dir=tmpdir, **extra_params)
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trainer.fit(model)
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assert trainer.state == TrainerState.INTERRUPTED
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