90 lines
3.4 KiB
Python
90 lines
3.4 KiB
Python
# Copyright The Lightning AI 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 lightning.pytorch import Callback, Trainer
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from lightning.pytorch.demos.boring_classes import BoringModel
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from lightning.pytorch.trainer.states import RunningStage, TrainerFn, TrainerState, TrainerStatus
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def test_initialize_state():
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"""Tests that state is INITIALIZING after Trainer creation."""
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trainer = Trainer()
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assert trainer.state == TrainerState(status=TrainerStatus.INITIALIZING, fn=None, stage=None)
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@pytest.mark.parametrize(
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"extra_params",
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[pytest.param({"fast_dev_run": True}, id="Fast-Run"), pytest.param({"max_steps": 1}, id="Single-Step")],
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)
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def test_trainer_fn_while_running(tmp_path, extra_params):
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class TestModel(BoringModel):
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def __init__(self, expected_fn, expected_stage):
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super().__init__()
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self.expected_fn = expected_fn
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self.expected_stage = expected_stage
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self.lr = 0.1
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def on_train_batch_start(self, *_):
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assert self.trainer.state.status == TrainerStatus.RUNNING
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assert self.trainer.state.fn == self.expected_fn
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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.state.status == TrainerStatus.RUNNING
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assert self.trainer.state.fn == self.expected_fn
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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.state.status == TrainerStatus.RUNNING
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assert self.trainer.state.fn == self.expected_fn
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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.state.status == TrainerStatus.RUNNING
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assert self.trainer.state.fn == self.expected_fn
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assert self.trainer.testing
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trainer = Trainer(default_root_dir=tmp_path, **extra_params)
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model = TestModel(TrainerFn.FITTING, RunningStage.TRAINING)
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trainer.fit(model)
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assert trainer.state.finished
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model = TestModel(TrainerFn.VALIDATING, RunningStage.VALIDATING)
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trainer.validate(model)
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assert trainer.state.finished
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model = TestModel(TrainerFn.TESTING, RunningStage.TESTING)
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trainer.test(model)
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assert trainer.state.finished
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@pytest.mark.parametrize(
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"extra_params",
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[pytest.param({"fast_dev_run": True}, id="Fast-Run"), pytest.param({"max_steps": 1}, id="Single-Step")],
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)
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def test_interrupt_state_on_keyboard_interrupt(tmp_path, 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_train_batch_start(self, trainer, pl_module, batch, batch_idx):
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raise KeyboardInterrupt
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trainer = Trainer(callbacks=[InterruptCallback()], default_root_dir=tmp_path, **extra_params)
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with pytest.raises(SystemExit):
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trainer.fit(model)
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assert trainer.interrupted
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