63 lines
2.0 KiB
Python
63 lines
2.0 KiB
Python
import os
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from pytorch_lightning import Trainer, seed_everything
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from tests.base import EvalModelTemplate
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def test_mc_called_on_fastdevrun(tmpdir):
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seed_everything(1234)
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os.environ['PL_DEV_DEBUG'] = '1'
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train_val_step_model = EvalModelTemplate()
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# fast dev run = called once
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# train loop only, dict, eval result
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trainer = Trainer(fast_dev_run=True)
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trainer.fit(train_val_step_model)
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# checkpoint should have been called once with fast dev run
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assert len(trainer.dev_debugger.checkpoint_callback_history) == 1
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# -----------------------
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# also called once with no val step
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# -----------------------
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train_step_only_model = EvalModelTemplate()
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train_step_only_model.validation_step = None
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# fast dev run = called once
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# train loop only, dict, eval result
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trainer = Trainer(fast_dev_run=True)
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trainer.fit(train_step_only_model)
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# make sure only training step was called
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assert train_step_only_model.training_step_called
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assert not train_step_only_model.validation_step_called
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assert not train_step_only_model.test_step_called
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# checkpoint should have been called once with fast dev run
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assert len(trainer.dev_debugger.checkpoint_callback_history) == 1
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def test_mc_called(tmpdir):
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seed_everything(1234)
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os.environ['PL_DEV_DEBUG'] = '1'
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# -----------------
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# TRAIN LOOP ONLY
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# -----------------
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train_step_only_model = EvalModelTemplate()
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train_step_only_model.validation_step = None
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# no callback
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trainer = Trainer(max_epochs=3, checkpoint_callback=False)
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trainer.fit(train_step_only_model)
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assert len(trainer.dev_debugger.checkpoint_callback_history) == 0
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# -----------------
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# TRAIN + VAL LOOP ONLY
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# -----------------
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val_train_model = EvalModelTemplate()
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# no callback
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trainer = Trainer(max_epochs=3, checkpoint_callback=False)
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trainer.fit(val_train_model)
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assert len(trainer.dev_debugger.checkpoint_callback_history) == 0
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