45 lines
1.3 KiB
Python
45 lines
1.3 KiB
Python
"""
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Tests to ensure that the training loop works with a dict
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"""
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from pytorch_lightning import Trainer
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from tests.base.model_template import EvalModelTemplate
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import os
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def test_training_step_scalar(tmpdir):
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"""
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Tests that only training_step can be used
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"""
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os.environ['PL_DEV_DEBUG'] = '1'
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model = EvalModelTemplate()
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model.validation_step = None
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model.test_step = None
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model.training_step = model.training_step_result_obj_dp
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model.training_step_end = None
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model.training_epoch_end = None
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model.validation_step = model.validation_step_result_obj_dp
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model.validation_step_end = None
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model.validation_epoch_end = None
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model.test_dataloader = None
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trainer = Trainer(
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default_root_dir=tmpdir,
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limit_train_batches=2,
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limit_val_batches=2,
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max_epochs=2,
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row_log_interval=1,
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weights_summary=None,
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)
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trainer.fit(model)
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# epoch 0
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assert trainer.dev_debugger.logged_metrics[0]['global_step'] == 0
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assert trainer.dev_debugger.logged_metrics[1]['global_step'] == 1
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assert trainer.dev_debugger.logged_metrics[2]['global_step'] == 1
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# epoch 1
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assert trainer.dev_debugger.logged_metrics[3]['global_step'] == 2
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assert trainer.dev_debugger.logged_metrics[4]['global_step'] == 3
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assert trainer.dev_debugger.logged_metrics[5]['global_step'] == 3
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