Python on_train_epoch_start Exemples

Langage de programmation: Python

Espace de nommage/Pack: unittest.mock.call

Méthode/Fonction: on_train_epoch_start

Exemples au hotexamples.com: 2

Python on_train_epoch_start - 2 exemples trouvés. Ce sont les exemples réels les mieux notés de unittest.mock.call.on_train_epoch_start extraits de projets open source. Vous pouvez noter les exemples pour nous aider à en améliorer la qualité.

Exemple #1

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def test_trainer_callback_hook_system_fit(_, tmpdir): """Test the callback hook system for fit.""" model = BoringModel() callback_mock = MagicMock() trainer = Trainer( default_root_dir=tmpdir, callbacks=[callback_mock], max_epochs=1, limit_val_batches=1, limit_train_batches=3, progress_bar_refresh_rate=0, ) # check that only the to calls exists assert trainer.callbacks[0] == callback_mock assert callback_mock.method_calls == [ call.on_init_start(trainer), call.on_init_end(trainer), ] # fit model trainer.fit(model) assert callback_mock.method_calls == [ call.on_init_start(trainer), call.on_init_end(trainer), call.on_before_accelerator_backend_setup(trainer, model), call.setup(trainer, model, 'fit'), call.on_configure_sharded_model(trainer, model), call.on_fit_start(trainer, model), call.on_pretrain_routine_start(trainer, model), call.on_pretrain_routine_end(trainer, model), call.on_sanity_check_start(trainer, model), call.on_validation_start(trainer, model), call.on_epoch_start(trainer, model), call.on_validation_epoch_start(trainer, model), call.on_validation_batch_start(trainer, model, ANY, 0, 0), call.on_validation_batch_end(trainer, model, ANY, ANY, 0, 0), call.on_validation_epoch_end(trainer, model), call.on_epoch_end(trainer, model), call.on_validation_end(trainer, model), call.on_sanity_check_end(trainer, model), call.on_train_start(trainer, model), call.on_epoch_start(trainer, model), call.on_train_epoch_start(trainer, model), call.on_batch_start(trainer, model), call.on_train_batch_start(trainer, model, ANY, 0, 0), call.on_before_zero_grad(trainer, model, trainer.optimizers[0]), call.on_after_backward(trainer, model), call.on_train_batch_end(trainer, model, ANY, ANY, 0, 0), call.on_batch_end(trainer, model), call.on_batch_start(trainer, model), call.on_train_batch_start(trainer, model, ANY, 1, 0), call.on_before_zero_grad(trainer, model, trainer.optimizers[0]), call.on_after_backward(trainer, model), call.on_train_batch_end(trainer, model, ANY, ANY, 1, 0), call.on_batch_end(trainer, model), call.on_batch_start(trainer, model), call.on_train_batch_start(trainer, model, ANY, 2, 0), call.on_before_zero_grad(trainer, model, trainer.optimizers[0]), call.on_after_backward(trainer, model), call.on_train_batch_end(trainer, model, ANY, ANY, 2, 0), call.on_batch_end(trainer, model), call.on_train_epoch_end(trainer, model, ANY), call.on_epoch_end(trainer, model), call.on_validation_start(trainer, model), call.on_epoch_start(trainer, model), call.on_validation_epoch_start(trainer, model), call.on_validation_batch_start(trainer, model, ANY, 0, 0), call.on_validation_batch_end(trainer, model, ANY, ANY, 0, 0), call.on_validation_epoch_end(trainer, model), call.on_epoch_end(trainer, model), call.on_validation_end(trainer, model), call.on_save_checkpoint( trainer, model), # should take ANY but we are inspecting signature for BC call.on_train_end(trainer, model), call.on_fit_end(trainer, model), call.teardown(trainer, model, 'fit'), ]

Exemple #2

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Fichier : test_callbacks.py Projet : texchi2/pytorch-lightning

def test_trainer_callback_system(torch_save): """Test the callback system.""" model = BoringModel() callback_mock = MagicMock() trainer_options = dict( callbacks=[callback_mock], max_epochs=1, limit_val_batches=1, limit_train_batches=3, limit_test_batches=2, progress_bar_refresh_rate=0, ) # no call yet callback_mock.assert_not_called() # fit model trainer = Trainer(**trainer_options) # check that only the to calls exists assert trainer.callbacks[0] == callback_mock assert callback_mock.method_calls == [ call.on_init_start(trainer), call.on_init_end(trainer), ] trainer.fit(model) assert callback_mock.method_calls == [ call.on_init_start(trainer), call.on_init_end(trainer), call.setup(trainer, model, 'fit'), call.on_fit_start(trainer, model), call.on_pretrain_routine_start(trainer, model), call.on_pretrain_routine_end(trainer, model), call.on_sanity_check_start(trainer, model), call.on_validation_start(trainer, model), call.on_validation_epoch_start(trainer, model), call.on_validation_batch_start(trainer, model, ANY, 0, 0), call.on_validation_batch_end(trainer, model, ANY, ANY, 0, 0), call.on_validation_epoch_end(trainer, model), call.on_validation_end(trainer, model), call.on_sanity_check_end(trainer, model), call.on_train_start(trainer, model), call.on_epoch_start(trainer, model), call.on_train_epoch_start(trainer, model), call.on_batch_start(trainer, model), call.on_train_batch_start(trainer, model, ANY, 0, 0), call.on_after_backward(trainer, model), call.on_before_zero_grad(trainer, model, trainer.optimizers[0]), call.on_batch_end(trainer, model), call.on_train_batch_end(trainer, model, ANY, ANY, 0, 0), call.on_batch_start(trainer, model), call.on_train_batch_start(trainer, model, ANY, 1, 0), call.on_after_backward(trainer, model), call.on_before_zero_grad(trainer, model, trainer.optimizers[0]), call.on_batch_end(trainer, model), call.on_train_batch_end(trainer, model, ANY, ANY, 1, 0), call.on_batch_start(trainer, model), call.on_train_batch_start(trainer, model, ANY, 2, 0), call.on_after_backward(trainer, model), call.on_before_zero_grad(trainer, model, trainer.optimizers[0]), call.on_batch_end(trainer, model), call.on_train_batch_end(trainer, model, ANY, ANY, 2, 0), call.on_epoch_end(trainer, model), call.on_train_epoch_end(trainer, model, ANY), call.on_validation_start(trainer, model), call.on_validation_epoch_start(trainer, model), call.on_validation_batch_start(trainer, model, ANY, 0, 0), call.on_validation_batch_end(trainer, model, ANY, ANY, 0, 0), call.on_validation_epoch_end(trainer, model), call.on_validation_end(trainer, model), call.on_save_checkpoint(trainer, model), call.on_train_end(trainer, model), call.on_fit_end(trainer, model), call.teardown(trainer, model, 'fit'), ] callback_mock.reset_mock() trainer = Trainer(**trainer_options) trainer.test(model) assert callback_mock.method_calls == [ call.on_init_start(trainer), call.on_init_end(trainer), call.setup(trainer, model, 'test'), call.on_fit_start(trainer, model), call.on_test_start(trainer, model), call.on_test_epoch_start(trainer, model), call.on_test_batch_start(trainer, model, ANY, 0, 0), call.on_test_batch_end(trainer, model, ANY, ANY, 0, 0), call.on_test_batch_start(trainer, model, ANY, 1, 0), call.on_test_batch_end(trainer, model, ANY, ANY, 1, 0), call.on_test_epoch_end(trainer, model), call.on_test_end(trainer, model), call.on_fit_end(trainer, model), call.teardown(trainer, model, 'fit'), call.teardown(trainer, model, 'test'), ]