Python keras.callbacks.BaseLogger() Examples
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code examples of keras.callbacks.BaseLogger().
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Example #1
| Source File: models.py From deep_qa with Apache License 2.0 | 4 votes |
|
def _prepare_callbacks(self,
callbacks: List[Callback],
val_ins: List[numpy.array],
epochs: int,
batch_size: int,
num_train_samples: int,
callback_metrics: List[str],
do_validation: bool,
verbose: int):
"""
Sets up Keras callbacks to perform various monitoring functions during training.
"""
self.history = History() # pylint: disable=attribute-defined-outside-init
callbacks = [BaseLogger()] + (callbacks or []) + [self.history]
if verbose:
callbacks += [ProgbarLogger()]
callbacks = CallbackList(callbacks)
# it's possible to callback a different model than self
# (used by Sequential models).
if hasattr(self, 'callback_model') and self.callback_model:
callback_model = self.callback_model
else:
callback_model = self # pylint: disable=redefined-variable-type
callbacks.set_model(callback_model)
callbacks.set_params({
'batch_size': batch_size,
'epochs': epochs,
'samples': num_train_samples,
'verbose': verbose,
'do_validation': do_validation,
'metrics': callback_metrics or [],
})
callbacks.on_train_begin()
callback_model.stop_training = False
for cbk in callbacks:
cbk.validation_data = val_ins
return callbacks, callback_model
