seqgra.learner.tensorflow.kerascallback module¶
- class LastEpochCallback(output_dir: str)[source]¶
Bases:
tensorflow.python.keras.callbacks.Callback
- on_batch_begin(batch, logs=None)¶
A backwards compatibility alias for on_train_batch_begin.
- on_batch_end(batch, logs=None)¶
A backwards compatibility alias for on_train_batch_end.
- on_epoch_begin(epoch, logs=None)¶
Called at the start of an epoch.
Subclasses should override for any actions to run. This function should only be called during TRAIN mode.
- Parameters
epoch – Integer, index of epoch.
logs – Dict. Currently no data is passed to this argument for this method but that may change in the future.
- on_epoch_end(epoch, logs=None)[source]¶
Called at the end of an epoch.
Subclasses should override for any actions to run. This function should only be called during TRAIN mode.
- Parameters
epoch – Integer, index of epoch.
logs –
- Dict, metric results for this training epoch, and for the
validation epoch if validation is performed. Validation result keys are prefixed with val_. For training epoch, the values of the
- Model’s metrics are returned. Example`{‘loss’: 0.2, ‘accuracy’:
0.7}`.
- on_predict_batch_begin(batch, logs=None)¶
Called at the beginning of a batch in predict methods.
Subclasses should override for any actions to run.
Note that if the steps_per_execution argument to compile in tf.keras.Model is set to N, this method will only be called every N batches.
- Parameters
batch – Integer, index of batch within the current epoch.
logs – Dict, contains the return value of model.predict_step, it typically returns a dict with a key ‘outputs’ containing the model’s outputs.
- on_predict_batch_end(batch, logs=None)¶
Called at the end of a batch in predict methods.
Subclasses should override for any actions to run.
Note that if the steps_per_execution argument to compile in tf.keras.Model is set to N, this method will only be called every N batches.
- Parameters
batch – Integer, index of batch within the current epoch.
logs – Dict. Aggregated metric results up until this batch.
- on_predict_begin(logs=None)¶
Called at the beginning of prediction.
Subclasses should override for any actions to run.
- Parameters
logs – Dict. Currently no data is passed to this argument for this method but that may change in the future.
- on_predict_end(logs=None)¶
Called at the end of prediction.
Subclasses should override for any actions to run.
- Parameters
logs – Dict. Currently no data is passed to this argument for this method but that may change in the future.
- on_test_batch_begin(batch, logs=None)¶
Called at the beginning of a batch in evaluate methods.
Also called at the beginning of a validation batch in the fit methods, if validation data is provided.
Subclasses should override for any actions to run.
Note that if the steps_per_execution argument to compile in tf.keras.Model is set to N, this method will only be called every N batches.
- Parameters
batch – Integer, index of batch within the current epoch.
logs – Dict, contains the return value of model.test_step. Typically, the values of the Model’s metrics are returned. Example: {‘loss’: 0.2, ‘accuracy’: 0.7}.
- on_test_batch_end(batch, logs=None)¶
Called at the end of a batch in evaluate methods.
Also called at the end of a validation batch in the fit methods, if validation data is provided.
Subclasses should override for any actions to run.
Note that if the steps_per_execution argument to compile in tf.keras.Model is set to N, this method will only be called every N batches.
- Parameters
batch – Integer, index of batch within the current epoch.
logs – Dict. Aggregated metric results up until this batch.
- on_test_begin(logs=None)¶
Called at the beginning of evaluation or validation.
Subclasses should override for any actions to run.
- Parameters
logs – Dict. Currently no data is passed to this argument for this method but that may change in the future.
- on_test_end(logs=None)¶
Called at the end of evaluation or validation.
Subclasses should override for any actions to run.
- Parameters
logs – Dict. Currently the output of the last call to on_test_batch_end() is passed to this argument for this method but that may change in the future.
- on_train_batch_begin(batch, logs=None)¶
Called at the beginning of a training batch in fit methods.
Subclasses should override for any actions to run.
Note that if the steps_per_execution argument to compile in tf.keras.Model is set to N, this method will only be called every N batches.
- Parameters
batch – Integer, index of batch within the current epoch.
logs – Dict, contains the return value of model.train_step. Typically, the values of the Model’s metrics are returned. Example: {‘loss’: 0.2, ‘accuracy’: 0.7}.
- on_train_batch_end(batch, logs=None)¶
Called at the end of a training batch in fit methods.
Subclasses should override for any actions to run.
Note that if the steps_per_execution argument to compile in tf.keras.Model is set to N, this method will only be called every N batches.
- Parameters
batch – Integer, index of batch within the current epoch.
logs – Dict. Aggregated metric results up until this batch.
- on_train_begin(logs=None)¶
Called at the beginning of training.
Subclasses should override for any actions to run.
- Parameters
logs – Dict. Currently no data is passed to this argument for this method but that may change in the future.
- on_train_end(logs=None)¶
Called at the end of training.
Subclasses should override for any actions to run.
- Parameters
logs – Dict. Currently the output of the last call to on_epoch_end() is passed to this argument for this method but that may change in the future.
- set_model(model)¶
- set_params(params)¶