tf.keras.callbacks.ProgbarLogger

Class ProgbarLogger

Inherits From: Callback

Defined in tensorflow/python/keras/callbacks.py.

Callback that prints metrics to stdout.

Arguments:

  • count_mode: One of "steps" or "samples". Whether the progress bar should count samples seen or steps (batches) seen.
  • stateful_metrics: Iterable of string names of metrics that should not be averaged over an epoch. Metrics in this list will be logged as-is. All others will be averaged over time (e.g. loss, etc).

Raises:

  • ValueError: In case of invalid count_mode.

__init__

__init__(
    count_mode='samples',
    stateful_metrics=None
)

Initialize self. See help(type(self)) for accurate signature.

Methods

tf.keras.callbacks.ProgbarLogger.on_batch_begin

on_batch_begin(
    batch,
    logs=None
)

tf.keras.callbacks.ProgbarLogger.on_batch_end

on_batch_end(
    batch,
    logs=None
)

tf.keras.callbacks.ProgbarLogger.on_epoch_begin

on_epoch_begin(
    epoch,
    logs=None
)

tf.keras.callbacks.ProgbarLogger.on_epoch_end

on_epoch_end(
    epoch,
    logs=None
)

tf.keras.callbacks.ProgbarLogger.on_train_batch_begin

on_train_batch_begin(
    batch,
    logs=None
)

tf.keras.callbacks.ProgbarLogger.on_train_batch_end

on_train_batch_end(
    batch,
    logs=None
)

tf.keras.callbacks.ProgbarLogger.on_train_begin

on_train_begin(logs=None)

tf.keras.callbacks.ProgbarLogger.on_train_end

on_train_end(logs=None)

tf.keras.callbacks.ProgbarLogger.set_model

set_model(model)

tf.keras.callbacks.ProgbarLogger.set_params

set_params(params)