tf.keras.callbacks.CSVLogger

Class CSVLogger

Inherits From: Callback

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

Callback that streams epoch results to a csv file.

Supports all values that can be represented as a string, including 1D iterables such as np.ndarray.

Example:

csv_logger = CSVLogger('training.log')
model.fit(X_train, Y_train, callbacks=[csv_logger])

Arguments:

• filename: filename of the csv file, e.g. 'run/log.csv'.
• separator: string used to separate elements in the csv file.
• append: True: append if file exists (useful for continuing training). False: overwrite existing file,

__init__

__init__(
    filename,
    separator=',',
    append=False
)

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

Methods

tf.keras.callbacks.CSVLogger.on_batch_begin

on_batch_begin(
    batch,
    logs=None
)

tf.keras.callbacks.CSVLogger.on_batch_end

on_batch_end(
    batch,
    logs=None
)

tf.keras.callbacks.CSVLogger.on_epoch_begin

on_epoch_begin(
    epoch,
    logs=None
)

tf.keras.callbacks.CSVLogger.on_epoch_end

on_epoch_end(
    epoch,
    logs=None
)

tf.keras.callbacks.CSVLogger.on_train_batch_begin

on_train_batch_begin(
    batch,
    logs=None
)

tf.keras.callbacks.CSVLogger.on_train_batch_end

on_train_batch_end(
    batch,
    logs=None
)

tf.keras.callbacks.CSVLogger.on_train_begin

on_train_begin(logs=None)

tf.keras.callbacks.CSVLogger.on_train_end

on_train_end(logs=None)

tf.keras.callbacks.CSVLogger.set_model

set_model(model)

tf.keras.callbacks.CSVLogger.set_params

set_params(params)