tf.keras.callbacks.CSVLogger

TensorFlow 1 version View source on GitHub

Callback that streams epoch results to a csv file.

Inherits From: Callback

tf.keras.callbacks.CSVLogger(
    filename, separator=',', append=False
)

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])

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,

Methods

on_batch_begin

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on_batch_begin(
    batch, logs=None
)

A backwards compatibility alias for on_train_batch_begin.

on_batch_end

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on_batch_end(
    batch, logs=None
)

A backwards compatibility alias for on_train_batch_end.

on_epoch_begin

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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.

Arguments
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

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on_epoch_end(
    epoch, logs=None
)

Called at the end of an epoch.

Subclasses should override for any actions to run. This function should only be called during TRAIN mode.

Arguments
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_.

on_predict_batch_begin

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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.

Arguments
batch integer, index of batch within the current epoch.
logs dict. Has keys batch and size representing the current batch number and the size of the batch.

on_predict_batch_end

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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.

Arguments
batch integer, index of batch within the current epoch.
logs dict. Metric results for this batch.

on_predict_begin

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on_predict_begin(
    logs=None
)

Called at the beginning of prediction.

Subclasses should override for any actions to run.

Arguments
logs dict. Currently no data is passed to this argument for this method but that may change in the future.

on_predict_end

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on_predict_end(
    logs=None
)

Called at the end of prediction.

Subclasses should override for any actions to run.

Arguments
logs dict. Currently no data is passed to this argument for this method but that may change in the future.

on_test_batch_begin

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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.

Arguments
batch integer, index of batch within the current epoch.
logs dict. Has keys batch and size representing the current batch number and the size of the batch.

on_test_batch_end

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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.

Arguments
batch integer, index of batch within the current epoch.
logs dict. Metric results for this batch.

on_test_begin

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on_test_begin(
    logs=None
)

Called at the beginning of evaluation or validation.

Subclasses should override for any actions to run.

Arguments
logs dict. Currently no data is passed to this argument for this method but that may change in the future.

on_test_end

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on_test_end(
    logs=None
)

Called at the end of evaluation or validation.

Subclasses should override for any actions to run.

Arguments
logs dict. Currently no data is passed to this argument for this method but that may change in the future.

on_train_batch_begin

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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.

Arguments
batch integer, index of batch within the current epoch.
logs dict. Has keys batch and size representing the current batch number and the size of the batch.

on_train_batch_end

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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.

Arguments
batch integer, index of batch within the current epoch.
logs dict. Metric results for this batch.

on_train_begin

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on_train_begin(
    logs=None
)

Called at the beginning of training.

Subclasses should override for any actions to run.

Arguments
logs dict. Currently no data is passed to this argument for this method but that may change in the future.

on_train_end

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on_train_end(
    logs=None
)

Called at the end of training.

Subclasses should override for any actions to run.

Arguments
logs dict. Currently no data is passed to this argument for this method but that may change in the future.

set_model

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set_model(
    model
)

set_params

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set_params(
    params
)