tf.keras.callbacks.LearningRateScheduler

Learning rate scheduler.

Inherits From: Callback

tf.keras.callbacks.LearningRateScheduler(
    schedule, verbose=0
)

Used in the notebooks

Used in the tutorials
Distributed training with Keras TensorBoard Scalars: Logging training metrics in Keras

At the beginning of every epoch, this callback gets the updated learning rate value from schedule function provided at __init__, with the current epoch and current learning rate, and applies the updated learning rate on the optimizer.

Args
`schedule`	A function that takes an epoch index (integer, indexed from 0) and current learning rate (float) as inputs and returns a new learning rate as output (float).
`verbose`	Integer. 0: quiet, 1: log update messages.

Example:

# This function keeps the initial learning rate for the first ten epochs
# and decreases it exponentially after that.
def scheduler(epoch, lr):
    if epoch < 10:
        return lr
    else:
        return lr * ops.exp(-0.1)

model = keras.models.Sequential([keras.layers.Dense(10)])
model.compile(keras.optimizers.SGD(), loss='mse')
round(model.optimizer.learning_rate, 5)
0.01

callback = keras.callbacks.LearningRateScheduler(scheduler)
history = model.fit(np.arange(100).reshape(5, 20), np.zeros(5),
                    epochs=15, callbacks=[callback], verbose=0)
round(model.optimizer.learning_rate, 5)
0.00607

Attributes
`model`

Attributes

model

Methods

`on_batch_begin`

View source

on_batch_begin(
    batch, logs=None
)

A backwards compatibility alias for on_train_batch_begin.

`on_batch_end`

View source

on_batch_end(
    batch, logs=None
)

A backwards compatibility alias for on_train_batch_end.

`on_epoch_begin`

View source

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.

Args
`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`

View source

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.

Args
`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`

View source

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 Model is set to N, this method will only be called every N batches.

Args
`batch`	Integer, index of batch within the current epoch.
`logs`	Dict. Currently no data is passed to this argument for this method but that may change in the future.

`on_predict_batch_end`

View source

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 Model is set to N, this method will only be called every N batches.

Args
`batch`	Integer, index of batch within the current epoch.
`logs`	Dict. Aggregated metric results up until this batch.

`on_predict_begin`

View source

on_predict_begin(
    logs=None
)

Called at the beginning of prediction.

Subclasses should override for any actions to run.

Args
`logs`	Dict. Currently no data is passed to this argument for this method but that may change in the future.

`on_predict_end`

View source

on_predict_end(
    logs=None
)

Called at the end of prediction.

Subclasses should override for any actions to run.

Args
`logs`	Dict. Currently no data is passed to this argument for this method but that may change in the future.

`on_test_batch_begin`

View source

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 Model is set to N, this method will only be called every N batches.

Args
`batch`	Integer, index of batch within the current epoch.
`logs`	Dict. Currently no data is passed to this argument for this method but that may change in the future.

`on_test_batch_end`

View source

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 Model is set to N, this method will only be called every N batches.

Args
`batch`	Integer, index of batch within the current epoch.
`logs`	Dict. Aggregated metric results up until this batch.

`on_test_begin`

View source

on_test_begin(
    logs=None
)

Called at the beginning of evaluation or validation.

Subclasses should override for any actions to run.

Args
`logs`	Dict. Currently no data is passed to this argument for this method but that may change in the future.

`on_test_end`

View source

on_test_end(
    logs=None
)

Called at the end of evaluation or validation.

Subclasses should override for any actions to run.

Args
`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`

View source

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 Model is set to N, this method will only be called every N batches.

Args
`batch`	Integer, index of batch within the current epoch.
`logs`	Dict. Currently no data is passed to this argument for this method but that may change in the future.

`on_train_batch_end`

View source

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 Model is set to N, this method will only be called every N batches.

Args
`batch`	Integer, index of batch within the current epoch.
`logs`	Dict. Aggregated metric results up until this batch.

`on_train_begin`

View source

on_train_begin(
    logs=None
)

Called at the beginning of training.

Subclasses should override for any actions to run.

Args
`logs`	Dict. Currently no data is passed to this argument for this method but that may change in the future.

`on_train_end`

View source

on_train_end(
    logs=None
)

Called at the end of training.

Subclasses should override for any actions to run.

Args
`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`

View source

set_model(
    model
)

`set_params`

View source

set_params(
    params
)

tf.keras.callbacks.LearningRateScheduler

Used in the notebooks

Args

Example:

Attributes

Methods

on_batch_begin

on_batch_end

on_epoch_begin

on_epoch_end

on_predict_batch_begin

on_predict_batch_end

on_predict_begin

on_predict_end

on_test_batch_begin

on_test_batch_end

on_test_begin

on_test_end

on_train_batch_begin

on_train_batch_end

on_train_begin

on_train_end

set_model

set_params

`on_batch_begin`

`on_batch_end`

`on_epoch_begin`

`on_epoch_end`

`on_predict_batch_begin`

`on_predict_batch_end`

`on_predict_begin`

`on_predict_end`

`on_test_batch_begin`

`on_test_batch_end`

`on_test_begin`

`on_test_end`

`on_train_batch_begin`

`on_train_batch_end`

`on_train_begin`

`on_train_end`

`set_model`

`set_params`