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

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.

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

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
)