Unpacks user-provided data tuple.

Used in the notebooks

Used in the guide

This is a convenience utility to be used when overriding Model.train_step, Model.test_step, or Model.predict_step. This utility makes it easy to support data of the form (x,), (x, y), or (x, y, sample_weight).

Standalone usage:

features_batch = tf.ones((10, 5))
labels_batch = tf.zeros((10, 5))
data = (features_batch, labels_batch)
# `y` and `sample_weight` will default to `None` if not provided.
x, y, sample_weight = tf.keras.utils.unpack_x_y_sample_weight(data)
sample_weight is None

Example in overridden Model.train_step:

class MyModel(tf.keras.Model):

  def train_step(self, data):
    # If `sample_weight` is not provided, all samples will be weighted
    # equally.
    x, y, sample_weight = tf.keras.utils.unpack_