tf.keras.backend.normalize_batch_in_training

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Computes mean and std for batch then apply batch_normalization on batch.

tf.keras.backend.normalize_batch_in_training(
    x, gamma, beta, reduction_axes, epsilon=0.001
)

Arguments:

• x: Input tensor or variable.
• gamma: Tensor by which to scale the input.
• beta: Tensor with which to center the input.
• reduction_axes: iterable of integers, axes over which to normalize.
• epsilon: Fuzz factor.

Returns:

A tuple length of 3, (normalized_tensor, mean, variance).