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tf.keras.backend.normalize_batch_in_training

TensorFlow 1 version View source on GitHub

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).