tf.compat.v1.nn.batch_norm_with_global_normalization

Batch normalization.

tf.compat.v1.nn.batch_norm_with_global_normalization(
    t=None, m=None, v=None, beta=None, gamma=None, variance_epsilon=None,
    scale_after_normalization=None, name=None, input=None, mean=None, variance=None
)

This op is deprecated. See tf.nn.batch_normalization.

Args
t	A 4D input Tensor.
m	A 1D mean Tensor with size matching the last dimension of t. This is the first output from tf.nn.moments, or a saved moving average thereof.
v	A 1D variance Tensor with size matching the last dimension of t. This is the second output from tf.nn.moments, or a saved moving average thereof.
beta	A 1D beta Tensor with size matching the last dimension of t. An offset to be added to the normalized tensor.
gamma	A 1D gamma Tensor with size matching the last dimension of t. If "scale_after_normalization" is true, this tensor will be multiplied with the normalized tensor.
variance_epsilon	A small float number to avoid dividing by 0.
scale_after_normalization	A bool indicating whether the resulted tensor needs to be multiplied with gamma.
name	A name for this operation (optional).
input	Alias for t.
mean	Alias for m.
variance	Alias for v.

Returns
A batch-normalized t.

References:

Batch Normalization - Accelerating Deep Network Training by Reducing Internal Covariate Shift: Ioffe et al., 2015 (pdf)