tf.nn.batch_norm_with_global_normalization

Batch normalization.

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

Args
input A 4D input Tensor.
mean 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.
variance 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).
Returns
A batch-normalized t.

References:

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

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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/nn/batch_norm_with_global_normalization