tf.nn.batch_norm_with_global_normalization(
t,
m,
v,
beta,
gamma,
variance_epsilon,
scale_after_normalization,
name=None
)
Defined in tensorflow/python/ops/nn_impl.py.
Batch normalization.
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).
Returns:
A batch-normalized t.