tf.compat.v1.nn.fused_batch_norm

Batch normalization.

tf.compat.v1.nn.fused_batch_norm(
    x, scale, offset, mean=None, variance=None, epsilon=0.001, data_format='NHWC',
    is_training=True, name=None
)

See Source: Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift; S. Ioffe, C. Szegedy.

Args
x	Input Tensor of 4 dimensions.
scale	A Tensor of 1 dimension for scaling.
offset	A Tensor of 1 dimension for bias.
mean	A Tensor of 1 dimension for population mean used for inference.
variance	A Tensor of 1 dimension for population variance used for inference.
epsilon	A small float number added to the variance of x.
data_format	The data format for x. Either "NHWC" (default) or "NCHW".
is_training	A bool value to specify if the operation is used for training or inference.
name	A name for this operation (optional).

Returns
y	A 4D Tensor for the normalized, scaled, offsetted x.
batch_mean	A 1D Tensor for the mean of x.
batch_var	A 1D Tensor for the variance of x.

Raises
ValueError	If mean or variance is not None when is_training is True.