tf.nn.fused_batch_norm

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Batch normalization.

tf.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.

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).

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.

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