tf.nn.fused_batch_norm( x, scale, offset, mean=None, variance=None, epsilon=0.001, data_format='NHWC', is_training=True, name=None )
See the guide: Neural Network > Normalization
As described in http://arxiv.org/abs/1502.03167.
Tensorof 4 dimensions.
Tensorof 1 dimension for scaling.
Tensorof 1 dimension for bias.
Tensorof 1 dimension for population mean used for inference.
Tensorof 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.
© 2018 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.