tf.raw_ops.BatchNormWithGlobalNormalizationGrad

Gradients for batch normalization.

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.raw_ops.BatchNormWithGlobalNormalizationGrad

tf.raw_ops.BatchNormWithGlobalNormalizationGrad(
    t, m, v, gamma, backprop, variance_epsilon, scale_after_normalization, name=None
)

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

Args
t	A Tensor. Must be one of the following types: float32, float64, int32, uint8, int16, int8, complex64, int64, qint8, quint8, qint32, bfloat16, uint16, complex128, half, uint32, uint64. A 4D input Tensor.
m	A Tensor. Must have the same type as t. 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 Tensor. Must have the same type as t. 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.
gamma	A Tensor. Must have the same type as t. 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.
backprop	A Tensor. Must have the same type as t. 4D backprop Tensor.
variance_epsilon	A float. A small float number to avoid dividing by 0.
scale_after_normalization	A bool. A bool indicating whether the resulted tensor needs to be multiplied with gamma.
name	A name for the operation (optional).

Returns
A tuple of Tensor objects (dx, dm, dv, db, dg).
dx	A Tensor. Has the same type as t.
dm	A Tensor. Has the same type as t.
dv	A Tensor. Has the same type as t.
db	A Tensor. Has the same type as t.
dg	A Tensor. Has the same type as t.