tf.nn.batch_normalization

TensorFlow 1 version

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Adds bias to value.

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.nn.bias_add

tf.nn.bias_add(
    value, bias, data_format=None, name=None
)

This is (mostly) a special case of tf.add where bias is restricted to 1-D. Broadcasting is supported, so value may have any number of dimensions. Unlike tf.add, the type of bias is allowed to differ from value in the case where both types are quantized.

Args
`value`	A `Tensor` with type `float`, `double`, `int64`, `int32`, `uint8`, `int16`, `int8`, `complex64`, or `complex128`.
`bias`	A 1-D `Tensor` with size matching the channel dimension of `value`. Must be the same type as `value` unless `value` is a quantized type, in which case a different quantized type may be used.
`data_format`	A string. 'N...C' and 'NC...' are supported. If `None` (the default) is specified then 'N..C' is assumed.
`name`	A name for the operation (optional).

Returns
A `Tensor` with the same type as `value`.

Raises
ValueError if data format is unrecognized, if `value` has less than two dimensions when `data_format` is 'N..C'/`None` or `value` has less then three dimensions when `data_format` is `NC..`, if `bias` does not have exactly one dimension (is a vector), or if the size of `bias` does not match the size of the channel dimension of `value`.

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tf.nn / batch_normalization

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Args

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