tf.nn.normalize

Computes rectified linear: max(features, 0).

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Compat aliases for migration

tf.compat.v1.nn.relu

tf.nn.relu(
    features, name=None
)

Used in the notebooks

Used in the guide	Used in the tutorials
Introduction to modules, layers, and models Making new Layers and Models via subclassing Masking and padding with Keras	Custom layers Image captioning with visual attention Generating Images with BigBiGAN Examining the TensorFlow Graph

See: https://en.wikipedia.org/wiki/Rectifier_(neural_networks) Example usage:

>>> tf.nn.relu([-2., 0., -0., 3.]).numpy()
array([ 0.,  0., -0.,  3.], dtype=float32)

Args
`features`	A `Tensor`. Must be one of the following types: `float32`, `float64`, `int32`, `uint8`, `int16`, `int8`, `int64`, `bfloat16`, `uint16`, `half`, `uint32`, `uint64`, `qint8`.
`name`	A name for the operation (optional).

Returns
A `Tensor`. Has the same type as `features`.

TensorFlow

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tf.nn / normalize_moments

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Used in the notebooks

Args

Returns