tf.nn.separable

Computes softmax activations.

View aliases

Main aliases

tf.math.softmax

tf.nn.softmax(
    logits, axis=None, name=None
)

Used in the notebooks

Used in the guide	Used in the tutorials
Making new Layers and Models via subclassing Training and evaluation with the built-in methods Introduction to Tensors	Integrated gradients Custom training: walkthrough Simple audio recognition: Recognizing keywords Image classification TensorFlow 2 quickstart for beginners

This function performs the equivalent of

softmax = tf.exp(logits) / tf.reduce_sum(tf.exp(logits), axis)

Args
`logits`	A non-empty `Tensor`. Must be one of the following types: `half`, `float32`, `float64`.
`axis`	The dimension softmax would be performed on. The default is -1 which indicates the last dimension.
`name`	A name for the operation (optional).

Returns
A `Tensor`. Has the same type and shape as `logits`.

Raises
`InvalidArgumentError`	if `logits` is empty or `axis` is beyond the last dimension of `logits`.

TensorFlow

tf

tf.audio

tf.autograph

tf.bitwise

tf.compat

tf.config

tf.data

tf.debugging

tf.distribute

tf.dtypes

tf.errors

tf.estimator

tf.experimental

tf.feature_column

tf.graph_util

tf.image

tf.initializers

tf.io

tf.keras

tf.linalg

tf.lite

tf.lookup

tf.losses

tf.math

tf.metrics

tf.nest

tf.nn

tf.optimizers

tf.quantization

tf.queue

tf.ragged

tf.random

tf.raw_ops

tf.saved_model

tf.sets

tf.signal

tf.sparse

tf.strings

tf.summary

tf.sysconfig

tf.test

tf.tpu

tf.train

tf.version

tf.xla

tf.nn / separable_conv2d

View aliases

Used in the notebooks

Args

Returns

Raises