tf.nn.softmax
tf.nn.softmax
tf.nn.softmax
softmax( logits, dim=-1, name=None )
Defined in tensorflow/python/ops/nn_ops.py
.
See the guides: Layers (contrib) > Higher level ops for building neural network layers, Neural Network > Classification
Computes softmax activations.
For each batch i
and class j
we have
softmax = exp(logits) / reduce_sum(exp(logits), dim)
Args:
-
logits
: A non-emptyTensor
. Must be one of the following types:half
,float32
,float64
. -
dim
: 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 as logits
. Same shape as logits
.
Raises:
-
InvalidArgumentError
: iflogits
is empty ordim
is beyond the last dimension oflogits
.
© 2017 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/nn/softmax