tf.nn.softmax
Computes softmax activations.
tf.nn.softmax(
logits, axis=None, name=None
)
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. |
© 2020 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/versions/r2.3/api_docs/python/tf/nn/softmax