tf.compat.v1.math.softmax
Computes softmax activations. (deprecated arguments)
tf.compat.v1.math.softmax(
logits, axis=None, name=None, dim=None
)
This function performs the equivalent of
softmax = tf.exp(logits) / tf.reduce_sum(tf.exp(logits), axis)
See: https://en.wikipedia.org/wiki/Softmax_function
Example usage:
tf.nn.softmax([-1, 0., 1.])
<tf.Tensor: shape=(3,), dtype=float32,
numpy=array([0.09003057, 0.24472848, 0.66524094], dtype=float32)>
| Args | |
|---|---|
logits |
A non-empty Tensor, or an object whose type has a registered Tensor conversion function. Must be one of the following types: half,float32, float64. See also convert_to_tensor |
axis |
The dimension softmax would be performed on. The default is -1 which indicates the last dimension. |
name |
A name for the operation (optional). |
dim |
Deprecated alias for axis. |
| 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. |
TypeError |
If no conversion function is registered for logits to Tensor. |
RuntimeError |
If a registered conversion function returns an invalid value. |
© 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/compat/v1/math/softmax