Computes log softmax activations.
tf.compat.v2.math.log_softmax(
logits, axis=None, name=None
)
For each batch i and class j we have
logsoftmax = logits - log(reduce_sum(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 as logits. Same 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/r1.15/api_docs/python/tf/compat/v2/math/log_softmax