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. |