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 | |
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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 | |
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A Tensor . Has the same type and shape as logits . |
Raises | |
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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/r2.4/api_docs/python/tf/compat/v1/math/softmax