tf.nn.softmax
Computes softmax activations.
View aliases
Main aliases
tf.math.softmax
tf.nn.softmax(
logits, axis=None, name=None
)
Used in the notebooks
Used in the guide |
Used in the tutorials |
|
|
Used for multi-class predictions. The sum of all outputs generated by softmax
is 1.
This function performs the equivalent of
softmax = tf.exp(logits) / tf.reduce_sum(tf.exp(logits), axis, keepdims=True)
Example usage:
softmax = tf.nn.softmax([-1, 0., 1.])
softmax
<tf.Tensor: shape=(3,), dtype=float32,
numpy=array([0.09003057, 0.24472848, 0.66524094], dtype=float32)>
sum(softmax)
<tf.Tensor: shape=(), dtype=float32, numpy=1.0>
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 .
|
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Last updated 2024-04-26 UTC.
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