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Softmax activation function.
tf.keras.layers.Softmax( axis=-1, **kwargs )
inp = np.asarray([1., 2., 1.]) layer = tf.keras.layers.Softmax() layer(inp).numpy() array([0.21194157, 0.5761169 , 0.21194157], dtype=float32) mask = np.asarray([True, False, True], dtype=bool) layer(inp, mask).numpy() array([0.5, 0. , 0.5], dtype=float32)
Arbitrary. Use the keyword argument input_shape
(tuple of integers, does not include the samples axis) when using this layer as the first layer in a model.
Same shape as the input.
Arguments | |
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axis | Integer, or list of Integers, axis along which the softmax normalization is applied. |
inputs
: The inputs, or logits to the softmax layer.mask
: A boolean mask of the same shape as inputs
. Defaults to None
.Returns | |
---|---|
softmaxed output with the same shape as inputs . |
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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/keras/layers/Softmax