tf.keras.layers.Softmax
Softmax activation function.
Inherits From: Layer
, Module
tf.keras.layers.Softmax(
axis=-1, **kwargs
)
Example without mask:
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.
|
Output shape |
Same shape as the input.
|
Args |
axis
|
Integer, or list of Integers, axis along which the softmax
normalization is applied.
|
Call arguments |
inputs
|
The inputs, or logits to the softmax layer.
|
mask
|
A boolean mask of the same shape as inputs . Defaults to None . The
mask specifies 1 to keep and 0 to mask.
|
Returns |
softmaxed output with the same shape as inputs .
|
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Last updated 2022-10-27 UTC.
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