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tf.keras.layers.Softmax
Softmax activation function.
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)
Input shape:
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.
| Arguments | |
|---|---|
| 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.
| Returns | |
|---|---|
| softmaxed output with the same shape as inputs. | 
© 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/keras/layers/Softmax