tf.keras.layers.Softmax
| View source on GitHub |
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 asinputs. Defaults toNone.
| 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