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)

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.

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. The mask specifies 1 to keep and 0 to mask. Defaults to None.

Returns
Softmaxed output with the same shape as inputs.