Softmax layer
Softmax class
tf_keras.layers.Softmax(axis=-1, **kwargs)
Softmax activation function.
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. The mask specifies 1 to keep and 0 to mask. Defaults toNone.
Returns
Softmaxed output with the same shape as inputs.