Softmax layer
Softmax class
keras.layers.Softmax(axis=-1, **kwargs)
Softmax activation layer.
Formula:
exp_x = exp(x - max(x))
f(x) = exp_x / sum(exp_x)
Example
>>> softmax_layer = keras.layers.Softmax()
>>> input = np.array([1.0, 2.0, 1.0])
>>> result = softmax_layer(input)
>>> result
[0.21194157, 0.5761169, 0.21194157]
Arguments
- axis: Integer, or list of Integers, axis along which the softmax normalization is applied.
- **kwargs: Base layer keyword arguments, such as
nameanddtype.
Call arguments
- inputs: The inputs (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.