» 케라스 API / Layers API / Activation layers / Softmax layer

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. Defaults to None.

Returns

softmaxed output with the same shape as inputs.