o 2h| @sPddlmZddlmZddlmZedGdddeZeddd Zd S) )ops) keras_export)Mergezkeras.layers.Subtractcs(eZdZdZfddZddZZS)SubtractabPerforms elementwise subtraction. It takes as input a list of tensors of size 2 both of the same shape, and returns a single tensor (inputs[0] - inputs[1]) of same shape. Examples: >>> input_shape = (2, 3, 4) >>> x1 = np.random.rand(*input_shape) >>> x2 = np.random.rand(*input_shape) >>> y = keras.layers.Subtract()([x1, x2]) Usage in a Keras model: >>> input1 = keras.layers.Input(shape=(16,)) >>> x1 = keras.layers.Dense(8, activation='relu')(input1) >>> input2 = keras.layers.Input(shape=(32,)) >>> x2 = keras.layers.Dense(8, activation='relu')(input2) >>> # equivalent to `subtracted = keras.layers.subtract([x1, x2])` >>> subtracted = keras.layers.Subtract()([x1, x2]) >>> out = keras.layers.Dense(4)(subtracted) >>> model = keras.models.Model(inputs=[input1, input2], outputs=out) cs*t|t|dkrtd|dS)NzOA `Subtract` layer should be called on exactly 2 inputs. Received: input_shape=)superbuildlen ValueError)self input_shape __class__\/var/www/html/chatgem/venv/lib/python3.10/site-packages/keras/src/layers/merging/subtract.pyr"s  zSubtract.buildcCs.t|dkr td|t|d|dS)NrzJA `Subtract` layer should be called on exactly 2 inputs. Received: inputs=r)r r rsubtract)r inputsrrr_merge_function*s zSubtract._merge_function)__name__ __module__ __qualname____doc__rr __classcell__rrr rrs rzkeras.layers.subtractcKstdi||S)aFunctional interface to the `keras.layers.Subtract` layer. Args: inputs: A list of input tensors of size 2, each tensor of the same shape. **kwargs: Standard layer keyword arguments. Returns: A tensor as the difference of the inputs. It has the same shape as the inputs. Examples: >>> input_shape = (2, 3, 4) >>> x1 = np.random.rand(*input_shape) >>> x2 = np.random.rand(*input_shape) >>> y = keras.layers.subtract([x1, x2]) Usage in a Keras model: >>> input1 = keras.layers.Input(shape=(16,)) >>> x1 = keras.layers.Dense(8, activation='relu')(input1) >>> input2 = keras.layers.Input(shape=(32,)) >>> x2 = keras.layers.Dense(8, activation='relu')(input2) >>> subtracted = keras.layers.subtract([x1, x2]) >>> out = keras.layers.Dense(4)(subtracted) >>> model = keras.models.Model(inputs=[input1, input2], outputs=out) Nr)r)rkwargsrrrr3srN) keras.srcrkeras.src.api_exportr#keras.src.layers.merging.base_mergerrrrrrrs  ,