:|h| pddlmZddlmZddlmZedGddeZeddZy ) )ops) keras_export)Mergezkeras.layers.Subtractc(eZdZdZfdZdZxZS)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) c\t||t|dk7rtd|y)NzOA `Subtract` layer should be called on exactly 2 inputs. Received: input_shape=)superbuildlen ValueError)self input_shape __class__s `/var/www/html/test/engine/venv/lib/python3.12/site-packages/keras/src/layers/merging/subtract.pyr zSubtract.build"s=  k" { q ))4 7  !crt|dk7rtd|tj|d|dS)Nr zJA `Subtract` layer should be called on exactly 2 inputs. Received: inputs=r)r r rsubtract)rinputss r_merge_functionzSubtract._merge_function*sE v;! $$*8- ||F1Ivay11r)__name__ __module__ __qualname____doc__r r __classcell__)rs@rrrs42rrzkeras.layers.subtractc $tdi||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) )r)rkwargss rrr3s> 8 f f %%rN) keras.srcrkeras.src.api_exportr#keras.src.layers.merging.base_mergerrrrrrr#sJ-5%&)2u)2')2X%&&'&r