o ·2úh\ã@sPddlmZddlmZddlmZedƒGdd„deƒƒZedƒdd „ƒZd S) é)Úops)Ú keras_export)ÚMergezkeras.layers.Minimumc@seZdZdZdd„ZdS)ÚMinimuma9Computes elementwise minimum on a list of inputs. It takes as input a list of tensors, all of the same shape, and returns a single tensor (also of the same shape). Examples: >>> input_shape = (2, 3, 4) >>> x1 = np.random.rand(*input_shape) >>> x2 = np.random.rand(*input_shape) >>> y = keras.layers.Minimum()([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 `y = keras.layers.minimum([x1, x2])` >>> y = keras.layers.Minimum()([x1, x2]) >>> out = keras.layers.Dense(4)(y) >>> model = keras.models.Model(inputs=[input1, input2], outputs=out) cCs| tj|¡S)N)Ú_apply_merge_op_and_or_maskrÚminimum)ÚselfÚinputs©r ú[/var/www/html/chatgem/venv/lib/python3.10/site-packages/keras/src/layers/merging/minimum.pyÚ_merge_function!szMinimum._merge_functionN)Ú__name__Ú __module__Ú __qualname__Ú__doc__r r r r r rs rzkeras.layers.minimumcKstdi|¤Ž|ƒS)axFunctional interface to the `keras.layers.Minimum` layer. Args: inputs: A list of input tensors , all of the same shape. **kwargs: Standard layer keyword arguments. Returns: A tensor as the elementwise product of the inputs with 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.minimum([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) >>> y = keras.layers.minimum([x1, x2]) >>> out = keras.layers.Dense(4)(y) >>> model = keras.models.Model(inputs=[input1, input2], outputs=out) Nr )r)r Úkwargsr r r r%srN)Ú keras.srcrÚkeras.src.api_exportrÚ#keras.src.layers.merging.base_mergerrrr r r r Ús