class_docstr: Generic merge layer for elementwise merge functions.
  
  Used to implement `Sum`, `Average`, etc.
  
  Args:
      **kwargs: standard layer keyword arguments.
class_docstr_tok: ["Generic","merge","layer","for","elementwise","merge","functions",".","Used","to","implement","`","Sum","`",",","`","Average","`",",","etc",".","Args",":","*","*","kwargs",":","standard","layer","keyword","arguments","."]
code: def compute_output_shape(self, input_shape):
      if input_shape[0] is None:
          output_shape = None
      else:
          output_shape = input_shape[0][1:]
  
      for i in range(1, len(input_shape)):
          if input_shape[i] is None:
              shape = None
          else:
              shape = input_shape[i][1:]
          output_shape = self._compute_elemwise_op_output_shape(
              output_shape, shape
          )
      batch_sizes = {s[0] for s in input_shape if s is not None} - {
          None
      }
      if len(batch_sizes) == 1:
          output_shape = (list(batch_sizes)[0],) + output_shape
      else:
          output_shape = (None,) + output_shape
      return output_shape
  
file_path: keras/keras/layers/merging/base_merge.py
imports: from keras import backend
  from keras import ops
  from keras.backend.common.keras_tensor import KerasTensor
  from keras.layers.layer import Layer
label_desc: Use image node_id 6 for calling the Merge obj's underlying member method code with example usage: obj.compute_output_shape(input_shape) and returns: output_shape