class_docstr: Generic merge layer for elementwise merge functions.
  
  Used to implement `Sum`, `Average`, etc.
code: def compute_mask(self, inputs, mask=None):
      if mask is None:
          return None
      if not isinstance(mask, (tuple, list)):
          raise ValueError("`mask` should be a list.")
      if not isinstance(inputs, (tuple, list)):
          raise ValueError("`inputs` should be a list.")
      if len(mask) != len(inputs):
          raise ValueError(
              "The lists `inputs` and `mask` "
              "should have the same length."
          )
      if all(m is None for m in mask):
          return None
      masks = [
          array_ops.expand_dims(m, axis=0)
          for m in mask
          if m is not None
      ]
      return backend.all(
          backend.concatenate(masks, axis=0), axis=0, keepdims=False
      )
  
imports: from tensorflow.python.keras import backend
  from tensorflow.python.keras.engine import base_layer_utils
  from tensorflow.python.keras.engine.base_layer import Layer
  from tensorflow.python.keras.utils import tf_utils
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn
label_desc: Use image node_id 7 for calling the _Merge obj's underlying member method code with example usage: obj.compute_mask(inputs, mask) and returns: backend, None, None