class_docstr: Used to create the input layer(s) for a Block.
  
  The most typical use case combines multiple inputs from previous layers into
  a single Tensor, by operations such as sum, depthwise concat, projection, and
  padding operations. Some blocks (such as NASNet) takes 2 Tensors as
  inputs, so we cannot make all Reducers output only one Tensor.
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docstr: Combines inputs to produce the Tensor(s) used by the next Block.
  
  Args:
    inputs: A list of Tensors selected by the InputSelector.  Returns a list
      of Tensors to be used as input layers.
    **kwargs: Allows data_format to be propagated using arg_scope.
  
  Returns:
    A list of Tensors after being combined.
code: def __call__(self, inputs, **kwargs):
      """Combines inputs to produce the Tensor(s) used by the next Block.
  
      Args:
        inputs: A list of Tensors selected by the InputSelector.  Returns a list
          of Tensors to be used as input layers.
        **kwargs: Allows data_format to be propagated using arg_scope.
  
      Returns:
        A list of Tensors after being combined.
      """
  
imports: import abc
  import collections
  import enum
  import time
  from absl import logging
  from model_search import block_builder
  from model_search import utils
  from model_search.architecture import architecture_utils
  from model_search.proto import phoenix_spec_pb2
  import tensorflow.compat.v2
label_desc: Use image node_id 2 for calling the Combiner obj's underlying member method code with example usage: obj.__call__(inputs) without return types