code: def merge_outputs(tensor_list, name="MergeOutputs"):
      """Merge Outputs.
  
      A layer that concatenate all outputs of a network into a single tensor.
  
      Input:
          List of Tensors [_shape_].
  
      Output:
          Concatenated Tensors [nb_tensors, _shape_].
  
      Arguments:
          tensor_list: list of `Tensor`. The network outputs.
          name: `str`. A name for this layer (optional).
  
      Returns:
          A `Tensor`.
  
      """
      with tf.name_scope(name) as scope:
          x = tf.concat(tensor_list, 1)
  
      # Track output tensor.
      tf.add_to_collection(tf.GraphKeys.LAYER_TENSOR + "/" + name, x)
  
      return x
  
imports: from __future__ import division, print_function, absolute_import
  import tensorflow.compat.v1
label_desc: Use image node_id 2 for calling a global function with example usage: merge_outputs(tensor_list, name) and returns: x