code: def build_or_reuse_placeholder(tensor_spec):
      
      g = tfv1.get_default_graph()
      name = tensor_spec.name
      try:
          tensor = g.get_tensor_by_name(name + ':0')
          assert "Placeholder" in tensor.op.type, "Tensor {} exists but is not a placeholder!".format(name)
          assert tensor_spec.is_compatible_with(tensor), \
              "Tensor {} exists but is not compatible with the signature!".format(tensor)
          return tensor
      except KeyError:
          with tfv1.name_scope(None):   # clear any name scope it might get called in
              ret = tfv1.placeholder(
                  tensor_spec.dtype, shape=tensor_spec.shape, name=tensor_spec.name)
          return ret
docs: Build a tf.placeholder from the metadata in the given tensor spec, or return an existing one.
  
      Args:
          tensor_spec (tf.TensorSpec):
  
      Returns:
          tf.Tensor: