class_docstr: Represents the output of a regression head.
class_docstr_tok: ["Represents","the","output","of","a","regression","head","."]
code: def as_signature_def(self, receiver_tensors):
      if len(receiver_tensors) != 1:
          raise ValueError(
              "Regression signatures can only accept a single tensor input of "
              "type tf.string. Please check to make sure that you have structured "
              "the serving_input_receiver_fn so that it creates a single string "
              "placeholder. If your model function expects multiple inputs, then "
              "use `tf.io.parse_example()` to parse the string into multiple "
              f"tensors.\n Received: {receiver_tensors}"
          )
      ((_, examples),) = receiver_tensors.items()
      if dtypes.as_dtype(examples.dtype) != dtypes.string:
          raise ValueError(
              "Regression signatures can only accept a single tensor input of "
              "type tf.string. Please check to make sure that you have structured "
              "the serving_input_receiver_fn so that it creates a single string "
              "placeholder. If your model function expects multiple inputs, then "
              "use `tf.io.parse_example()` to parse the string into multiple "
              f"tensors.\n Received: {receiver_tensors}"
          )
      return signature_def_utils.regression_signature_def(
          examples, self.value
      )
  
imports: import abc
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.saved_model import signature_def_utils
label_desc: Use image node_id 3 for calling the RegressionOutput obj's underlying member method code with example usage: obj.as_signature_def(receiver_tensors) and returns: signature_def_utils