class_docstr: For training speaker recognition models. 
code: def create_serving_input_receiver_fn(self):
      # with batch_size
      taskconf = self.config["data"]["task"]
      shape = [None] + taskconf["audio"]["feature_shape"]
      logging.debug("serving input shape:{}".format(shape))
  
      return tf.estimator.export.build_raw_serving_input_receiver_fn(
          features={
              "inputs": tf.placeholder(
                  name="inputs", shape=shape, dtype=tf.float32
              ),
          },
          default_batch_size=None,
      )
  
file_path: delta/delta/utils/solver/speaker_solver.py
imports: from absl import logging
  import librosa
  import delta.compat
  from delta.utils.solver.estimator_solver import EstimatorSolver
  from delta.utils.register import registers
label_desc: Use image node_id 2 for calling the SpeakerSolver obj's underlying member method code with example usage: obj.create_serving_input_receiver_fn() and returns: tf