class_docstr: A csv data provider.
class_docstr_tok: ["A","csv","data","provider","."]
docstr: Returns an `input_fn` for serving in an exported SavedModel.
  
  Args:
    hparams: tf.HParams object.
  
  Returns:
    Returns an `input_fn` that takes no arguments and returns a
      `ServingInputReceiver`.
docstr_tok: ["Returns","an","`","input_fn","`","for","serving","in","an","exported","SavedModel",".","Args",":","hparams",":","tf.HParams","object",".","Returns",":","Returns","an","`","input_fn","`","that","takes","no","arguments","and","returns","a","`","ServingInputReceiver","`","."]
code: def get_serving_input_fn(self, hparams):
      """Returns an `input_fn` for serving in an exported SavedModel.
  
      Args:
        hparams: tf.HParams object.
  
      Returns:
        Returns an `input_fn` that takes no arguments and returns a
          `ServingInputReceiver`.
      """
  
      features_ind = [
          idx for idx in self._features if idx != str(self._label_index)
      ]
      tf.compat.v1.disable_eager_execution()
      features = {
          idx: tf.compat.v1.placeholder(tf.float32, [None], idx)
          for idx in features_ind
      }
      return tf.estimator.export.build_raw_serving_input_receiver_fn(
          features=features
      )
  
file_path: model_search/model_search/data/csv_data_for_binary.py
imports: from absl import flags
  from model_search.data import data
  import numpy
  import pandas
  import tensorflow.compat.v2
label_desc: Use image node_id 3 for calling the Provider obj's underlying member method code with example usage: obj.get_serving_input_fn(hparams) and returns: tf