class_docstr: A DoFn that loads tflite models and predicts.
class_docstr_tok: ["A","DoFn","that","loads","tflite","models","and","predicts","."]
docstr: Get input name from input detail.
  
  Args:
    input_detail: the details for a model input.
  
  Returns:
    Input name. The signature key prefix and argument postfix will be removed.
docstr_tok: ["Get","input","name","from","input","detail",".","Args",":","input_detail",":","the","details","for","a","model","input",".","Returns",":","Input","name",".","The","signature","key","prefix","and","argument","postfix","will","be","removed","."]
code: def _get_input_name_from_input_detail(self, input_detail):
      """Get input name from input detail.
  
      Args:
        input_detail: the details for a model input.
  
      Returns:
        Input name. The signature key prefix and argument postfix will be removed.
      """
      input_name = input_detail["name"]
      # TFLite saved model converter inserts the signature key name at beginning
      # of the input names. TFLite rewriter assumes that the default signature key
      # ('serving_default') will be used as an exported name when saving.
      if input_name.startswith("serving_default_"):
          input_name = input_name[len("serving_default_") :]
      # Remove argument that starts with ':'.
      input_name = input_name.split(":")[0]
      return input_name
  
imports: import collections
  import copy
  from typing import Callable, Dict, Sequence, Union
  from absl import logging
  import apache_beam
  import numpy
  import tensorflow
  from tensorflow_model_analysis import constants
  from tensorflow_model_analysis.api import types
  from tensorflow_model_analysis.extractors import extractor
  from tensorflow_model_analysis.proto import config_pb2
  from tensorflow_model_analysis.utils import model_util
  from tensorflow_model_analysis.utils import util
label_desc: Use image node_id 4 for calling the TFLitePredictionDoFn obj's underlying member method code with example usage: obj._get_input_name_from_input_detail(input_detail) and returns: input_name