class_docstr: A DoFn that loads tflite models and predicts.
class_docstr_tok: ["A","DoFn","that","loads","tflite","models","and","predicts","."]
code: def setup(self):
      super().setup()
      self._interpreters = {}
  
      major, minor, _ = tf.version.VERSION.split(".")
      op_resolver_type = _OpResolverType.AUTO
      # TODO(b/207600661): drop BUILTIN_WITHOUT_DEFAULT_DELEGATES once the issue
      # is fixed.
      if int(major) > 2 or (int(major) == 2 and int(minor) >= 5):
          op_resolver_type = (
              _OpResolverType.BUILTIN_WITHOUT_DEFAULT_DELEGATES
          )
      for model_name, model_contents in self._loaded_models.items():
          self._interpreters[model_name] = self._make_interpreter(
              model_content=model_contents.contents,
              experimental_op_resolver_type=op_resolver_type,
          )
  
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 2 for calling the TFLitePredictionDoFn obj's underlying member method code with example usage: obj.setup() without return types