class_docstr: Test class that extends tf.test.TestCase with extra functionality.
docstr: Run predict_list for a list of examples for a injective model.
  
  Args:
    eval_saved_model: EvalSavedModel
    raw_example_bytes_list: List of raw example bytes
  
  Returns:
    The list of FPLs returned by eval_saved_model.predict on the given
    raw_example_bytes.
docstr_tok: ["Run","predict_list","for","a","list","of","examples","for","a","injective","model",".","Args",":","eval_saved_model",":","EvalSavedModel","raw_example_bytes_list",":","List","of","raw","example","bytes","Returns",":","The","list","of","FPLs","returned","by","eval_saved_model.predict","on","the","given","raw_example_bytes","."]
code: def predict_injective_example_list(
      self,
      eval_saved_model: load.EvalSavedModel,
      raw_example_bytes_list: List[bytes],
  ) -> List[types.FeaturesPredictionsLabels]:
      """Run predict_list for a list of examples for a injective model.
  
      Args:
        eval_saved_model: EvalSavedModel
        raw_example_bytes_list: List of raw example bytes
  
      Returns:
        The list of FPLs returned by eval_saved_model.predict on the given
        raw_example_bytes.
      """
      fetched_list = eval_saved_model.predict_list(
          raw_example_bytes_list
      )
  
      # Check that each FPL corresponds to one example.
      self.assertSequenceEqual(
          range(0, len(raw_example_bytes_list)),
          [fetched.input_ref for fetched in fetched_list],
      )
  
      return eval_saved_model.as_features_predictions_labels(
          fetched_list
      )
  
imports: import math
  import tempfile
  from typing import Dict, Iterable, List, Optional, Sequence, Tuple, Union
  import tensorflow
  from tensorflow_model_analysis import constants
  from tensorflow_model_analysis.api import types
  from tensorflow_model_analysis.eval_saved_model import constants
  from tensorflow_model_analysis.eval_saved_model import load
  from tensorflow_model_analysis.eval_saved_model import util
  from tensorflow_model_analysis.utils import model_util
label_desc: Use image node_id 13 for calling the TensorflowModelAnalysisTest obj's underlying member method code with example usage: obj.predict_injective_example_list(eval_saved_model, raw_example_bytes_list) and returns: eval_saved_model