docstr: This function computes the expected height and width when providing images to TvpImageProcessor,
  assuming do_resize is set to True with a scalar size.
docstr_tok: ["This","function","computes","the","expected","height","and","width","when","providing","images","to","TvpImageProcessor",",","assuming","do_resize","is","set","to","True","with","a","scalar","size","."]
code: def get_expected_values(self, image_inputs, batched=False):
      """
      This function computes the expected height and width when providing images to TvpImageProcessor,
      assuming do_resize is set to True with a scalar size.
      """
      if not batched:
          return (
              int(self.pad_size["height"]),
              int(self.pad_size["width"]),
          )
  
      else:
          expected_values = []
          for image in image_inputs:
              (
                  expected_height,
                  expected_width,
              ) = self.get_expected_values([image])
              expected_values.append((expected_height, expected_width))
          expected_height = max(
              expected_values, key=lambda item: item[0]
          )[0]
          expected_width = max(
              expected_values, key=lambda item: item[1]
          )[1]
  
      return expected_height, expected_width
  
imports: import unittest
  from typing import Dict, List, Optional, Union
  import numpy
  from transformers.image_transforms import PaddingMode
  from transformers.testing_utils import require_torch, require_vision
  from transformers.utils import is_torch_available, is_vision_available
  from ...test_image_processing_common import ImageProcessingTestMixin, prepare_video_inputs
label_desc: Use image node_id 3 for calling the TvpImageProcessingTester obj's underlying member method code with example usage: obj.get_expected_values(image_inputs, batched) and returns: expected_height,  expected_width, int,  int