code: def test_inference_mask_generation_two_points_point_batch(self):
      model = TFSamModel.from_pretrained("facebook/sam-vit-base")
      processor = SamProcessor.from_pretrained("facebook/sam-vit-base")
  
      raw_image = prepare_image()
  
      input_points = tf.convert_to_tensor([[[400, 650]], [[220, 470]]])  # fmt: skip
  
      input_points = tf.expand_dims(input_points, 0)
  
      inputs = processor(
          raw_image, input_points=input_points, return_tensors="tf"
      )
  
      outputs = model(**inputs)
  
      iou_scores = outputs.iou_scores
      self.assertTrue(iou_scores.shape == (1, 2, 3))
      self.assertTrue(
          np.allclose(
              iou_scores.numpy(),
              np.array(
                  [[[0.9105, 0.9825, 0.9675], [0.7646, 0.7943, 0.7774]]]
              ),
              atol=1e-4,
              rtol=1e-4,
          )
      )
  
imports: from __future__ import annotations
  import inspect
  import unittest
  import numpy
  import requests
  from transformers import SamConfig, SamMaskDecoderConfig, SamPromptEncoderConfig, SamVisionConfig
  from transformers.testing_utils import require_tf, slow
  from transformers.utils import is_tf_available, is_vision_available
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 10 for calling the TFSamModelIntegrationTest obj's underlying member method code with example usage: obj.test_inference_mask_generation_two_points_point_batch() without return types