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test_generative_multi_modal_embedding.py 3.0 kB

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  1. # Copyright (c) Alibaba, Inc. and its affiliates.
  2. import unittest
  3. import numpy as np
  4. from modelscope.models import Model
  5. from modelscope.pipelines import pipeline
  6. from modelscope.utils.constant import Tasks
  7. from modelscope.utils.test_utils import test_level
  8. class GEMMMultiModalEmbeddingTest(unittest.TestCase):
  9. model_id = 'damo/multi-modal_gemm-vit-large-patch14_generative-multi-modal-embedding'
  10. test_input = {
  11. 'image': 'data/test/images/generative_multimodal.jpg',
  12. 'text':
  13. 'interior design of modern living room with fireplace in a new house',
  14. 'captioning': False
  15. }
  16. @unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
  17. def test_run(self):
  18. generative_multi_modal_embedding_pipeline = pipeline(
  19. Tasks.generative_multi_modal_embedding, model=self.model_id)
  20. output = generative_multi_modal_embedding_pipeline(self.test_input)
  21. print(output)
  22. @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
  23. def test_run_with_default_model(self):
  24. generative_multi_modal_embedding_pipeline = pipeline(
  25. task=Tasks.generative_multi_modal_embedding)
  26. output = generative_multi_modal_embedding_pipeline(self.test_input)
  27. print(output)
  28. @unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
  29. def test_run_with_model_from_modelhub(self):
  30. model = Model.from_pretrained(self.model_id)
  31. generative_multi_modal_embedding_pipeline = pipeline(
  32. task=Tasks.generative_multi_modal_embedding, model=model)
  33. output = generative_multi_modal_embedding_pipeline(self.test_input)
  34. print(output)
  35. @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
  36. def test_run_with_output_captioning(self):
  37. generative_multi_modal_embedding_pipeline = pipeline(
  38. task=Tasks.generative_multi_modal_embedding, model=self.model_id)
  39. test_input = {'image': self.test_input['image'], 'captioning': True}
  40. output = generative_multi_modal_embedding_pipeline(test_input)
  41. print(output)
  42. @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
  43. def test_run_with_output_only_image(self):
  44. generative_multi_modal_embedding_pipeline = pipeline(
  45. task=Tasks.generative_multi_modal_embedding, model=self.model_id)
  46. test_input = {'image': self.test_input['image'], 'captioning': False}
  47. output = generative_multi_modal_embedding_pipeline(test_input)
  48. print(output)
  49. @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
  50. def test_run_with_output_only_text(self):
  51. generative_multi_modal_embedding_pipeline = pipeline(
  52. task=Tasks.generative_multi_modal_embedding, model=self.model_id)
  53. test_input = {'text': self.test_input['text']}
  54. output = generative_multi_modal_embedding_pipeline(test_input)
  55. print(output)
  56. if __name__ == '__main__':
  57. unittest.main()