





import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path

from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError

from transformers import AutoImageProcessor, ViTImageProcessor
from transformers.testing_utils import TOKEN, USER, get_tests_dir, is_staging_test


sys.path.append(str(Path(__file__).parent.parent / """utils"""))

from test_module.custom_image_processing import CustomImageProcessor  # noqa E402


SCREAMING_SNAKE_CASE_						       =	get_tests_dir("""fixtures""")

class 		UpperCamelCase__			(				unittest.TestCase       ):



					'''simple docstring'''

					def     SCREAMING_SNAKE_CASE__  (							self						:   Dict	)					->		int:




											'''simple docstring'''


											SCREAMING_SNAKE_CASE		=						mock.Mock()
											SCREAMING_SNAKE_CASE		=						500
											SCREAMING_SNAKE_CASE		=						{}
											SCREAMING_SNAKE_CASE		=						HTTPError
											SCREAMING_SNAKE_CASE		=						{}

											# Download this model to make sure it's in the cache.
											SCREAMING_SNAKE_CASE		=						ViTImageProcessor.from_pretrained("""hf-internal-testing/tiny-random-vit"""	)
											# Under the mock environment we get a 500 error when trying to reach the model.
											with mock.patch("""requests.Session.request"""						,return_value=_snake_case	) as mock_head:
																	SCREAMING_SNAKE_CASE		=						ViTImageProcessor.from_pretrained("""hf-internal-testing/tiny-random-vit"""	)
																	# This check we did call the fake head request
																	mock_head.assert_called()






					def     SCREAMING_SNAKE_CASE__  (							self						:   List[Any]	)					->		str:




											'''simple docstring'''


											SCREAMING_SNAKE_CASE		=						ViTImageProcessor.from_pretrained(
											    """https://huggingface.co/hf-internal-testing/tiny-random-vit/resolve/main/preprocessor_config.json"""	)






					def     SCREAMING_SNAKE_CASE__  (							self						:   str	)					->		List[Any]:




											'''simple docstring'''


											with self.assertRaises(_snake_case	):
																	# config is in subfolder, the following should not work without specifying the subfolder
																	SCREAMING_SNAKE_CASE		=						AutoImageProcessor.from_pretrained("""hf-internal-testing/stable-diffusion-all-variants"""	)

											SCREAMING_SNAKE_CASE		=						AutoImageProcessor.from_pretrained(
											    """hf-internal-testing/stable-diffusion-all-variants"""						,subfolder="""feature_extractor"""	)

											self.assertIsNotNone(_snake_case	)

@is_staging_test
class 		UpperCamelCase__			(				unittest.TestCase       ):



					'''simple docstring'''

					@classmethod
					def     SCREAMING_SNAKE_CASE__  (							cls						:   Union[str, Any]	)					->		Optional[Any]:




											'''simple docstring'''


											SCREAMING_SNAKE_CASE		=						TOKEN
											HfFolder.save_token(_snake_case	)






					@classmethod
					def     SCREAMING_SNAKE_CASE__  (							cls						:   Any	)					->		str:




											'''simple docstring'''


											try:
																	delete_repo(token=cls._token						,repo_id="""test-image-processor"""	)
											except HTTPError:
																	pass

											try:
																	delete_repo(token=cls._token						,repo_id="""valid_org/test-image-processor-org"""	)
											except HTTPError:
																	pass

											try:
																	delete_repo(token=cls._token						,repo_id="""test-dynamic-image-processor"""	)
											except HTTPError:
																	pass






					def     SCREAMING_SNAKE_CASE__  (							self						:   Any	)					->		List[Any]:




											'''simple docstring'''


											SCREAMING_SNAKE_CASE		=						ViTImageProcessor.from_pretrained(_snake_case	)
											image_processor.push_to_hub("""test-image-processor"""						,use_auth_token=self._token	)

											SCREAMING_SNAKE_CASE		=						ViTImageProcessor.from_pretrained(F"""{USER}/test-image-processor"""	)
											for k, v in image_processor.__dict__.items():
																	self.assertEqual(_snake_case						,getattr(_snake_case						,_snake_case	)	)

											# Reset repo
											delete_repo(token=self._token						,repo_id="""test-image-processor"""	)

											# Push to hub via save_pretrained
											with tempfile.TemporaryDirectory() as tmp_dir:
																	image_processor.save_pretrained(
																	    _snake_case						,repo_id="""test-image-processor"""						,push_to_hub=_snake_case						,use_auth_token=self._token	)

											SCREAMING_SNAKE_CASE		=						ViTImageProcessor.from_pretrained(F"""{USER}/test-image-processor"""	)
											for k, v in image_processor.__dict__.items():
																	self.assertEqual(_snake_case						,getattr(_snake_case						,_snake_case	)	)






					def     SCREAMING_SNAKE_CASE__  (							self						:   Union[str, Any]	)					->		int:




											'''simple docstring'''


											SCREAMING_SNAKE_CASE		=						ViTImageProcessor.from_pretrained(_snake_case	)
											image_processor.push_to_hub("""valid_org/test-image-processor"""						,use_auth_token=self._token	)

											SCREAMING_SNAKE_CASE		=						ViTImageProcessor.from_pretrained("""valid_org/test-image-processor"""	)
											for k, v in image_processor.__dict__.items():
																	self.assertEqual(_snake_case						,getattr(_snake_case						,_snake_case	)	)

											# Reset repo
											delete_repo(token=self._token						,repo_id="""valid_org/test-image-processor"""	)

											# Push to hub via save_pretrained
											with tempfile.TemporaryDirectory() as tmp_dir:
																	image_processor.save_pretrained(
																	    _snake_case						,repo_id="""valid_org/test-image-processor-org"""						,push_to_hub=_snake_case						,use_auth_token=self._token	)

											SCREAMING_SNAKE_CASE		=						ViTImageProcessor.from_pretrained("""valid_org/test-image-processor-org"""	)
											for k, v in image_processor.__dict__.items():
																	self.assertEqual(_snake_case						,getattr(_snake_case						,_snake_case	)	)






					def     SCREAMING_SNAKE_CASE__  (							self						:   List[Any]	)					->		str:




											'''simple docstring'''


											CustomImageProcessor.register_for_auto_class()
											SCREAMING_SNAKE_CASE		=						CustomImageProcessor.from_pretrained(_snake_case	)

											image_processor.push_to_hub("""test-dynamic-image-processor"""						,use_auth_token=self._token	)

											# This has added the proper auto_map field to the config
											self.assertDictEqual(
											    image_processor.auto_map						,{"""AutoImageProcessor""": """custom_image_processing.CustomImageProcessor"""}						,)

											SCREAMING_SNAKE_CASE		=						AutoImageProcessor.from_pretrained(
											    F"""{USER}/test-dynamic-image-processor"""						,trust_remote_code=_snake_case	)
											# Can't make an isinstance check because the new_image_processor is from the CustomImageProcessor class of a dynamic module
											self.assertEqual(new_image_processor.__class__.__name__						,"""CustomImageProcessor"""	)









import json
import sys



def        __lowercase       (				_SCREAMING_SNAKE_CASE			,						_SCREAMING_SNAKE_CASE     )			->       Any:


      '''simple docstring'''


      with open(_SCREAMING_SNAKE_CASE			,						encoding="""utf-8"""     ) as f:
            SCREAMING_SNAKE_CASE		=						json.load(_SCREAMING_SNAKE_CASE     )

      SCREAMING_SNAKE_CASE		=						["""<details>""", """<summary>Show updated benchmarks!</summary>""", """ """]

      for benchmark_name in sorted(_SCREAMING_SNAKE_CASE     ):
            SCREAMING_SNAKE_CASE		=						results[benchmark_name]

            SCREAMING_SNAKE_CASE		=						benchmark_name.split("""/"""     )[-1]
            output_md.append(F"""### Benchmark: {benchmark_file_name}"""     )

            SCREAMING_SNAKE_CASE		=						"""| metric |"""
            SCREAMING_SNAKE_CASE		=						"""|--------|"""
            SCREAMING_SNAKE_CASE		=						"""| new / old (diff) |"""
            for metric_name in sorted(_SCREAMING_SNAKE_CASE     ):
                  SCREAMING_SNAKE_CASE		=						benchmark_res[metric_name]
                  SCREAMING_SNAKE_CASE		=						metric_vals["""new"""]
                  SCREAMING_SNAKE_CASE		=						metric_vals.get("""old"""			,						_SCREAMING_SNAKE_CASE     )
                  SCREAMING_SNAKE_CASE		=						metric_vals.get("""diff"""			,						_SCREAMING_SNAKE_CASE     )

                  SCREAMING_SNAKE_CASE		=						F""" {new_val:f}""" if isinstance(_SCREAMING_SNAKE_CASE			,						(int, float)     ) else """None"""

                  if old_val is not None:
                        val_str += F""" / {old_val:f}""" if isinstance(_SCREAMING_SNAKE_CASE			,						(int, float)     ) else "None"
                  if dif_val is not None:
                        val_str += F""" ({dif_val:f})""" if isinstance(_SCREAMING_SNAKE_CASE			,						(int, float)     ) else "None"

                  title += " " + metric_name + " |"
                  lines += "---|"
                  value += val_str + " |"

            output_md += [title, lines, value, " "]

      output_md.append("""</details>"""     )

      with open(_SCREAMING_SNAKE_CASE			,						"""w"""			,						encoding="""utf-8"""     ) as f:
            f.writelines("""\n""".join(_SCREAMING_SNAKE_CASE     )     )


if __name__ == "__main__":
      SCREAMING_SNAKE_CASE_						       =	sys.argv[1]
      SCREAMING_SNAKE_CASE_						       =	sys.argv[2]

      format_json_to_md(input_json_file, output_md_file)


