



import json
import sys
import tempfile
import unittest
from pathlib import Path

import transformers
from transformers import (
    CONFIG_MAPPING,
    IMAGE_PROCESSOR_MAPPING,
    AutoConfig,
    AutoImageProcessor,
    CLIPConfig,
    CLIPImageProcessor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER


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

from test_module.custom_configuration import CustomConfig  # noqa E402
from test_module.custom_image_processing import CustomImageProcessor  # noqa E402

class        snake_case__    (unittest.TestCase		):







						"""simple docstring"""




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




									a__       :						Optional[Any]							=  0

						def 							SCREAMING_SNAKE_CASE__(       self  ) ->				Union[str, Any]:
									"""simple docstring"""




									a__       :						List[Any]							=  AutoImageProcessor.from_pretrained("""openai/clip-vit-base-patch32"""  )
									self.assertIsInstance(__lowercase ,       __lowercase  )

						def 							SCREAMING_SNAKE_CASE__(       self  ) ->				Optional[Any]:
									"""simple docstring"""




									with tempfile.TemporaryDirectory() as tmpdirname:
												a__       :						Tuple							=  Path(__lowercase  ) / """preprocessor_config.json"""
												a__       :						List[Any]							=  Path(__lowercase  ) / """config.json"""
												json.dump(
												    {"""image_processor_type""": """CLIPImageProcessor""", """processor_class""": """CLIPProcessor"""} ,       open(__lowercase ,       """w"""  ) ,       )
												json.dump({"""model_type""": """clip"""} ,       open(__lowercase ,       """w"""  )  )

												a__       :						str							=  AutoImageProcessor.from_pretrained(__lowercase  )
												self.assertIsInstance(__lowercase ,       __lowercase  )

						def 							SCREAMING_SNAKE_CASE__(       self  ) ->				Optional[Any]:
									"""simple docstring"""




									with tempfile.TemporaryDirectory() as tmpdirname:
												a__       :						Tuple							=  Path(__lowercase  ) / """preprocessor_config.json"""
												a__       :						int							=  Path(__lowercase  ) / """config.json"""
												json.dump(
												    {"""feature_extractor_type""": """CLIPFeatureExtractor""", """processor_class""": """CLIPProcessor"""} ,       open(__lowercase ,       """w"""  ) ,       )
												json.dump({"""model_type""": """clip"""} ,       open(__lowercase ,       """w"""  )  )

												a__       :						Tuple							=  AutoImageProcessor.from_pretrained(__lowercase  )
												self.assertIsInstance(__lowercase ,       __lowercase  )

						def 							SCREAMING_SNAKE_CASE__(       self  ) ->				Dict:
									"""simple docstring"""




									with tempfile.TemporaryDirectory() as tmpdirname:
												a__       :						List[str]							=  CLIPConfig()

												# Create a dummy config file with image_proceesor_type
												a__       :						Union[str, Any]							=  Path(__lowercase  ) / """preprocessor_config.json"""
												a__       :						Dict							=  Path(__lowercase  ) / """config.json"""
												json.dump(
												    {"""image_processor_type""": """CLIPImageProcessor""", """processor_class""": """CLIPProcessor"""} ,       open(__lowercase ,       """w"""  ) ,       )
												json.dump({"""model_type""": """clip"""} ,       open(__lowercase ,       """w"""  )  )

												# remove image_processor_type to make sure config.json alone is enough to load image processor locally
												a__       :						str							=  AutoImageProcessor.from_pretrained(__lowercase  ).to_dict()

												config_dict.pop("""image_processor_type"""  )
												a__       :						Optional[int]							=  CLIPImageProcessor(**__lowercase  )

												# save in new folder
												model_config.save_pretrained(__lowercase  )
												config.save_pretrained(__lowercase  )

												a__       :						Optional[Any]							=  AutoImageProcessor.from_pretrained(__lowercase  )

												# make sure private variable is not incorrectly saved
												a__       :						List[Any]							=  json.loads(config.to_json_string()  )
												self.assertTrue("""_processor_class""" not in dict_as_saved  )

									self.assertIsInstance(__lowercase ,       __lowercase  )

						def 							SCREAMING_SNAKE_CASE__(       self  ) ->				List[str]:
									"""simple docstring"""




									with tempfile.TemporaryDirectory() as tmpdirname:
												a__       :						Tuple							=  Path(__lowercase  ) / """preprocessor_config.json"""
												json.dump(
												    {"""image_processor_type""": """CLIPImageProcessor""", """processor_class""": """CLIPProcessor"""} ,       open(__lowercase ,       """w"""  ) ,       )

												a__       :						Tuple							=  AutoImageProcessor.from_pretrained(__lowercase  )
												self.assertIsInstance(__lowercase ,       __lowercase  )

						def 							SCREAMING_SNAKE_CASE__(       self  ) ->				str:
									"""simple docstring"""




									with self.assertRaisesRegex(
									    __lowercase ,       """clip-base is not a local folder and is not a valid model identifier"""  ):
												a__       :						Tuple							=  AutoImageProcessor.from_pretrained("""clip-base"""  )

						def 							SCREAMING_SNAKE_CASE__(       self  ) ->				int:
									"""simple docstring"""




									with self.assertRaisesRegex(
									    __lowercase ,       r"""aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"""  ):
												a__       :						Optional[Any]							=  AutoImageProcessor.from_pretrained(__lowercase ,       revision="""aaaaaa"""  )

						def 							SCREAMING_SNAKE_CASE__(       self  ) ->				Union[str, Any]:
									"""simple docstring"""




									with self.assertRaisesRegex(
									    __lowercase ,       """hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json.""" ,       ):
												a__       :						List[str]							=  AutoImageProcessor.from_pretrained("""hf-internal-testing/config-no-model"""  )

						def 							SCREAMING_SNAKE_CASE__(       self  ) ->				str:
									"""simple docstring"""




									with self.assertRaises(__lowercase  ):
												a__       :						Any							=  AutoImageProcessor.from_pretrained("""hf-internal-testing/test_dynamic_image_processor"""  )
									# If remote code is disabled, we can't load this config.
									with self.assertRaises(__lowercase  ):
												a__       :						Dict							=  AutoImageProcessor.from_pretrained(
												    """hf-internal-testing/test_dynamic_image_processor""" ,       trust_remote_code=__lowercase  )

									a__       :						List[str]							=  AutoImageProcessor.from_pretrained(
									    """hf-internal-testing/test_dynamic_image_processor""" ,       trust_remote_code=__lowercase  )
									self.assertEqual(image_processor.__class__.__name__ ,       """NewImageProcessor"""  )

									# Test image processor can be reloaded.
									with tempfile.TemporaryDirectory() as tmp_dir:
												image_processor.save_pretrained(__lowercase  )
												a__       :						Union[str, Any]							=  AutoImageProcessor.from_pretrained(__lowercase ,       trust_remote_code=__lowercase  )
									self.assertEqual(reloaded_image_processor.__class__.__name__ ,       """NewImageProcessor"""  )

						def 							SCREAMING_SNAKE_CASE__(       self  ) ->				int:
									"""simple docstring"""




									try:
												AutoConfig.register("""custom""" ,       __lowercase  )
												AutoImageProcessor.register(__lowercase ,       __lowercase  )
												# Trying to register something existing in the Transformers library will raise an error
												with self.assertRaises(__lowercase  ):
															AutoImageProcessor.register(__lowercase ,       __lowercase  )

												with tempfile.TemporaryDirectory() as tmpdirname:
															a__       :						Any							=  Path(__lowercase  ) / """preprocessor_config.json"""
															a__       :						int							=  Path(__lowercase  ) / """config.json"""
															json.dump(
															    {"""feature_extractor_type""": """CLIPFeatureExtractor""", """processor_class""": """CLIPProcessor"""} ,       open(__lowercase ,       """w"""  ) ,       )
															json.dump({"""model_type""": """clip"""} ,       open(__lowercase ,       """w"""  )  )

															a__       :						Union[str, Any]							=  CustomImageProcessor.from_pretrained(__lowercase  )

												# Now that the config is registered, it can be used as any other config with the auto-API
												with tempfile.TemporaryDirectory() as tmp_dir:
															image_processor.save_pretrained(__lowercase  )
															a__       :						Tuple							=  AutoImageProcessor.from_pretrained(__lowercase  )
															self.assertIsInstance(__lowercase ,       __lowercase  )

									finally:
												if "custom" in CONFIG_MAPPING._extra_content:
															del CONFIG_MAPPING._extra_content["custom"]
												if CustomConfig in IMAGE_PROCESSOR_MAPPING._extra_content:
															del IMAGE_PROCESSOR_MAPPING._extra_content[CustomConfig]

						def 							SCREAMING_SNAKE_CASE__(       self  ) ->				Dict:
									"""simple docstring"""




									class        snake_case__    (A__		):







															"""simple docstring"""




															__lowerCAmelCase					:str      =					True

									try:
												AutoConfig.register("""custom""" ,       __lowercase  )
												AutoImageProcessor.register(__lowercase ,       __lowercase  )
												# If remote code is not set, the default is to use local
												a__       :						Any							=  AutoImageProcessor.from_pretrained("""hf-internal-testing/test_dynamic_image_processor"""  )
												self.assertEqual(image_processor.__class__.__name__ ,       """NewImageProcessor"""  )
												self.assertTrue(image_processor.is_local  )

												# If remote code is disabled, we load the local one.
												a__       :						List[str]							=  AutoImageProcessor.from_pretrained(
												    """hf-internal-testing/test_dynamic_image_processor""" ,       trust_remote_code=__lowercase  )
												self.assertEqual(image_processor.__class__.__name__ ,       """NewImageProcessor"""  )
												self.assertTrue(image_processor.is_local  )

												# If remote is enabled, we load from the Hub
												a__       :						Tuple							=  AutoImageProcessor.from_pretrained(
												    """hf-internal-testing/test_dynamic_image_processor""" ,       trust_remote_code=__lowercase  )
												self.assertEqual(image_processor.__class__.__name__ ,       """NewImageProcessor"""  )
												self.assertTrue(not hasattr(__lowercase ,       """is_local"""  )  )

									finally:
												if "custom" in CONFIG_MAPPING._extra_content:
															del CONFIG_MAPPING._extra_content["custom"]
												if CustomConfig in IMAGE_PROCESSOR_MAPPING._extra_content:
															del IMAGE_PROCESSOR_MAPPING._extra_content[CustomConfig]









import warnings

from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor


_lowercase		:				Union[str, Any]      		=logging.get_logger(__name__)

class        snake_case__    (A__		):







						"""simple docstring"""




						def __init__(       self ,       *__lowercase ,       **__lowercase  ) ->				None:
									"""simple docstring"""




									warnings.warn(
									    """The class MobileViTFeatureExtractor is deprecated and will be removed in version 5 of Transformers."""
									    """ Please use MobileViTImageProcessor instead.""" ,       __lowercase ,       )
									super().__init__(*__lowercase ,       **__lowercase  )




