


import warnings

from ...utils import logging
from .image_processing_flava import FlavaImageProcessor


lowerCamelCase__							:						Union[str, Any]							     =   logging.get_logger(__name__)
class 		__magic_name__						(snake_case_				):





     '''simple docstring'''



     def __init__(					self:List[str]     ,		*_a:List[Any]     ,		**_a:Optional[Any]   ):
       warnings.warn(
           '''The class FlavaFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'''
           ''' use FlavaImageProcessor instead.'''     ,		_a     ,		)
       super().__init__(*_a     ,		**_a   )





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 		__magic_name__						(unittest.TestCase				):





     '''simple docstring'''



     def 	SCREAMING_SNAKE_CASE__						(					self:List[Any]   ):
       snake_case__						= 0

     def 	SCREAMING_SNAKE_CASE__						(					self:Optional[Any]   ):
       snake_case__						= AutoImageProcessor.from_pretrained('''openai/clip-vit-base-patch32'''   )
       self.assertIsInstance(_a     ,		_a   )

     def 	SCREAMING_SNAKE_CASE__						(					self:str   ):
       with tempfile.TemporaryDirectory() as tmpdirname:
         snake_case__						= Path(_a   ) / '''preprocessor_config.json'''
         snake_case__						= Path(_a   ) / '''config.json'''
         json.dump(
             {'''image_processor_type''': '''CLIPImageProcessor''', '''processor_class''': '''CLIPProcessor'''}     ,		open(_a     ,		'''w'''   )     ,		)
         json.dump({'''model_type''': '''clip'''}     ,		open(_a     ,		'''w'''   )   )

         snake_case__						= AutoImageProcessor.from_pretrained(_a   )
         self.assertIsInstance(_a     ,		_a   )

     def 	SCREAMING_SNAKE_CASE__						(					self:Dict   ):
       # Ensure we can load the image processor from the feature extractor config
       with tempfile.TemporaryDirectory() as tmpdirname:
         snake_case__						= Path(_a   ) / '''preprocessor_config.json'''
         snake_case__						= Path(_a   ) / '''config.json'''
         json.dump(
             {'''feature_extractor_type''': '''CLIPFeatureExtractor''', '''processor_class''': '''CLIPProcessor'''}     ,		open(_a     ,		'''w'''   )     ,		)
         json.dump({'''model_type''': '''clip'''}     ,		open(_a     ,		'''w'''   )   )

         snake_case__						= AutoImageProcessor.from_pretrained(_a   )
         self.assertIsInstance(_a     ,		_a   )

     def 	SCREAMING_SNAKE_CASE__						(					self:Optional[int]   ):
       with tempfile.TemporaryDirectory() as tmpdirname:
         snake_case__						= CLIPConfig()

         # Create a dummy config file with image_proceesor_type
         snake_case__						= Path(_a   ) / '''preprocessor_config.json'''
         snake_case__						= Path(_a   ) / '''config.json'''
         json.dump(
             {'''image_processor_type''': '''CLIPImageProcessor''', '''processor_class''': '''CLIPProcessor'''}     ,		open(_a     ,		'''w'''   )     ,		)
         json.dump({'''model_type''': '''clip'''}     ,		open(_a     ,		'''w'''   )   )

         # remove image_processor_type to make sure config.json alone is enough to load image processor locally
         snake_case__						= AutoImageProcessor.from_pretrained(_a   ).to_dict()

         config_dict.pop('''image_processor_type'''   )
         snake_case__						= CLIPImageProcessor(**_a   )

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

         snake_case__						= AutoImageProcessor.from_pretrained(_a   )

         # make sure private variable is not incorrectly saved
         snake_case__						= json.loads(config.to_json_string()   )
         self.assertTrue('''_processor_class''' not in dict_as_saved   )

       self.assertIsInstance(_a     ,		_a   )

     def 	SCREAMING_SNAKE_CASE__						(					self:List[str]   ):
       with tempfile.TemporaryDirectory() as tmpdirname:
         snake_case__						= Path(_a   ) / '''preprocessor_config.json'''
         json.dump(
             {'''image_processor_type''': '''CLIPImageProcessor''', '''processor_class''': '''CLIPProcessor'''}     ,		open(_a     ,		'''w'''   )     ,		)

         snake_case__						= AutoImageProcessor.from_pretrained(_a   )
         self.assertIsInstance(_a     ,		_a   )

     def 	SCREAMING_SNAKE_CASE__						(					self:Dict   ):
       with self.assertRaisesRegex(
           _a     ,		'''clip-base is not a local folder and is not a valid model identifier'''   ):
         snake_case__						= AutoImageProcessor.from_pretrained('''clip-base'''   )

     def 	SCREAMING_SNAKE_CASE__						(					self:Union[str, Any]   ):
       with self.assertRaisesRegex(
           _a     ,		r'''aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'''   ):
         snake_case__						= AutoImageProcessor.from_pretrained(_a     ,		revision='''aaaaaa'''   )

     def 	SCREAMING_SNAKE_CASE__						(					self:List[Any]   ):
       with self.assertRaisesRegex(
           _a     ,		'''hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json.'''     ,		):
         snake_case__						= AutoImageProcessor.from_pretrained('''hf-internal-testing/config-no-model'''   )

     def 	SCREAMING_SNAKE_CASE__						(					self:Dict   ):
       # If remote code is not set, we will time out when asking whether to load the model.
       with self.assertRaises(_a   ):
         snake_case__						= AutoImageProcessor.from_pretrained('''hf-internal-testing/test_dynamic_image_processor'''   )
       # If remote code is disabled, we can't load this config.
       with self.assertRaises(_a   ):
         snake_case__						= AutoImageProcessor.from_pretrained(
             '''hf-internal-testing/test_dynamic_image_processor'''     ,		trust_remote_code=_a   )

       snake_case__						= AutoImageProcessor.from_pretrained(
           '''hf-internal-testing/test_dynamic_image_processor'''     ,		trust_remote_code=_a   )
       self.assertEqual(image_processor.__class__.__name__     ,		'''NewImageProcessor'''   )

       # Test image processor can be reloaded.
       with tempfile.TemporaryDirectory() as tmp_dir:
         image_processor.save_pretrained(_a   )
         snake_case__						= AutoImageProcessor.from_pretrained(_a     ,		trust_remote_code=_a   )
       self.assertEqual(reloaded_image_processor.__class__.__name__     ,		'''NewImageProcessor'''   )

     def 	SCREAMING_SNAKE_CASE__						(					self:Dict   ):
       try:
         AutoConfig.register('''custom'''     ,		_a   )
         AutoImageProcessor.register(_a     ,		_a   )
         # Trying to register something existing in the Transformers library will raise an error
         with self.assertRaises(_a   ):
           AutoImageProcessor.register(_a     ,		_a   )

         with tempfile.TemporaryDirectory() as tmpdirname:
           snake_case__						= Path(_a   ) / '''preprocessor_config.json'''
           snake_case__						= Path(_a   ) / '''config.json'''
           json.dump(
               {'''feature_extractor_type''': '''CLIPFeatureExtractor''', '''processor_class''': '''CLIPProcessor'''}     ,		open(_a     ,		'''w'''   )     ,		)
           json.dump({'''model_type''': '''clip'''}     ,		open(_a     ,		'''w'''   )   )

           snake_case__						= CustomImageProcessor.from_pretrained(_a   )

         # 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(_a   )
           snake_case__						= AutoImageProcessor.from_pretrained(_a   )
           self.assertIsInstance(_a     ,		_a   )

       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:Optional[int]   ):
       class 		__magic_name__						(snake_case_				):





            '''simple docstring'''



            __lowercase				:							List[str]	   =       True

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

         # If remote is enabled, we load from the Hub
         snake_case__						= AutoImageProcessor.from_pretrained(
             '''hf-internal-testing/test_dynamic_image_processor'''     ,		trust_remote_code=_a   )
         self.assertEqual(image_processor.__class__.__name__     ,		'''NewImageProcessor'''   )
         self.assertTrue(not hasattr(_a     ,		'''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]

