






import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging


SCREAMING_SNAKE_CASE						=	logging.get_logger(__name__)
class UpperCAmelCase_					(    __UpperCAmelCase				):




      """simple docstring"""




      UpperCamelCase_								=			"""encoder-decoder"""
      UpperCamelCase_								=			True






      def __init__( self			:		Tuple     ,      **UpperCAmelCase			:		str		)  ->  Tuple:


       '''simple docstring'''

       super().__init__(**UpperCAmelCase_		)
       assert (
           "encoder" in kwargs and "decoder" in kwargs
       ), "Config has to be initialized with encoder and decoder config"
       lowercase					:   List[str]				  =kwargs.pop('''encoder'''		)
       lowercase					:   Optional[int]				  =encoder_config.pop('''model_type'''		)
       lowercase					:   Optional[int]				  =kwargs.pop('''decoder'''		)
       lowercase					:   int				  =decoder_config.pop('''model_type'''		)

       from ..auto.configuration_auto import AutoConfig

       lowercase					:   Optional[Any]				  =AutoConfig.for_model(UpperCAmelCase_     ,      **UpperCAmelCase_		)
       lowercase					:   int				  =AutoConfig.for_model(UpperCAmelCase_     ,      **UpperCAmelCase_		)
       lowercase					:   Union[str, Any]				  =True






      @classmethod
      def 				A__      ( cls			:		Union[str, Any]     ,      UpperCAmelCase			:		List[Any]     ,      UpperCAmelCase			:		Tuple     ,      **UpperCAmelCase			:		Optional[Any]		)  ->  Dict:


       '''simple docstring'''

       logger.info('''Set `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config'''		)
       lowercase					:   int				  =True
       lowercase					:   Optional[Any]				  =True

       return cls(encoder=encoder_config.to_dict()     ,      decoder=decoder_config.to_dict()     ,      **UpperCAmelCase_		)






      def 				A__      ( self			:		Dict		)  ->  Dict:


       '''simple docstring'''

       lowercase					:   Dict				  =copy.deepcopy(self.__dict__		)
       lowercase					:   str				  =self.encoder.to_dict()
       lowercase					:   int				  =self.decoder.to_dict()
       lowercase					:   Dict				  =self.__class__.model_type
       return output











'''simple docstring'''



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 UpperCAmelCase_					(    unittest.TestCase				):




      """simple docstring"""




      def 				A__      ( self			:		int		)  ->  Any:


       '''simple docstring'''

       lowercase					:   Union[str, Any]				  =0






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


       '''simple docstring'''

       lowercase					:   Tuple				  =AutoImageProcessor.from_pretrained('''openai/clip-vit-base-patch32'''		)
       self.assertIsInstance(UpperCAmelCase     ,      UpperCAmelCase		)






      def 				A__      ( self			:		Any		)  ->  int:


       '''simple docstring'''

       with tempfile.TemporaryDirectory() as tmpdirname:
        lowercase					:   int				  =Path(UpperCAmelCase		) / '''preprocessor_config.json'''
        lowercase					:   str				  =Path(UpperCAmelCase		) / '''config.json'''
        json.dump(
            {'''image_processor_type''': '''CLIPImageProcessor''', '''processor_class''': '''CLIPProcessor'''}     ,      open(UpperCAmelCase     ,      '''w'''		)     ,      )
        json.dump({'''model_type''': '''clip'''}     ,      open(UpperCAmelCase     ,      '''w'''		)		)

        lowercase					:   str				  =AutoImageProcessor.from_pretrained(UpperCAmelCase		)
        self.assertIsInstance(UpperCAmelCase     ,      UpperCAmelCase		)






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


       '''simple docstring'''

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

        lowercase					:   Optional[Any]				  =AutoImageProcessor.from_pretrained(UpperCAmelCase		)
        self.assertIsInstance(UpperCAmelCase     ,      UpperCAmelCase		)






      def 				A__      ( self			:		Optional[Any]		)  ->  Any:


       '''simple docstring'''

       with tempfile.TemporaryDirectory() as tmpdirname:
        lowercase					:   str				  =CLIPConfig()

        # Create a dummy config file with image_proceesor_type
        lowercase					:   Optional[int]				  =Path(UpperCAmelCase		) / '''preprocessor_config.json'''
        lowercase					:   Optional[Any]				  =Path(UpperCAmelCase		) / '''config.json'''
        json.dump(
            {'''image_processor_type''': '''CLIPImageProcessor''', '''processor_class''': '''CLIPProcessor'''}     ,      open(UpperCAmelCase     ,      '''w'''		)     ,      )
        json.dump({'''model_type''': '''clip'''}     ,      open(UpperCAmelCase     ,      '''w'''		)		)

        # remove image_processor_type to make sure config.json alone is enough to load image processor locally
        lowercase					:   Dict				  =AutoImageProcessor.from_pretrained(UpperCAmelCase		).to_dict()

        config_dict.pop('''image_processor_type'''		)
        lowercase					:   str				  =CLIPImageProcessor(**UpperCAmelCase		)

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

        lowercase					:   Optional[int]				  =AutoImageProcessor.from_pretrained(UpperCAmelCase		)

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

       self.assertIsInstance(UpperCAmelCase     ,      UpperCAmelCase		)






      def 				A__      ( self			:		str		)  ->  List[str]:


       '''simple docstring'''

       with tempfile.TemporaryDirectory() as tmpdirname:
        lowercase					:   Dict				  =Path(UpperCAmelCase		) / '''preprocessor_config.json'''
        json.dump(
            {'''image_processor_type''': '''CLIPImageProcessor''', '''processor_class''': '''CLIPProcessor'''}     ,      open(UpperCAmelCase     ,      '''w'''		)     ,      )

        lowercase					:   Optional[Any]				  =AutoImageProcessor.from_pretrained(UpperCAmelCase		)
        self.assertIsInstance(UpperCAmelCase     ,      UpperCAmelCase		)






      def 				A__      ( self			:		int		)  ->  List[str]:


       '''simple docstring'''

       with self.assertRaisesRegex(
           UpperCAmelCase     ,      '''clip-base is not a local folder and is not a valid model identifier'''		):
        lowercase					:   Union[str, Any]				  =AutoImageProcessor.from_pretrained('''clip-base'''		)






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


       '''simple docstring'''

       with self.assertRaisesRegex(
           UpperCAmelCase     ,      R'''aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'''		):
        lowercase					:   Any				  =AutoImageProcessor.from_pretrained(UpperCAmelCase     ,      revision='''aaaaaa'''		)






      def 				A__      ( self			:		Tuple		)  ->  Optional[int]:


       '''simple docstring'''

       with self.assertRaisesRegex(
           UpperCAmelCase     ,      '''hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json.'''     ,      ):
        lowercase					:   Optional[int]				  =AutoImageProcessor.from_pretrained('''hf-internal-testing/config-no-model'''		)






      def 				A__      ( self			:		List[str]		)  ->  str:


       '''simple docstring'''

       with self.assertRaises(UpperCAmelCase		):
        lowercase					:   Dict				  =AutoImageProcessor.from_pretrained('''hf-internal-testing/test_dynamic_image_processor'''		)
       # If remote code is disabled, we can't load this config.
       with self.assertRaises(UpperCAmelCase		):
        lowercase					:   List[str]				  =AutoImageProcessor.from_pretrained(
            '''hf-internal-testing/test_dynamic_image_processor'''     ,      trust_remote_code=UpperCAmelCase		)

       lowercase					:   Union[str, Any]				  =AutoImageProcessor.from_pretrained(
           '''hf-internal-testing/test_dynamic_image_processor'''     ,      trust_remote_code=UpperCAmelCase		)
       self.assertEqual(image_processor.__class__.__name__     ,      '''NewImageProcessor'''		)

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






      def 				A__      ( self			:		Union[str, Any]		)  ->  Dict:


       '''simple docstring'''

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

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

         lowercase					:   Optional[int]				  =CustomImageProcessor.from_pretrained(UpperCAmelCase		)

        # 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(UpperCAmelCase		)
         lowercase					:   Dict				  =AutoImageProcessor.from_pretrained(UpperCAmelCase		)
         self.assertIsInstance(UpperCAmelCase     ,      UpperCAmelCase		)

       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 				A__      ( self			:		Any		)  ->  Any:


       '''simple docstring'''

       class UpperCAmelCase_					(    __A				):




             """simple docstring"""




             UpperCamelCase_								=			True

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

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



