
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 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       a_      :	Tuple      =							0


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       a_      :	List[str]      =							AutoImageProcessor.from_pretrained("""openai/clip-vit-base-patch32""" )
       self.assertIsInstance(UpperCAmelCase_							,		UpperCAmelCase_ )


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       with tempfile.TemporaryDirectory() as tmpdirname:
         a_      :	str      =							Path(UpperCAmelCase_ ) / """preprocessor_config.json"""
         a_      :	Union[str, 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""" ) )

         a_      :	List[str]      =							AutoImageProcessor.from_pretrained(UpperCAmelCase_ )
         self.assertIsInstance(UpperCAmelCase_							,		UpperCAmelCase_ )


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       with tempfile.TemporaryDirectory() as tmpdirname:
         a_      :	str      =							Path(UpperCAmelCase_ ) / """preprocessor_config.json"""
         a_      :	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""" ) )

         a_      :	Optional[int]      =							AutoImageProcessor.from_pretrained(UpperCAmelCase_ )
         self.assertIsInstance(UpperCAmelCase_							,		UpperCAmelCase_ )


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       with tempfile.TemporaryDirectory() as tmpdirname:
         a_      :	Tuple      =							CLIPConfig()

         # Create a dummy config file with image_proceesor_type
         a_      :	int      =							Path(UpperCAmelCase_ ) / """preprocessor_config.json"""
         a_      :	List[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""" ) )

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

         config_dict.pop("""image_processor_type""" )
         a_      :	Any      =							CLIPImageProcessor(**UpperCAmelCase_ )

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

         a_      :	Optional[int]      =							AutoImageProcessor.from_pretrained(UpperCAmelCase_ )

         # make sure private variable is not incorrectly saved
         a_      :	Dict      =							json.loads(config.to_json_string() )
         self.assertTrue("""_processor_class""" not in dict_as_saved )

       self.assertIsInstance(UpperCAmelCase_							,		UpperCAmelCase_ )


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

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

         a_      :	Optional[int]      =							AutoImageProcessor.from_pretrained(UpperCAmelCase_ )
         self.assertIsInstance(UpperCAmelCase_							,		UpperCAmelCase_ )


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

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


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

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


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

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


     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       with self.assertRaises(UpperCAmelCase_ ):
         a_      :	Tuple      =							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_ ):
         a_      :	Dict      =							AutoImageProcessor.from_pretrained(
             """hf-internal-testing/test_dynamic_image_processor"""							,		trust_remote_code=UpperCAmelCase_ )

       a_      :	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_ )
         a_      :	Any      =							AutoImageProcessor.from_pretrained(UpperCAmelCase_							,		trust_remote_code=UpperCAmelCase_ )
       self.assertEqual(reloaded_image_processor.__class__.__name__							,		"""NewImageProcessor""" )


     def 							_lowerCAmelCase  (      self ):

       '''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:
           a_      :	str      =							Path(UpperCAmelCase_ ) / """preprocessor_config.json"""
           a_      :	Union[str, Any]      =							Path(UpperCAmelCase_ ) / """config.json"""
           json.dump(
               {"""feature_extractor_type""": """CLIPFeatureExtractor""", """processor_class""": """CLIPProcessor"""}							,		open(UpperCAmelCase_							,		"""w""" )							,		)
           json.dump({"""model_type""": """clip"""}							,		open(UpperCAmelCase_							,		"""w""" ) )

           a_      :	Tuple      =							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_ )
           a_      :	int      =							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 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       class  _UpperCAmelCase ( __UpperCAmelCase    ):

            """simple docstring"""

            a_    	=					True

       try:
         AutoConfig.register("""custom"""							,		UpperCAmelCase_ )
         AutoImageProcessor.register(UpperCAmelCase_							,		UpperCAmelCase_ )
         # If remote code is not set, the default is to use local
         a_      :	int      =							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_      :	Dict      =							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
         a_      :	Optional[int]      =							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]




'''simple docstring'''

from torch import nn






def 	_snake_case						(      A_       :    Dict   ):
  """simple docstring"""







  if act_fn in ["swish", "silu"]:
    return nn.SiLU()
  elif act_fn == "mish":
    return nn.Mish()
  elif act_fn == "gelu":
    return nn.GELU()
  else:
    raise ValueError(f'''Unsupported activation function: {act_fn}'''   )


