

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    lowercase_	(							self		:	int      )	->							Optional[int]:
       SCREAMING_SNAKE_CASE__					=					0






  def    lowercase_	(							self		:	Any      )	->							Union[str, Any]:
       SCREAMING_SNAKE_CASE__					=					AutoImageProcessor.from_pretrained('''openai/clip-vit-base-patch32'''      )
       self.assertIsInstance(__lowerCamelCase			,     __lowerCamelCase      )






  def    lowercase_	(							self		:	int      )	->							Optional[Any]:
       with tempfile.TemporaryDirectory() as tmpdirname:
            SCREAMING_SNAKE_CASE__					=					Path(__lowerCamelCase      ) / '''preprocessor_config.json'''
            SCREAMING_SNAKE_CASE__					=					Path(__lowerCamelCase      ) / '''config.json'''
            json.dump(
                {'''image_processor_type''': '''CLIPImageProcessor''', '''processor_class''': '''CLIPProcessor'''}			,     open(__lowerCamelCase			,     '''w'''      )			,     )
            json.dump({'''model_type''': '''clip'''}			,     open(__lowerCamelCase			,     '''w'''      )      )

            SCREAMING_SNAKE_CASE__					=					AutoImageProcessor.from_pretrained(__lowerCamelCase      )
            self.assertIsInstance(__lowerCamelCase			,     __lowerCamelCase      )






  def    lowercase_	(							self		:	List[Any]      )	->							Optional[Any]:
       # Ensure we can load the image processor from the feature extractor config
       with tempfile.TemporaryDirectory() as tmpdirname:
            SCREAMING_SNAKE_CASE__					=					Path(__lowerCamelCase      ) / '''preprocessor_config.json'''
            SCREAMING_SNAKE_CASE__					=					Path(__lowerCamelCase      ) / '''config.json'''
            json.dump(
                {'''feature_extractor_type''': '''CLIPFeatureExtractor''', '''processor_class''': '''CLIPProcessor'''}			,     open(__lowerCamelCase			,     '''w'''      )			,     )
            json.dump({'''model_type''': '''clip'''}			,     open(__lowerCamelCase			,     '''w'''      )      )

            SCREAMING_SNAKE_CASE__					=					AutoImageProcessor.from_pretrained(__lowerCamelCase      )
            self.assertIsInstance(__lowerCamelCase			,     __lowerCamelCase      )






  def    lowercase_	(							self		:	Optional[int]      )	->							Any:
       with tempfile.TemporaryDirectory() as tmpdirname:
            SCREAMING_SNAKE_CASE__					=					CLIPConfig()

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

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

            config_dict.pop('''image_processor_type'''      )
            SCREAMING_SNAKE_CASE__					=					CLIPImageProcessor(**__lowerCamelCase      )

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

            SCREAMING_SNAKE_CASE__					=					AutoImageProcessor.from_pretrained(__lowerCamelCase      )

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

       self.assertIsInstance(__lowerCamelCase			,     __lowerCamelCase      )






  def    lowercase_	(							self		:	str      )	->							Optional[Any]:
       with tempfile.TemporaryDirectory() as tmpdirname:
            SCREAMING_SNAKE_CASE__					=					Path(__lowerCamelCase      ) / '''preprocessor_config.json'''
            json.dump(
                {'''image_processor_type''': '''CLIPImageProcessor''', '''processor_class''': '''CLIPProcessor'''}			,     open(__lowerCamelCase			,     '''w'''      )			,     )

            SCREAMING_SNAKE_CASE__					=					AutoImageProcessor.from_pretrained(__lowerCamelCase      )
            self.assertIsInstance(__lowerCamelCase			,     __lowerCamelCase      )






  def    lowercase_	(							self		:	int      )	->							Any:
       with self.assertRaisesRegex(
           __lowerCamelCase			,     '''clip-base is not a local folder and is not a valid model identifier'''      ):
            SCREAMING_SNAKE_CASE__					=					AutoImageProcessor.from_pretrained('''clip-base'''      )






  def    lowercase_	(							self		:	Dict      )	->							List[Any]:
       with self.assertRaisesRegex(
           __lowerCamelCase			,     r'''aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'''      ):
            SCREAMING_SNAKE_CASE__					=					AutoImageProcessor.from_pretrained(__lowerCamelCase			,     revision='''aaaaaa'''      )






  def    lowercase_	(							self		:	Tuple      )	->							Any:
       with self.assertRaisesRegex(
           __lowerCamelCase			,     '''hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json.'''			,     ):
            SCREAMING_SNAKE_CASE__					=					AutoImageProcessor.from_pretrained('''hf-internal-testing/config-no-model'''      )






  def    lowercase_	(							self		:	Union[str, Any]      )	->							Tuple:
       # If remote code is not set, we will time out when asking whether to load the model.
       with self.assertRaises(__lowerCamelCase      ):
            SCREAMING_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(__lowerCamelCase      ):
            SCREAMING_SNAKE_CASE__					=					AutoImageProcessor.from_pretrained(
                '''hf-internal-testing/test_dynamic_image_processor'''			,     trust_remote_code=__lowerCamelCase      )

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

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






  def    lowercase_	(							self		:	Dict      )	->							List[str]:
       try:
            AutoConfig.register('''custom'''			,     __lowerCamelCase      )
            AutoImageProcessor.register(__lowerCamelCase			,     __lowerCamelCase      )
            # Trying to register something existing in the Transformers library will raise an error
            with self.assertRaises(__lowerCamelCase      ):
                 AutoImageProcessor.register(__lowerCamelCase			,     __lowerCamelCase      )

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

                 SCREAMING_SNAKE_CASE__					=					CustomImageProcessor.from_pretrained(__lowerCamelCase      )

            # 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(__lowerCamelCase      )
                 SCREAMING_SNAKE_CASE__					=					AutoImageProcessor.from_pretrained(__lowerCamelCase      )
                 self.assertIsInstance(__lowerCamelCase			,     __lowerCamelCase      )

       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    lowercase_	(							self		:	Optional[Any]      )	->							List[Any]:






       class  UpperCAmelCase__	( A__ ):






         """simple docstring"""


         a     =      True

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

            # If remote is enabled, we load from the Hub
            SCREAMING_SNAKE_CASE__					=					AutoImageProcessor.from_pretrained(
                '''hf-internal-testing/test_dynamic_image_processor'''			,     trust_remote_code=__lowerCamelCase      )
            self.assertEqual(image_processor.__class__.__name__			,     '''NewImageProcessor'''      )
            self.assertTrue(not hasattr(__lowerCamelCase			,     '''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 random
def        UpperCAmelCase_     (		_A   ,	_A   ,	_A       ):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__					=					a[left_index]
     SCREAMING_SNAKE_CASE__					=					left_index + 1
     for j in range(left_index + 1   ,	_A       ):
          if a[j] < pivot:
               SCREAMING_SNAKE_CASE__,SCREAMING_SNAKE_CASE__					=					a[i], a[j]
               i += 1
     SCREAMING_SNAKE_CASE__,SCREAMING_SNAKE_CASE__					=					a[i - 1], a[left_index]
     return i - 1
def        UpperCAmelCase_     (		_A   ,	_A   ,	_A       ):





     '''simple docstring'''




     if left < right:
          SCREAMING_SNAKE_CASE__					=					random.randint(_A   ,	right - 1       )
          SCREAMING_SNAKE_CASE__,SCREAMING_SNAKE_CASE__					=					(
              a[left],
              a[pivot],
          )  # switches the pivot with the left most bound
          SCREAMING_SNAKE_CASE__					=					partition(_A   ,	_A   ,	_A       )
          quick_sort_random(
              _A   ,	_A   ,	_A       )  # recursive quicksort to the left of the pivot point
          quick_sort_random(
              _A   ,	pivot_index + 1   ,	_A       )  # recursive quicksort to the right of the pivot point
def        UpperCAmelCase_     (		):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__					=					input('''Enter numbers separated by a comma:\n'''       ).strip()
     SCREAMING_SNAKE_CASE__					=					[int(_A       ) for item in user_input.split(''','''       )]

     quick_sort_random(_A   ,	0   ,	len(_A       )       )

     print(_A       )


if __name__ == "__main__":
       main()


