


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 							lowercase  (						unittest.TestCase			):







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







     def 							lowercase__       (						self :						List[str]      ):
           SCREAMING_SNAKE_CASE__       :  int						     =		AutoImageProcessor.from_pretrained('''openai/clip-vit-base-patch32'''      )
           self.assertIsInstance(_lowercase   ,   _lowercase      )







     def 							lowercase__       (						self :						Any      ):
           with tempfile.TemporaryDirectory() as tmpdirname:
                 SCREAMING_SNAKE_CASE__       :  Union[str, Any]						     =		Path(_lowercase      ) / '''preprocessor_config.json'''
                 SCREAMING_SNAKE_CASE__       :  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'''      )      )

                 SCREAMING_SNAKE_CASE__       :  Tuple						     =		AutoImageProcessor.from_pretrained(_lowercase      )
                 self.assertIsInstance(_lowercase   ,   _lowercase      )







     def 							lowercase__       (						self :						Dict      ):
           # Ensure we can load the image processor from the feature extractor config
           with tempfile.TemporaryDirectory() as tmpdirname:
                 SCREAMING_SNAKE_CASE__       :  List[str]						     =		Path(_lowercase      ) / '''preprocessor_config.json'''
                 SCREAMING_SNAKE_CASE__       :  Optional[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'''      )      )

                 SCREAMING_SNAKE_CASE__       :  Any						     =		AutoImageProcessor.from_pretrained(_lowercase      )
                 self.assertIsInstance(_lowercase   ,   _lowercase      )







     def 							lowercase__       (						self :						List[str]      ):
           with tempfile.TemporaryDirectory() as tmpdirname:
                 SCREAMING_SNAKE_CASE__       :  int						     =		CLIPConfig()

                 # Create a dummy config file with image_proceesor_type
                 SCREAMING_SNAKE_CASE__       :  Union[str, Any]						     =		Path(_lowercase      ) / '''preprocessor_config.json'''
                 SCREAMING_SNAKE_CASE__       :  Optional[int]						     =		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
                 SCREAMING_SNAKE_CASE__       :  str						     =		AutoImageProcessor.from_pretrained(_lowercase      ).to_dict()

                 config_dict.pop('''image_processor_type'''      )
                 SCREAMING_SNAKE_CASE__       :  List[str]						     =		CLIPImageProcessor(**_lowercase      )

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

                 SCREAMING_SNAKE_CASE__       :  Union[str, Any]						     =		AutoImageProcessor.from_pretrained(_lowercase      )

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

           self.assertIsInstance(_lowercase   ,   _lowercase      )







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

                 SCREAMING_SNAKE_CASE__       :  Optional[int]						     =		AutoImageProcessor.from_pretrained(_lowercase      )
                 self.assertIsInstance(_lowercase   ,   _lowercase      )







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







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







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







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

           SCREAMING_SNAKE_CASE__       :  Optional[Any]						     =		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      )
                 SCREAMING_SNAKE_CASE__       :  Any						     =		AutoImageProcessor.from_pretrained(_lowercase   ,   trust_remote_code=_lowercase      )
           self.assertEqual(reloaded_image_processor.__class__.__name__   ,   '''NewImageProcessor'''      )







     def 							lowercase__       (						self :						List[str]      ):
           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:
                       SCREAMING_SNAKE_CASE__       :  Union[str, Any]						     =		Path(_lowercase      ) / '''preprocessor_config.json'''
                       SCREAMING_SNAKE_CASE__       :  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'''      )      )

                       SCREAMING_SNAKE_CASE__       :  List[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      )
                       SCREAMING_SNAKE_CASE__       :  List[Any]						     =		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 							lowercase__       (						self :						Optional[Any]      ):

           class 							lowercase  (						_UpperCAmelCase			):
                lowerCamelCase			:			Union[str, Any]      = True

           try:
                 AutoConfig.register('''custom'''   ,   _lowercase      )
                 AutoImageProcessor.register(_lowercase   ,   _lowercase      )
                 # If remote code is not set, the default is to use local
                 SCREAMING_SNAKE_CASE__       :  Optional[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.
                 SCREAMING_SNAKE_CASE__       :  List[Any]						     =		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
                 SCREAMING_SNAKE_CASE__       :  Any						     =		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]












'''simple docstring'''


def 						lowerCamelCase__   (				a							):
						__snake_case						 =   int(a							)
						if n_element < 1:
												__snake_case						 =   ValueError('a should be a positive number'							)
												raise my_error

						__snake_case						 =   [1]
						__snake_case ,       __snake_case ,       __snake_case						 =   (0, 0, 0)
						__snake_case						 =   1
						while index < n_element:
												while hamming_list[i] * 2 <= hamming_list[-1]:
																		i += 1
												while hamming_list[j] * 3 <= hamming_list[-1]:
																		j += 1
												while hamming_list[k] * 5 <= hamming_list[-1]:
																		k += 1
												hamming_list.append(
												    min(hamming_list[i] * 2    ,	hamming_list[j] * 3    ,	hamming_list[k] * 5							)							)
												index += 1
						return hamming_list


if __name__ == "__main__":
	_lowercase  =			input("""Enter the last number (nth term) of the Hamming Number Series: """)
	print("""Formula of Hamming Number Series => 2^i * 3^j * 5^k""")
	_lowercase  =			hamming(int(n))
	print("""-----------------------------------------------------""")
	print(f'''The list with nth numbers is: {hamming_numbers}''')
	print("""-----------------------------------------------------""")

