



import json
import sys
import tempfile
import unittest
from pathlib import Path

import transformers
from transformers import (
    CONFIG_MAPPING,
    FEATURE_EXTRACTOR_MAPPING,
    AutoConfig,
    AutoFeatureExtractor,
    WavaVecaConfig,
    WavaVecaFeatureExtractor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, get_tests_dir


sys.path.append(str(Path(__file__).parent.parent.parent.parent / "utils"))

from test_module.custom_configuration import CustomConfig  # noqa E402
from test_module.custom_feature_extraction import CustomFeatureExtractor  # noqa E402


__lowerCamelCase     :							int  							=				get_tests_dir("fixtures")
__lowerCamelCase     :							str  							=				get_tests_dir("fixtures/dummy_feature_extractor_config.json")
__lowerCamelCase     :							Any  							=				get_tests_dir("fixtures/dummy-config.json")





class  __magic_name__   (							unittest.TestCase						):






		def SCREAMING_SNAKE_CASE_			(						self      :     Optional[Any]      )				->					Optional[int]:
								'''simple docstring'''







								UpperCAmelCase         =     0






		def SCREAMING_SNAKE_CASE_			(						self      :     Optional[int]      )				->					List[Any]:
								'''simple docstring'''







								UpperCAmelCase         =     AutoFeatureExtractor.from_pretrained("facebook/wav2vec2-base-960h"      )
								self.assertIsInstance(UpperCamelCase__				,		UpperCamelCase__      )






		def SCREAMING_SNAKE_CASE_			(						self      :     Optional[Any]      )				->					Optional[int]:
								'''simple docstring'''







								UpperCAmelCase         =     AutoFeatureExtractor.from_pretrained(UpperCamelCase__      )
								self.assertIsInstance(UpperCamelCase__				,		UpperCamelCase__      )






		def SCREAMING_SNAKE_CASE_			(						self      :     Any      )				->					Union[str, Any]:
								'''simple docstring'''







								with tempfile.TemporaryDirectory() as tmpdirname:
														UpperCAmelCase         =     WavaVecaConfig()

														# remove feature_extractor_type to make sure config.json alone is enough to load feature processor locally
														UpperCAmelCase         =     AutoFeatureExtractor.from_pretrained(UpperCamelCase__      ).to_dict()

														config_dict.pop("feature_extractor_type"      )
														UpperCAmelCase         =     WavaVecaFeatureExtractor(**UpperCamelCase__      )

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

														UpperCAmelCase         =     AutoFeatureExtractor.from_pretrained(UpperCamelCase__      )

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

								self.assertIsInstance(UpperCamelCase__				,		UpperCamelCase__      )






		def SCREAMING_SNAKE_CASE_			(						self      :     Any      )				->					Tuple:
								'''simple docstring'''







								UpperCAmelCase         =     AutoFeatureExtractor.from_pretrained(UpperCamelCase__      )
								self.assertIsInstance(UpperCamelCase__				,		UpperCamelCase__      )






		def SCREAMING_SNAKE_CASE_			(						self      :     Union[str, Any]      )				->					Optional[int]:
								'''simple docstring'''







								with self.assertRaisesRegex(
								    UpperCamelCase__				,		"bert-base is not a local folder and is not a valid model identifier"      ):
														UpperCAmelCase         =     AutoFeatureExtractor.from_pretrained("bert-base"      )






		def SCREAMING_SNAKE_CASE_			(						self      :     Dict      )				->					Optional[int]:
								'''simple docstring'''







								with self.assertRaisesRegex(
								    UpperCamelCase__				,		R"aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"      ):
														UpperCAmelCase         =     AutoFeatureExtractor.from_pretrained(UpperCamelCase__				,		revision="aaaaaa"      )






		def SCREAMING_SNAKE_CASE_			(						self      :     Optional[int]      )				->					Optional[Any]:
								'''simple docstring'''







								with self.assertRaisesRegex(
								    UpperCamelCase__				,		"hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json."				,		):
														UpperCAmelCase         =     AutoFeatureExtractor.from_pretrained("hf-internal-testing/config-no-model"      )






		def SCREAMING_SNAKE_CASE_			(						self      :     str      )				->					int:
								'''simple docstring'''







								with self.assertRaises(UpperCamelCase__      ):
														UpperCAmelCase         =     AutoFeatureExtractor.from_pretrained(
														    "hf-internal-testing/test_dynamic_feature_extractor"      )
								# If remote code is disabled, we can't load this config.
								with self.assertRaises(UpperCamelCase__      ):
														UpperCAmelCase         =     AutoFeatureExtractor.from_pretrained(
														    "hf-internal-testing/test_dynamic_feature_extractor"				,		trust_remote_code=UpperCamelCase__      )

								UpperCAmelCase         =     AutoFeatureExtractor.from_pretrained(
								    "hf-internal-testing/test_dynamic_feature_extractor"				,		trust_remote_code=UpperCamelCase__      )
								self.assertEqual(feature_extractor.__class__.__name__				,		"NewFeatureExtractor"      )

								# Test feature extractor can be reloaded.
								with tempfile.TemporaryDirectory() as tmp_dir:
														feature_extractor.save_pretrained(UpperCamelCase__      )
														UpperCAmelCase         =     AutoFeatureExtractor.from_pretrained(UpperCamelCase__				,		trust_remote_code=UpperCamelCase__      )
								self.assertEqual(reloaded_feature_extractor.__class__.__name__				,		"NewFeatureExtractor"      )






		def SCREAMING_SNAKE_CASE_			(						self      :     int      )				->					Optional[Any]:
								'''simple docstring'''







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

														# Now that the config is registered, it can be used as any other config with the auto-API
														UpperCAmelCase         =     CustomFeatureExtractor.from_pretrained(UpperCamelCase__      )
														with tempfile.TemporaryDirectory() as tmp_dir:
																				feature_extractor.save_pretrained(UpperCamelCase__      )
																				UpperCAmelCase         =     AutoFeatureExtractor.from_pretrained(UpperCamelCase__      )
																				self.assertIsInstance(UpperCamelCase__				,		UpperCamelCase__      )

								finally:
														if "custom" in CONFIG_MAPPING._extra_content:
																				del CONFIG_MAPPING._extra_content["custom"]
														if CustomConfig in FEATURE_EXTRACTOR_MAPPING._extra_content:
																				del FEATURE_EXTRACTOR_MAPPING._extra_content[CustomConfig]







		def SCREAMING_SNAKE_CASE_			(						self      :     Optional[Any]      )				->					int:
								'''simple docstring'''







								class  __magic_name__   (							A__						):
										lowercase      :       int          =True

								try:
														AutoConfig.register("custom"				,		UpperCamelCase__      )
														AutoFeatureExtractor.register(UpperCamelCase__				,		UpperCamelCase__      )
														# If remote code is not set, the default is to use local
														UpperCAmelCase         =     AutoFeatureExtractor.from_pretrained(
														    "hf-internal-testing/test_dynamic_feature_extractor"      )
														self.assertEqual(feature_extractor.__class__.__name__				,		"NewFeatureExtractor"      )
														self.assertTrue(feature_extractor.is_local      )

														# If remote code is disabled, we load the local one.
														UpperCAmelCase         =     AutoFeatureExtractor.from_pretrained(
														    "hf-internal-testing/test_dynamic_feature_extractor"				,		trust_remote_code=UpperCamelCase__      )
														self.assertEqual(feature_extractor.__class__.__name__				,		"NewFeatureExtractor"      )
														self.assertTrue(feature_extractor.is_local      )

														# If remote is enabled, we load from the Hub
														UpperCAmelCase         =     AutoFeatureExtractor.from_pretrained(
														    "hf-internal-testing/test_dynamic_feature_extractor"				,		trust_remote_code=UpperCamelCase__      )
														self.assertEqual(feature_extractor.__class__.__name__				,		"NewFeatureExtractor"      )
														self.assertTrue(not hasattr(UpperCamelCase__				,		"is_local"      )      )

								finally:
														if "custom" in CONFIG_MAPPING._extra_content:
																				del CONFIG_MAPPING._extra_content["custom"]
														if CustomConfig in FEATURE_EXTRACTOR_MAPPING._extra_content:
																				del FEATURE_EXTRACTOR_MAPPING._extra_content[CustomConfig]








def    lowerCamelCase_(lowerCamelCase_    ,   lowerCamelCase_    ) ->       list[int]:
						UpperCAmelCase         =     int(lowerCamelCase_    )

						# Initialize Result
						UpperCAmelCase         =     []

						# Traverse through all denomination
						for denomination in reversed(lowerCamelCase_    ):
												# Find denominations
												while int(lowerCamelCase_    ) >= int(lowerCamelCase_    ):
																		total_value -= int(lowerCamelCase_    )
																		answer.append(lowerCamelCase_    )  # Append the "answers" array

						return answer


# Driver Code
if __name__ == "__main__":
		__lowerCamelCase     :							Optional[int]  							=				[]
		__lowerCamelCase     :							Dict  							=				"0"

		if (
		    input("Do you want to enter your denominations ? (yY/n): ").strip().lower()
		    == "y"
		):
				__lowerCamelCase     :							List[Any]  							=				int(input("Enter the number of denominations you want to add: ").strip())

				for i in range(0, n):
						denominations.append(int(input(F'''Denomination {i}: ''').strip()))
				__lowerCamelCase     :							str  							=				input("Enter the change you want to make in Indian Currency: ").strip()
		else:
				# All denominations of Indian Currency if user does not enter
				__lowerCamelCase     :							Optional[int]  							=				[1, 2, 5, 10, 20, 50, 100, 500, 2_000]
				__lowerCamelCase     :							Optional[int]  							=				input("Enter the change you want to make: ").strip()

		if int(value) == 0 or int(value) < 0:
				print("The total value cannot be zero or negative.")

		else:
				print(F'''Following is minimal change for {value}: ''')
				__lowerCamelCase     :							Union[str, Any]  							=				find_minimum_change(denominations, value)
				# Print result
				for i in range(len(answer)):
						print(answer[i], end=" ")



