






'''simple docstring'''




from __future__ import annotations

def 						__UpperCAmelCase							(			__magic_name__  ,__magic_name__ = None  ,__magic_name__ = None  ,__magic_name__ = False  ,)->     tuple[int, float, str]:



			"""simple docstring"""



			snake_case_					:       Any =							cipher_alphabet or [chr(lowerCAmelCase_    ) for i in range(97  ,123    )]

			# If the argument is None or the user provided an empty dictionary
			if not frequencies_dict:
						# Frequencies of letters in the english language (how much they show up)
						snake_case_					:       Optional[Any] =							{
						    "a": 0.08_497,
						    "b": 0.01_492,
						    "c": 0.02_202,
						    "d": 0.04_253,
						    "e": 0.11_162,
						    "f": 0.02_228,
						    "g": 0.02_015,
						    "h": 0.06_094,
						    "i": 0.07_546,
						    "j": 0.00_153,
						    "k": 0.01_292,
						    "l": 0.04_025,
						    "m": 0.02_406,
						    "n": 0.06_749,
						    "o": 0.07_507,
						    "p": 0.01_929,
						    "q": 0.00_095,
						    "r": 0.07_587,
						    "s": 0.06_327,
						    "t": 0.09_356,
						    "u": 0.02_758,
						    "v": 0.00_978,
						    "w": 0.02_560,
						    "x": 0.00_150,
						    "y": 0.01_994,
						    "z": 0.00_077,
						}
			else:
						# Custom frequencies dictionary
						snake_case_					:       int =							frequencies_dict

			if not case_sensitive:
						snake_case_					:       Optional[int] =							ciphertext.lower()

			# Chi squared statistic values
			snake_case_					:       List[str] =							{}

			# cycle through all of the shifts
			for shift in range(len(lowerCAmelCase_    )    ):
						snake_case_					:       Dict =							""

						# decrypt the message with the shift
						for letter in ciphertext:
									try:
												# Try to index the letter in the alphabet
												snake_case_					:       List[str] =							(alphabet_letters.index(letter.lower()    ) - shift) % len(
												    lowerCAmelCase_    )
												decrypted_with_shift += (
												    alphabet_letters[new_key].upper()
												    if case_sensitive and letter.isupper()
												    else alphabet_letters[new_key]
												)
									except ValueError:
												# Append the character if it isn't in the alphabet
												decrypted_with_shift += letter

						snake_case_					:       List[str] =							0.0

						# Loop through each letter in the decoded message with the shift
						for letter in decrypted_with_shift:
									if case_sensitive:
												snake_case_					:       Optional[int] =							letter.lower()
												if letter in frequencies:
															# Get the amount of times the letter occurs in the message
															snake_case_					:       Optional[int] =							decrypted_with_shift.lower().count(lowerCAmelCase_    )

															# Get the excepcted amount of times the letter should appear based
															# on letter frequencies
															snake_case_					:       List[str] =							frequencies[letter] * occurrences

															# Complete the chi squared statistic formula
															snake_case_					:       Dict =							((occurrences - expected) ** 2) / expected

															# Add the margin of error to the total chi squared statistic
															chi_squared_statistic += chi_letter_value
									else:
												if letter.lower() in frequencies:
															# Get the amount of times the letter occurs in the message
															snake_case_					:       Optional[int] =							decrypted_with_shift.count(lowerCAmelCase_    )

															# Get the excepcted amount of times the letter should appear based
															# on letter frequencies
															snake_case_					:       Tuple =							frequencies[letter] * occurrences

															# Complete the chi squared statistic formula
															snake_case_					:       Dict =							((occurrences - expected) ** 2) / expected

															# Add the margin of error to the total chi squared statistic
															chi_squared_statistic += chi_letter_value

												# Add the data to the chi_squared_statistic_values dictionary
						snake_case_					:       List[str] =							(
						    chi_squared_statistic,
						    decrypted_with_shift,
						)

			# Get the most likely cipher by finding the cipher with the smallest chi squared
			# statistic
			def chi_squared_statistic_values_sorting_key(__magic_name__    ) -> tuple[float, str]:
						return chi_squared_statistic_values[key]

			snake_case_					:       List[str] =							min(
			    lowerCAmelCase_  ,key=lowerCAmelCase_  ,)

			# Get all the data from the most likely cipher (key, decoded message)
			(
			    (
			    snake_case_     
			),						(
			    snake_case_     
			),						     
			)					:       Any =							chi_squared_statistic_values[most_likely_cipher]

			# Return the data on the most likely shift
			return (
			    most_likely_cipher,
			    most_likely_cipher_chi_squared_value,
			    decoded_most_likely_cipher,
			)









"""simple docstring"""






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

import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_bert import BertConfig
from transformers.models.roberta.configuration_roberta import RobertaConfig
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


snake_case   					=				get_tests_dir('''fixtures/dummy-config.json''')



class     UpperCAmelCase    (	unittest.TestCase  ):



   def    __UpperCAmelCase    (       self    :	Any				):



     """simple docstring"""
     _snake_case   	=      0



   def    __UpperCAmelCase    (       self    :	Optional[Any]				):



     """simple docstring"""
     self.assertIsNotNone(transformers.models.auto.__spec__				)
     self.assertIsNotNone(importlib.util.find_spec('''transformers.models.auto'''				)				)



   def    __UpperCAmelCase    (       self    :	List[str]				):



     """simple docstring"""
     _snake_case   	=      AutoConfig.from_pretrained('''bert-base-uncased'''				)
     self.assertIsInstance(__lowerCamelCase							,       __lowerCamelCase				)



   def    __UpperCAmelCase    (       self    :	Union[str, Any]				):



     """simple docstring"""
     _snake_case   	=      AutoConfig.from_pretrained(__lowerCamelCase				)
     self.assertIsInstance(__lowerCamelCase							,       __lowerCamelCase				)



   def    __UpperCAmelCase    (       self    :	int				):



     """simple docstring"""
     _snake_case   	=      AutoConfig.from_pretrained(__lowerCamelCase				)
     self.assertIsInstance(__lowerCamelCase							,       __lowerCamelCase				)



   def    __UpperCAmelCase    (       self    :	Union[str, Any]				):



     """simple docstring"""
     _snake_case   	=      AutoConfig.for_model('''roberta'''				)
     self.assertIsInstance(__lowerCamelCase							,       __lowerCamelCase				)



   def    __UpperCAmelCase    (       self    :	Dict				):



     """simple docstring"""
     with tempfile.TemporaryDirectory() as tmp_dir:
       # This model name contains bert and roberta, but roberta ends up being picked.
       _snake_case   	=      os.path.join(__lowerCamelCase							,       '''fake-roberta'''				)
       os.makedirs(__lowerCamelCase							,       exist_ok=__lowerCamelCase				)
       with open(os.path.join(__lowerCamelCase							,       '''config.json'''				)							,       '''w'''				) as f:
         f.write(json.dumps({}				)				)
       _snake_case   	=      AutoConfig.from_pretrained(__lowerCamelCase				)
       self.assertEqual(type(__lowerCamelCase				)							,       __lowerCamelCase				)



   def    __UpperCAmelCase    (       self    :	Optional[Any]				):



     """simple docstring"""
     try:
       AutoConfig.register('''custom'''							,       __lowerCamelCase				)
       # Wrong model type will raise an error
       with self.assertRaises(__lowerCamelCase				):
         AutoConfig.register('''model'''							,       __lowerCamelCase				)
       # Trying to register something existing in the Transformers library will raise an error
       with self.assertRaises(__lowerCamelCase				):
         AutoConfig.register('''bert'''							,       __lowerCamelCase				)

       # Now that the config is registered, it can be used as any other config with the auto-API
       _snake_case   	=      CustomConfig()
       with tempfile.TemporaryDirectory() as tmp_dir:
         config.save_pretrained(__lowerCamelCase				)
         _snake_case   	=      AutoConfig.from_pretrained(__lowerCamelCase				)
         self.assertIsInstance(__lowerCamelCase							,       __lowerCamelCase				)

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



   def    __UpperCAmelCase    (       self    :	Optional[int]				):



     """simple docstring"""
     with self.assertRaisesRegex(
         __lowerCamelCase							,       '''bert-base is not a local folder and is not a valid model identifier'''				):
       _snake_case   	=      AutoConfig.from_pretrained('''bert-base'''				)



   def    __UpperCAmelCase    (       self    :	Dict				):



     """simple docstring"""
     with self.assertRaisesRegex(
         __lowerCamelCase							,       R'''aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'''				):
       _snake_case   	=      AutoConfig.from_pretrained(__lowerCamelCase							,       revision='''aaaaaa'''				)



   def    __UpperCAmelCase    (       self    :	Dict				):



     """simple docstring"""
     with self.assertRaisesRegex(
         __lowerCamelCase							,       '''hf-internal-testing/no-config-test-repo does not appear to have a file named config.json.'''							,       ):
       _snake_case   	=      AutoConfig.from_pretrained('''hf-internal-testing/no-config-test-repo'''				)



   def    __UpperCAmelCase    (       self    :	str				):



     """simple docstring"""
     # If remote code is not set, we will time out when asking whether to load the model.
     with self.assertRaises(__lowerCamelCase				):
       _snake_case   	=      AutoConfig.from_pretrained('''hf-internal-testing/test_dynamic_model'''				)
     # If remote code is disabled, we can't load this config.
     with self.assertRaises(__lowerCamelCase				):
       _snake_case   	=      AutoConfig.from_pretrained('''hf-internal-testing/test_dynamic_model'''							,       trust_remote_code=__lowerCamelCase				)

     _snake_case   	=      AutoConfig.from_pretrained('''hf-internal-testing/test_dynamic_model'''							,       trust_remote_code=__lowerCamelCase				)
     self.assertEqual(config.__class__.__name__							,       '''NewModelConfig'''				)

     # Test config can be reloaded.
     with tempfile.TemporaryDirectory() as tmp_dir:
       config.save_pretrained(__lowerCamelCase				)
       _snake_case   	=      AutoConfig.from_pretrained(__lowerCamelCase							,       trust_remote_code=__lowerCamelCase				)
     self.assertEqual(reloaded_config.__class__.__name__							,       '''NewModelConfig'''				)





   def    __UpperCAmelCase    (       self    :	Union[str, Any]				):



     """simple docstring"""



     class     UpperCAmelCase    (	__SCREAMING_SNAKE_CASE  ):
        A__		:	List[Any]           =  '''new-model'''

     try:
       AutoConfig.register('''new-model'''							,       __lowerCamelCase				)
       # If remote code is not set, the default is to use local
       _snake_case   	=      AutoConfig.from_pretrained('''hf-internal-testing/test_dynamic_model'''				)
       self.assertEqual(config.__class__.__name__							,       '''NewModelConfigLocal'''				)

       # If remote code is disabled, we load the local one.
       _snake_case   	=      AutoConfig.from_pretrained('''hf-internal-testing/test_dynamic_model'''							,       trust_remote_code=__lowerCamelCase				)
       self.assertEqual(config.__class__.__name__							,       '''NewModelConfigLocal'''				)

       # If remote is enabled, we load from the Hub
       _snake_case   	=      AutoConfig.from_pretrained('''hf-internal-testing/test_dynamic_model'''							,       trust_remote_code=__lowerCamelCase				)
       self.assertEqual(config.__class__.__name__							,       '''NewModelConfig'''				)

     finally:
       if "new-model" in CONFIG_MAPPING._extra_content:
         del CONFIG_MAPPING._extra_content["new-model"]





