
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


SCREAMING_SNAKE_CASE							:List[str]							 =				{'configuration_mra': ['MRA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MraConfig']}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					SCREAMING_SNAKE_CASE							:List[str]							 =				[
					    'MRA_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'MraForMaskedLM',
					    'MraForMultipleChoice',
					    'MraForQuestionAnswering',
					    'MraForSequenceClassification',
					    'MraForTokenClassification',
					    'MraLayer',
					    'MraModel',
					    'MraPreTrainedModel',
					]


if TYPE_CHECKING:
					from .configuration_mra import MRA_PRETRAINED_CONFIG_ARCHIVE_MAP, MraConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_mra import (
										    MRA_PRETRAINED_MODEL_ARCHIVE_LIST,
										    MraForMaskedLM,
										    MraForMultipleChoice,
										    MraForQuestionAnswering,
										    MraForSequenceClassification,
										    MraForTokenClassification,
										    MraLayer,
										    MraModel,
										    MraPreTrainedModel,
										)
else:
					import sys

					SCREAMING_SNAKE_CASE							:List[str]							 =				_LazyModule(__name__, globals()['__file__'], _import_structure)







import random

class 		UpperCamelCase__ :



     '''simple docstring'''

     @staticmethod
     def 				SCREAMING_SNAKE_CASE__  (							lowerCamelCase__						:    str       )     ->		tuple[list[int], list[int]]:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						[ord(lowerCamelCase__       ) for i in text]
           SCREAMING_SNAKE_CASE		=						[]
           SCREAMING_SNAKE_CASE		=						[]
           for i in plain:
                 SCREAMING_SNAKE_CASE		=						random.randint(1						,300       )
                 SCREAMING_SNAKE_CASE		=						(i + k) * k
                 cipher.append(lowerCamelCase__       )
                 key.append(lowerCamelCase__       )
           return cipher, key






     @staticmethod
     def 				SCREAMING_SNAKE_CASE__  (							lowerCamelCase__						:    list[int]						,lowerCamelCase__						:    list[int]       )     ->		str:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						[]
           for i in range(len(lowerCamelCase__       )       ):
                 SCREAMING_SNAKE_CASE		=						int((cipher[i] - (key[i]) ** 2) / key[i]       )
                 plain.append(chr(lowerCamelCase__       )       )
           return "".join(lowerCamelCase__       )


if __name__ == "__main__":
      SCREAMING_SNAKE_CASE_   ,						SCREAMING_SNAKE_CASE_						   =       Onepad().encrypt("""Hello""")
      print(c, k)
      print(Onepad().decrypt(c, k))


