


'''simple docstring'''






import json
from typing import TYPE_CHECKING, List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gpta import GPTaTokenizer


if TYPE_CHECKING:
		from transformers.pipelines.conversational import Conversation


__UpperCAmelCase					       =							logging.get_logger(__name__)

__UpperCAmelCase					       =							{'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

__UpperCAmelCase					       =							{
    '''vocab_file''': {
        '''gpt2''': '''https://huggingface.co/gpt2/resolve/main/vocab.json''',
        '''gpt2-medium''': '''https://huggingface.co/gpt2-medium/resolve/main/vocab.json''',
        '''gpt2-large''': '''https://huggingface.co/gpt2-large/resolve/main/vocab.json''',
        '''gpt2-xl''': '''https://huggingface.co/gpt2-xl/resolve/main/vocab.json''',
        '''distilgpt2''': '''https://huggingface.co/distilgpt2/resolve/main/vocab.json''',
    },
    '''merges_file''': {
        '''gpt2''': '''https://huggingface.co/gpt2/resolve/main/merges.txt''',
        '''gpt2-medium''': '''https://huggingface.co/gpt2-medium/resolve/main/merges.txt''',
        '''gpt2-large''': '''https://huggingface.co/gpt2-large/resolve/main/merges.txt''',
        '''gpt2-xl''': '''https://huggingface.co/gpt2-xl/resolve/main/merges.txt''',
        '''distilgpt2''': '''https://huggingface.co/distilgpt2/resolve/main/merges.txt''',
    },
    '''tokenizer_file''': {
        '''gpt2''': '''https://huggingface.co/gpt2/resolve/main/tokenizer.json''',
        '''gpt2-medium''': '''https://huggingface.co/gpt2-medium/resolve/main/tokenizer.json''',
        '''gpt2-large''': '''https://huggingface.co/gpt2-large/resolve/main/tokenizer.json''',
        '''gpt2-xl''': '''https://huggingface.co/gpt2-xl/resolve/main/tokenizer.json''',
        '''distilgpt2''': '''https://huggingface.co/distilgpt2/resolve/main/tokenizer.json''',
    },
}

__UpperCAmelCase					       =							{
    '''gpt2''': 1_024,
    '''gpt2-medium''': 1_024,
    '''gpt2-large''': 1_024,
    '''gpt2-xl''': 1_024,
    '''distilgpt2''': 1_024,
}




class 	a__       (							a__						):





							'''simple docstring'''






							lowercase__    :     str					=   VOCAB_FILES_NAMES
							lowercase__    :     List[str]					=   PRETRAINED_VOCAB_FILES_MAP
							lowercase__    :     Tuple					=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							lowercase__    :     Optional[Any]					=   ["input_ids", "attention_mask"]
							lowercase__    :     int					=   GPTaTokenizer







							def __init__(	self      ,					lowerCamelCase_=None      ,					lowerCamelCase_=None      ,					lowerCamelCase_=None      ,					lowerCamelCase_="<|endoftext|>"      ,					lowerCamelCase_="<|endoftext|>"      ,					lowerCamelCase_="<|endoftext|>"      ,					lowerCamelCase_=False      ,					**lowerCamelCase_      ,					) ->							Any:
														super().__init__(
														    lowerCamelCase_      ,					lowerCamelCase_      ,					tokenizer_file=lowerCamelCase_      ,					unk_token=lowerCamelCase_      ,					bos_token=lowerCamelCase_      ,					eos_token=lowerCamelCase_      ,					add_prefix_space=lowerCamelCase_      ,					**lowerCamelCase_      ,					)

														lowerCAmelCase__      =			kwargs.pop('''add_bos_token'''      ,					lowerCamelCase_     )

														lowerCAmelCase__      =			json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()     )
														if pre_tok_state.get('''add_prefix_space'''      ,					lowerCamelCase_     ) != add_prefix_space:
																					lowerCAmelCase__      =			getattr(lowerCamelCase_      ,					pre_tok_state.pop('''type'''     )     )
																					lowerCAmelCase__      =			add_prefix_space
																					lowerCAmelCase__      =			pre_tok_class(**lowerCamelCase_     )

														lowerCAmelCase__      =			add_prefix_space







							def 						__SCREAMING_SNAKE_CASE							(	self      ,					*lowerCamelCase_      ,					**lowerCamelCase_     ) ->							BatchEncoding:
														lowerCAmelCase__      =			kwargs.get('''is_split_into_words'''      ,					lowerCamelCase_     )
														assert self.add_prefix_space or not is_split_into_words, (
														    F"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
														    "to use it with pretokenized inputs."
														)

														return super()._batch_encode_plus(*lowerCamelCase_      ,					**lowerCamelCase_     )







							def 						__SCREAMING_SNAKE_CASE							(	self      ,					*lowerCamelCase_      ,					**lowerCamelCase_     ) ->							BatchEncoding:
														lowerCAmelCase__      =			kwargs.get('''is_split_into_words'''      ,					lowerCamelCase_     )

														assert self.add_prefix_space or not is_split_into_words, (
														    F"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
														    "to use it with pretokenized inputs."
														)

														return super()._encode_plus(*lowerCamelCase_      ,					**lowerCamelCase_     )







							def 						__SCREAMING_SNAKE_CASE							(	self      ,					lowerCamelCase_      ,					lowerCamelCase_ = None     ) ->							Tuple[str]:
														lowerCAmelCase__      =			self._tokenizer.model.save(lowerCamelCase_      ,					name=lowerCamelCase_     )
														return tuple(lowerCamelCase_     )







							def 						__SCREAMING_SNAKE_CASE							(	self      ,					lowerCamelCase_     ) ->							List[int]:
														lowerCAmelCase__      =			[]
														for is_user, text in conversation.iter_texts():
																					input_ids.extend(self.encode(lowerCamelCase_      ,					add_special_tokens=lowerCamelCase_     ) + [self.eos_token_id]     )

														if len(lowerCamelCase_     ) > self.model_max_length:
																					lowerCAmelCase__      =			input_ids[-self.model_max_length :]
														return input_ids



'''simple docstring'''






from __future__ import annotations




class 	a__       :





							'''simple docstring'''






							def __init__(	self      ,					lowerCamelCase_ = 0     ) ->							List[Any]:
														lowerCAmelCase__      =			key







							def 						__SCREAMING_SNAKE_CASE							(	self      ,					lowerCamelCase_      ,					lowerCamelCase_     ) ->							list[str]:
														assert isinstance(lowerCamelCase_      ,					lowerCamelCase_     ) and isinstance(lowerCamelCase_      ,					lowerCamelCase_     )

														lowerCAmelCase__      =			key or self.__key or 1

														# make sure key is an appropriate size
														key %= 2_55

														return [chr(ord(lowerCamelCase_     ) ^ key     ) for ch in content]







							def 						__SCREAMING_SNAKE_CASE							(	self      ,					lowerCamelCase_      ,					lowerCamelCase_     ) ->							list[str]:
														assert isinstance(lowerCamelCase_      ,					lowerCamelCase_     ) and isinstance(lowerCamelCase_      ,					lowerCamelCase_     )

														lowerCAmelCase__      =			key or self.__key or 1

														# make sure key is an appropriate size
														key %= 2_55

														return [chr(ord(lowerCamelCase_     ) ^ key     ) for ch in content]







							def 						__SCREAMING_SNAKE_CASE							(	self      ,					lowerCamelCase_      ,					lowerCamelCase_ = 0     ) ->							str:
														assert isinstance(lowerCamelCase_      ,					lowerCamelCase_     ) and isinstance(lowerCamelCase_      ,					lowerCamelCase_     )

														lowerCAmelCase__      =			key or self.__key or 1

														# make sure key can be any size
														while key > 2_55:
																					key -= 2_55

														# This will be returned
														lowerCAmelCase__      =			''''''

														for ch in content:
																					ans += chr(ord(lowerCamelCase_     ) ^ key     )

														return ans







							def 						__SCREAMING_SNAKE_CASE							(	self      ,					lowerCamelCase_      ,					lowerCamelCase_ = 0     ) ->							str:
														assert isinstance(lowerCamelCase_      ,					lowerCamelCase_     ) and isinstance(lowerCamelCase_      ,					lowerCamelCase_     )

														lowerCAmelCase__      =			key or self.__key or 1

														# make sure key can be any size
														while key > 2_55:
																					key -= 2_55

														# This will be returned
														lowerCAmelCase__      =			''''''

														for ch in content:
																					ans += chr(ord(lowerCamelCase_     ) ^ key     )

														return ans







							def 						__SCREAMING_SNAKE_CASE							(	self      ,					lowerCamelCase_      ,					lowerCamelCase_ = 0     ) ->							bool:
														assert isinstance(lowerCamelCase_      ,					lowerCamelCase_     ) and isinstance(lowerCamelCase_      ,					lowerCamelCase_     )

														try:
																					with open(lowerCamelCase_     ) as fin, open('''encrypt.out'''      ,					'''w+'''     ) as fout:
																												# actual encrypt-process
																												for line in fin:
																																			fout.write(self.encrypt_string(lowerCamelCase_      ,					lowerCamelCase_     )     )

														except OSError:
																					return False

														return True







							def 						__SCREAMING_SNAKE_CASE							(	self      ,					lowerCamelCase_      ,					lowerCamelCase_     ) ->							bool:
														assert isinstance(lowerCamelCase_      ,					lowerCamelCase_     ) and isinstance(lowerCamelCase_      ,					lowerCamelCase_     )

														try:
																					with open(lowerCamelCase_     ) as fin, open('''decrypt.out'''      ,					'''w+'''     ) as fout:
																												# actual encrypt-process
																												for line in fin:
																																			fout.write(self.decrypt_string(lowerCamelCase_      ,					lowerCamelCase_     )     )

														except OSError:
																					return False

														return True


# Tests
# crypt = XORCipher()
# key = 67

# # test encrypt
# print(crypt.encrypt("hallo welt",key))
# # test decrypt
# print(crypt.decrypt(crypt.encrypt("hallo welt",key), key))

# # test encrypt_string
# print(crypt.encrypt_string("hallo welt",key))

# # test decrypt_string
# print(crypt.decrypt_string(crypt.encrypt_string("hallo welt",key),key))

# if (crypt.encrypt_file("test.txt",key)):
#       print("encrypt successful")
# else:
#       print("encrypt unsuccessful")

# if (crypt.decrypt_file("encrypt.out",key)):
#       print("decrypt successful")
# else:
#       print("decrypt unsuccessful")