



"""simple docstring"""
import os
from shutil import copyfile
from typing import TYPE_CHECKING, Optional, Tuple

from tokenizers import processors

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
from ...utils.versions import require_version


if TYPE_CHECKING:
			from transformers.pipelines.conversational import Conversation

require_version('''tokenizers>=0.13.3''')

if is_sentencepiece_available():
			from .tokenization_llama import LlamaTokenizer
else:
			__SCREAMING_SNAKE_CASE     :  Tuple										=					None

__SCREAMING_SNAKE_CASE     :  int										=					logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE     :  int										=					{'''vocab_file''': '''tokenizer.model''', '''tokenizer_file''': '''tokenizer.json'''}

__SCREAMING_SNAKE_CASE							,    __SCREAMING_SNAKE_CASE     :  Dict										=					'''[INST]''', '''[/INST]'''
__SCREAMING_SNAKE_CASE							,    __SCREAMING_SNAKE_CASE     :  List[str]										=					'''<<SYS>>\n''', '''\n<</SYS>>\n\n'''

# fmt: off
__SCREAMING_SNAKE_CASE     :  Optional[int]										=					'''You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your\
answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure\
that your responses are socially unbiased and positive in nature.

If a question does not make any sense, or is not factually coherent, explain why instead of answering something not\
correct. If you don\'t know the answer to a question, please don\'t share false information.'''


class 							lowerCamelCase_(      A__			):





					'''simple docstring'''



					lowercase__      :				Dict        =       VOCAB_FILES_NAMES
					lowercase__      :				Union[str, Any]        =       LlamaTokenizer
					lowercase__      :				Optional[Any]        =       'left'
					lowercase__      :				Union[str, Any]        =       ['input_ids', 'attention_mask']

					def __init__(			self ,				lowerCamelCase__=None ,				lowerCamelCase__=None ,				lowerCamelCase__=False ,				lowerCamelCase__="<unk>" ,				lowerCamelCase__="<s>" ,				lowerCamelCase__="</s>" ,				lowerCamelCase__=True ,				lowerCamelCase__=False ,				**lowerCamelCase__ ,				):
									super().__init__(
									    vocab_file=lowerCamelCase__ ,				tokenizer_file=lowerCamelCase__ ,				clean_up_tokenization_spaces=lowerCamelCase__ ,				unk_token=lowerCamelCase__ ,				bos_token=lowerCamelCase__ ,				eos_token=lowerCamelCase__ ,				**lowerCamelCase__ ,				)
									_lowerCamelCase					     = add_bos_token
									_lowerCamelCase					     = add_eos_token
									self.update_post_processor()

									_lowerCamelCase					     = vocab_file
									_lowerCamelCase					     = False if not self.vocab_file else True

					def 	snake_case__					(			self      ):
									_lowerCamelCase					     = self.bos_token
									_lowerCamelCase					     = self.bos_token_id

									_lowerCamelCase					     = self.eos_token
									_lowerCamelCase					     = self.eos_token_id

									_lowerCamelCase					     = F"""{(bos+":0 ") * self.add_bos_token}$A:0{(" "+eos+":0") * self.add_eos_token}"""
									_lowerCamelCase					     = F"""{single}{(" "+bos+":1") * self.add_bos_token} $B:1{(" "+eos+":1") * self.add_eos_token}"""

									_lowerCamelCase					     = []
									if self.add_bos_token:
													special_tokens.append((bos, bos_token_id)      )
									if self.add_eos_token:
													special_tokens.append((eos, eos_token_id)      )
									_lowerCamelCase					     = processors.TemplateProcessing(
									    single=lowerCamelCase__ ,				pair=lowerCamelCase__ ,				special_tokens=lowerCamelCase__      )

					@property
					def 	snake_case__					(			self      ):
									return self._add_eos_token

					@property
					def 	snake_case__					(			self      ):
									return self._add_bos_token

					@add_eos_token.setter
					def 	snake_case__					(			self ,				lowerCamelCase__      ):
									_lowerCamelCase					     = value
									self.update_post_processor()

					@add_bos_token.setter
					def 	snake_case__					(			self ,				lowerCamelCase__      ):
									_lowerCamelCase					     = value
									self.update_post_processor()

					def 	snake_case__					(			self ,				lowerCamelCase__ ,				lowerCamelCase__ = None      ):
									if not self.can_save_slow_tokenizer:
													raise ValueError(
													    '''Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '''
													    '''tokenizer.'''      )

									if not os.path.isdir(lowerCamelCase__      ):
													logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""      )
													return
									_lowerCamelCase					     = os.path.join(
									    lowerCamelCase__ ,				(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']      )

									if os.path.abspath(self.vocab_file      ) != os.path.abspath(lowerCamelCase__      ):
													copyfile(self.vocab_file ,				lowerCamelCase__      )

									return (out_vocab_file,)





					def 	snake_case__					(			self ,				lowerCamelCase__      ):
									_lowerCamelCase					     = list(conversation.iter_texts()      )
									if not all([is_user for is_user, msg in dialogue[::2]]      ) or not all(
									    [not is_user for is_user, msg in dialogue[1::2]]      ):
													raise ValueError(
													    '''The model only supports \'user\' and \'assistant\' roles, starting with user and alternating (u/a/u/a/u...)'''      )

									_lowerCamelCase					     = []
									if len(conversation.past_user_inputs      ) > 0:
													if not conversation.past_user_inputs[0].startswith(lowerCamelCase__      ) or E_SYS not in conversation.past_user_inputs[0]:
																	_lowerCamelCase					     = (
																	    B_SYS + DEFAULT_SYSTEM_PROMPT + E_SYS + conversation.past_user_inputs[0]
																	)
									elif not dialogue[0][1].startswith(lowerCamelCase__      ) or E_SYS not in dialogue[0][1]:
													_lowerCamelCase					     = (dialogue[0][0], B_SYS + DEFAULT_SYSTEM_PROMPT + E_SYS + dialogue[0][1])

									dialog_tokens += sum(
									    [
									        [self.bos_token_id]
									        + self.encode(
									            F"""{B_INST} {(prompt[1]).strip()} {E_INST} {(answer[1]).strip()} """ ,				add_special_tokens=lowerCamelCase__      )
									        + [self.eos_token_id]
									        for prompt, answer in zip(dialogue[::2] ,				dialogue[1::2]      )
									    ] ,				[] ,				)
									if not (dialogue[-1][0]):
													raise ValueError(F"""Last message must be from user, got {dialogue[-1]["role"]}"""      )
									dialog_tokens += [self.bos_token_id] + self.encode(
									    F"""{B_INST} {(dialogue[-1][1]).strip()} {E_INST}""" ,				add_special_tokens=lowerCamelCase__      )
									return dialog_tokens





"""simple docstring"""
def 				lowerCAmelCase_(      lowercase_   :							str  ,      lowercase_   :							str							)		->				int:
				# The longer word should come first
				if len(lowercase_							) < len(lowercase_							):
								return levenshtein_distance(lowercase_  ,      lowercase_							)

				if len(lowercase_							) == 0:
								return len(lowercase_							)

				_lowerCamelCase					     = list(range(len(lowercase_							) + 1							)							)

				for i, ca in enumerate(lowercase_							):
								_lowerCamelCase					     = [i + 1]

								for j, ca in enumerate(lowercase_							):
												# Calculate insertions, deletions and substitutions
												_lowerCamelCase					     = previous_row[j + 1] + 1
												_lowerCamelCase					     = current_row[j] + 1
												_lowerCamelCase					     = previous_row[j] + (ca != ca)

												# Get the minimum to append to the current row
												current_row.append(min(lowercase_  ,      lowercase_  ,      lowercase_							)							)

								# Store the previous row
								_lowerCamelCase					     = current_row

				# Returns the last element (distance)
				return previous_row[-1]


if __name__ == "__main__":
			__SCREAMING_SNAKE_CASE     :  int										=					input('''Enter the first word:\n''').strip()
			__SCREAMING_SNAKE_CASE     :  Optional[Any]										=					input('''Enter the second word:\n''').strip()

			__SCREAMING_SNAKE_CASE     :  Optional[Any]										=					levenshtein_distance(first_word, second_word)
			print(F"""Levenshtein distance between {first_word} and {second_word} is {result}""")
