

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:
	__snake_case							:			Any      		= None

__snake_case							:			str      		= logging.get_logger(__name__)
__snake_case							:			Union[str, Any]      		= {"""vocab_file""": """tokenizer.model""", """tokenizer_file""": """tokenizer.json"""}

__snake_case							:			Union[str, Any]      		= """[INST]""", """[/INST]"""
__snake_case							:			Optional[int]      		= """<<SYS>>\n""", """\n<</SYS>>\n\n"""

# fmt: off
__snake_case							:			List[str]      		= """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 					A__(UpperCAmelCase__       ):
						"""simple docstring"""






						_A						:							Union[str, Any]									= VOCAB_FILES_NAMES
						_A						:							Union[str, Any]									= LlamaTokenizer
						_A						:							Optional[int]									= 'left'
						_A						:							Tuple									= ['input_ids', 'attention_mask']





						def __init__(						self     ,			_lowercase=None     ,			_lowercase=None     ,			_lowercase=False     ,			_lowercase="<unk>"     ,			_lowercase="<s>"     ,			_lowercase="</s>"     ,			_lowercase=True     ,			_lowercase=False     ,			**_lowercase     ,			)    ->   Optional[int]:
									super().__init__(
									    vocab_file=lowerCamelCase__     ,			tokenizer_file=lowerCamelCase__     ,			clean_up_tokenization_spaces=lowerCamelCase__     ,			unk_token=lowerCamelCase__     ,			bos_token=lowerCamelCase__     ,			eos_token=lowerCamelCase__     ,			**lowerCamelCase__     ,			)
									a_	:	Dict          =   add_bos_token
									a_	:	Tuple          =   add_eos_token
									self.update_post_processor()

									a_	:	List[Any]          =   vocab_file
									a_	:	Tuple          =   False if not self.vocab_file else True





						def  UpperCamelCase__				(						self						)    ->   Tuple:
									a_	:	Optional[int]          =   self.bos_token
									a_	:	List[str]          =   self.bos_token_id

									a_	:	Union[str, Any]          =   self.eos_token
									a_	:	str          =   self.eos_token_id

									a_	:	int          =   F'''{(bos+":0 ") * self.add_bos_token}$A:0{(" "+eos+":0") * self.add_eos_token}'''
									a_	:	List[str]          =   F'''{single}{(" "+bos+":1") * self.add_bos_token} $B:1{(" "+eos+":1") * self.add_eos_token}'''

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





						@property
						def  UpperCamelCase__				(						self						)    ->   List[Any]:
									return self._add_eos_token





						@property
						def  UpperCamelCase__				(						self						)    ->   List[str]:
									return self._add_bos_token





						@add_eos_token.setter
						def  UpperCamelCase__				(						self     ,			_lowercase						)    ->   Optional[Any]:
									a_	:	int          =   value
									self.update_post_processor()





						@add_bos_token.setter
						def  UpperCamelCase__				(						self     ,			_lowercase						)    ->   Optional[int]:
									a_	:	int          =   value
									self.update_post_processor()





						def  UpperCamelCase__				(						self     ,			_lowercase     ,			_lowercase = None						)    ->   Dict:
									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
									a_	:	Any          =   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  UpperCamelCase__				(						self     ,			_lowercase						)    ->   List[str]:
									a_	:	List[str]          =   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...)"""						)

									a_	:	Tuple          =   []
									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]:
															a_	:	int          =   (
															    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]:
												a_	:	Any          =   (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





from collections import defaultdict


def 				_UpperCAmelCase							(	a__):

			'''simple docstring'''



			a_	:	defaultdict[str, int]          =   defaultdict(a__)
			# Creating a dictionary containing count of each word
			for word in sentence.split():
						occurrence[word] += 1
			return occurrence


if __name__ == "__main__":
	for word, count in word_occurrence("""INPUT STRING""").items():
		print(F"""{word}: {count}""")


