


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:
	A :	Optional[int]												=     None

A :	List[str]												=     logging.get_logger(__name__)
A :	Optional[Any]												=     {'vocab_file': 'tokenizer.model', 'tokenizer_file': 'tokenizer.json'}

A :	Tuple												=     '[INST]', '[/INST]'
A :	str												=     '<<SYS>>\n', '\n<</SYS>>\n\n'

# fmt: off
A :	Optional[int]												=     'You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your\\nanswers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure\\nthat your responses are socially unbiased and positive in nature.\n\nIf a question does not make any sense, or is not factually coherent, explain why instead of answering something not\\ncorrect. If you don\'t know the answer to a question, please don\'t share false information.'



class 							A					( UpperCAmelCase__							):
					'''simple docstring'''






					A__    =				VOCAB_FILES_NAMES
					A__    =				LlamaTokenizer
					A__    =				'''left'''
					A__    =				['''input_ids''', '''attention_mask''']

					def __init__(self					:		List[str]   ,      _UpperCAmelCase					:		int=None   ,      _UpperCAmelCase					:		Dict=None   ,      _UpperCAmelCase					:		Optional[int]=False   ,      _UpperCAmelCase					:		Tuple="<unk>"   ,      _UpperCAmelCase					:		Tuple="<s>"   ,      _UpperCAmelCase					:		Tuple="</s>"   ,      _UpperCAmelCase					:		int=True   ,      _UpperCAmelCase					:		int=False   ,      **_UpperCAmelCase					:		List[Any]   ,      )		->     Tuple:




							"""simple docstring"""


							super().__init__(
							    vocab_file=_UpperCAmelCase   ,      tokenizer_file=_UpperCAmelCase   ,      clean_up_tokenization_spaces=_UpperCAmelCase   ,      unk_token=_UpperCAmelCase   ,      bos_token=_UpperCAmelCase   ,      eos_token=_UpperCAmelCase   ,      **_UpperCAmelCase   ,      )
							lowercase__      =	add_bos_token
							lowercase__      =	add_eos_token
							self.update_post_processor()

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

					def 						lowerCamelCase__  (self					:		Any	)		->     Union[str, Any]:




							"""simple docstring"""


							lowercase__      =	self.bos_token
							lowercase__      =	self.bos_token_id

							lowercase__      =	self.eos_token
							lowercase__      =	self.eos_token_id

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

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

					@property
					def 						lowerCamelCase__  (self					:		List[Any]	)		->     Optional[Any]:




							"""simple docstring"""


							return self._add_eos_token

					@property
					def 						lowerCamelCase__  (self					:		Dict	)		->     Optional[int]:




							"""simple docstring"""


							return self._add_bos_token

					@add_eos_token.setter
					def 						lowerCamelCase__  (self					:		Tuple   ,      _UpperCAmelCase					:		Optional[int]	)		->     str:




							"""simple docstring"""


							lowercase__      =	value
							self.update_post_processor()

					@add_bos_token.setter
					def 						lowerCamelCase__  (self					:		Optional[Any]   ,      _UpperCAmelCase					:		Dict	)		->     Optional[Any]:




							"""simple docstring"""


							lowercase__      =	value
							self.update_post_processor()

					def 						lowerCamelCase__  (self					:		List[Any]   ,      _UpperCAmelCase					:		str   ,      _UpperCAmelCase					:		Optional[str] = None	)		->     Tuple[str]:




							"""simple docstring"""


							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(_UpperCAmelCase	):
									logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''	)
									return
							lowercase__      =	os.path.join(
							    _UpperCAmelCase   ,      (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]	)

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

							return (out_vocab_file,)


					def 						lowerCamelCase__  (self					:		List[Any]   ,      _UpperCAmelCase					:		"Conversation"	)		->     Optional[Any]:




							"""simple docstring"""


							lowercase__      =	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...)"""	)

							lowercase__      =	[]
							if len(conversation.past_user_inputs	) > 0:
									if not conversation.past_user_inputs[0].startswith(_UpperCAmelCase	) or E_SYS not in conversation.past_user_inputs[0]:
											lowercase__      =	(
											    B_SYS + DEFAULT_SYSTEM_PROMPT + E_SYS + conversation.past_user_inputs[0]
											)
							elif not dialogue[0][1].startswith(_UpperCAmelCase	) or E_SYS not in dialogue[0][1]:
									lowercase__      =	(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=_UpperCAmelCase	)
							        + [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=_UpperCAmelCase	)
							return dialog_tokens





import warnings

from ...utils import logging
from .image_processing_mobilenet_va import MobileNetVaImageProcessor


A :	Optional[Any]												=     logging.get_logger(__name__)



class 							A					( UpperCAmelCase__							):
					'''simple docstring'''






					def __init__(self					:		Optional[int]   ,      *_UpperCAmelCase					:		Union[str, Any]   ,      **_UpperCAmelCase					:		Any	)		->     None:




							"""simple docstring"""


							warnings.warn(
							    """The class MobileNetV1FeatureExtractor is deprecated and will be removed in version 5 of Transformers."""
							    """ Please use MobileNetV1ImageProcessor instead."""   ,      _UpperCAmelCase   ,      )
							super().__init__(*_UpperCAmelCase   ,      **_UpperCAmelCase	)

