



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:
				_lowercase:					Dict      =						None

_lowercase:					int      =						logging.get_logger(__name__)
_lowercase:					Optional[int]      =						{"vocab_file": "tokenizer.model", "tokenizer_file": "tokenizer.json"}

_lowercase     ,							_lowercase:					Optional[int]      =						"[INST]", "[/INST]"
_lowercase     ,							_lowercase:					Tuple      =						"<<SYS>>\n", "\n<</SYS>>\n\n"

# fmt: off
_lowercase:					str      =						"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       _lowercase				(  lowerCAmelCase      ):





	"""simple docstring"""
	__A		      =				VOCAB_FILES_NAMES
	__A		      =				LlamaTokenizer
	__A		      =				"left"
	__A		      =				["input_ids", "attention_mask"]




	def __init__(self						,			lowerCamelCase_=None						,			lowerCamelCase_=None						,			lowerCamelCase_=False						,			lowerCamelCase_="<unk>"						,			lowerCamelCase_="<s>"						,			lowerCamelCase_="</s>"						,			lowerCamelCase_=True						,			lowerCamelCase_=False						,			**lowerCamelCase_						,			):
						"""simple docstring"""

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

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




	def 	UpperCamelCase_			(self						):
						"""simple docstring"""

						a   	=  self.bos_token
						a   	=  self.bos_token_id

						a   	=  self.eos_token
						a   	=  self.eos_token_id

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

						a   	=  []
						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   	=  processors.TemplateProcessing(
						    single=lowerCamelCase_						,			pair=lowerCamelCase_						,			special_tokens=lowerCamelCase_						)




	@property
	def 	UpperCamelCase_			(self						):
						"""simple docstring"""

						return self._add_eos_token




	@property
	def 	UpperCamelCase_			(self						):
						"""simple docstring"""

						return self._add_bos_token




	@add_eos_token.setter
	def 	UpperCamelCase_			(self						,			lowerCamelCase_						):
						"""simple docstring"""

						a   	=  value
						self.update_post_processor()




	@add_bos_token.setter
	def 	UpperCamelCase_			(self						,			lowerCamelCase_						):
						"""simple docstring"""

						a   	=  value
						self.update_post_processor()




	def 	UpperCamelCase_			(self						,			lowerCamelCase_						,			lowerCamelCase_ = None						):
						"""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(lowerCamelCase_						):
											logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''						)
											return
						a   	=  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						,			lowerCamelCase_						):
						"""simple docstring"""

						a   	=  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   	=  []
						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   	=  (
																    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   	=  (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 .pipeline_kandinskya_a import KandinskyVaaPipeline
from .pipeline_kandinsky2_2_controlnet import KandinskyVaaControlnetPipeline
from .pipeline_kandinsky2_2_controlnet_img2img import KandinskyVaaControlnetImgaImgPipeline
from .pipeline_kandinsky2_2_img2img import KandinskyVaaImgaImgPipeline
from .pipeline_kandinsky2_2_inpainting import KandinskyVaaInpaintPipeline
from .pipeline_kandinsky2_2_prior import KandinskyVaaPriorPipeline
from .pipeline_kandinsky2_2_prior_emb2emb import KandinskyVaaPriorEmbaEmbPipeline
