
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple

import numpy as np

from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging


if TYPE_CHECKING:
    from transformers.pipelines.conversational import Conversation


lowerCamelCase_							=     logging.get_logger(__name__)

lowerCamelCase_							=     {"vocab_file": "vocab.txt", "emoji_file": "emoji.json"}

lowerCamelCase_							=     {
    "vocab_file": {
        "abeja/gpt-neox-japanese-2.7b": "https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/vocab.txt",
    },
    "emoji_file": {
        "abeja/gpt-neox-japanese-2.7b": "https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/emoji.json",
    },
}

lowerCamelCase_							=     {
    "abeja/gpt-neox-japanese-2.7b": 20_48,
}






def 						__magic_name__ (    __a			:       Union[str, Any]       ,		__a			:       List[str]						):



     '''simple docstring'''




     with open(UpperCamelCase__       ,		"""r"""       ,		encoding="""utf-8"""						) as f:
          UpperCamelCase__				=				json.loads(f.read()						)

     UpperCamelCase__				=				collections.OrderedDict()
     UpperCamelCase__				=				collections.OrderedDict()
     UpperCamelCase__				=				collections.OrderedDict()
     with open(UpperCamelCase__       ,		"""r"""       ,		encoding="""utf-8"""						) as f:
          UpperCamelCase__				=				f.readlines()
     UpperCamelCase__				=				[[t.rstrip("""\n"""						)] if (t == """,""" or """,""" not in t) else t.rstrip("""\n"""						).split(""","""						) for t in token]
     for idx, b in enumerate(UpperCamelCase__						):
          UpperCamelCase__				=				b
          UpperCamelCase__				=				idx
          for wd in b:
               UpperCamelCase__				=				idx

     return vocab, raw_vocab, ids_to_tokens, emoji




class 	__A(				a_ ):

  """simple docstring"""
  SCREAMING_SNAKE_CASE__			    =			VOCAB_FILES_NAMES
  SCREAMING_SNAKE_CASE__			    =			PRETRAINED_VOCAB_FILES_MAP
  SCREAMING_SNAKE_CASE__			    =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  SCREAMING_SNAKE_CASE__			    =			["""input_ids""", """attention_mask"""]







  def __init__(self       ,			SCREAMING_SNAKE_CASE_       ,			SCREAMING_SNAKE_CASE_       ,			SCREAMING_SNAKE_CASE_="<|endoftext|>"       ,			SCREAMING_SNAKE_CASE_="<|endoftext|>"       ,			SCREAMING_SNAKE_CASE_="<|startoftext|>"       ,			SCREAMING_SNAKE_CASE_="<|endoftext|>"       ,			SCREAMING_SNAKE_CASE_=False       ,			**SCREAMING_SNAKE_CASE_       ,			):
       super().__init__(
           unk_token=_A       ,			pad_token=_A       ,			bos_token=_A       ,			eos_token=_A       ,			do_clean_text=_A       ,			**_A       ,			)
       if not os.path.isfile(_A						):
            raise ValueError(
                F"Can't find a vocabulary file at path '{vocab_file}'. To load the vocabulary from a Google pretrained"
                """ model use `tokenizer = GPTNeoXJapaneseokenizer.from_pretrained(PRETRAINED_MODEL_NAME)`"""						)
       if not os.path.isfile(_A						):
            raise ValueError(
                F"Can't find a emoji file at path '{emoji_file}'. To load the emoji information from a Google"
                """ pretrained model use `tokenizer = GPTNeoXJapaneseokenizer.from_pretrained(PRETRAINED_MODEL_NAME)`"""						)
       UpperCamelCase__				=				do_clean_text
       UpperCamelCase__		,       UpperCamelCase__		,       UpperCamelCase__		,       UpperCamelCase__				=				load_vocab_and_emoji(_A       ,			_A						)
       UpperCamelCase__				=				SubWordJapaneseTokenizer(
           vocab=self.vocab       ,			ids_to_tokens=self.ids_to_tokens       ,			emoji=self.emoji						)







  @property
  def        UpperCAmelCase_					(self						):
       return len(self.raw_vocab						)







  def        UpperCAmelCase_					(self						):
       return dict(self.raw_vocab       ,			**self.added_tokens_encoder						)







  def        UpperCAmelCase_					(self       ,			SCREAMING_SNAKE_CASE_						):
       return self.subword_tokenizer.tokenize(_A       ,			clean=self.do_clean_text						)







  def        UpperCAmelCase_					(self       ,			SCREAMING_SNAKE_CASE_						):
       return self.vocab.get(_A       ,			self.vocab.get(self.unk_token						)						)







  def        UpperCAmelCase_					(self       ,			SCREAMING_SNAKE_CASE_						):
       return self.subword_tokenizer.convert_id_to_token(_A						)







  def        UpperCAmelCase_					(self       ,			SCREAMING_SNAKE_CASE_						):
       UpperCamelCase__				=				"""""".join(_A						).strip()
       return out_string







  def        UpperCAmelCase_					(self       ,			SCREAMING_SNAKE_CASE_						):
       UpperCamelCase__				=				[]
       for is_user, text in conversation.iter_texts():
            input_ids.extend(self.encode(_A       ,			add_special_tokens=_A						) + [self.eos_token_id]						)

       if len(_A						) > self.model_max_length:
            UpperCamelCase__				=				input_ids[-self.model_max_length :]
       return input_ids







  def        UpperCAmelCase_					(self       ,			SCREAMING_SNAKE_CASE_       ,			SCREAMING_SNAKE_CASE_ = None						):
       UpperCamelCase__				=				0
       if os.path.isdir(_A						):
            UpperCamelCase__				=				os.path.join(
                _A       ,			(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]						)
            UpperCamelCase__				=				os.path.join(
                _A       ,			(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""emoji_file"""]						)
       else:
            UpperCamelCase__				=				(
                (filename_prefix + """-""" if filename_prefix else """""") + save_directory + VOCAB_FILES_NAMES["""vocab_file"""]
            )
            UpperCamelCase__				=				(
                (filename_prefix + """-""" if filename_prefix else """""") + save_directory + VOCAB_FILES_NAMES["""emoji_file"""]
            )
       with open(_A       ,			"""w"""       ,			encoding="""utf-8"""						) as writer:
            for token_index, token in self.ids_to_tokens.items():
                 if index != token_index:
                      logger.warning(
                          F"Saving vocabulary to {vocab_file}: vocabulary indices are not consecutive."
                          """ Please check that the vocabulary is not corrupted!"""						)
                      UpperCamelCase__				=				token_index
                 writer.write(""",""".join(_A						) + """\n"""						)
                 index += 1
       with open(_A       ,			"""w"""       ,			encoding="""utf-8"""						) as writer:
            json.dump(self.emoji       ,			_A						)
       return vocab_file, emoji_file






class 	__A(				a_ ):

  """simple docstring"""







  def __init__(self       ,			SCREAMING_SNAKE_CASE_       ,			SCREAMING_SNAKE_CASE_       ,			SCREAMING_SNAKE_CASE_						):
       UpperCamelCase__				=				vocab  # same as swe
       UpperCamelCase__				=				ids_to_tokens  # same as bpe
       UpperCamelCase__				=				emoji
       UpperCamelCase__				=				np.max([len(_A						) for w in self.vocab.keys()]						)
       UpperCamelCase__				=				re.compile(r"""(https?|ftp)(:\/\/[-_\.!~*\'()a-zA-Z0-9;\/?:\@&=\+$,%#]+)"""						)
       UpperCamelCase__				=				re.compile(r"""[A-Za-z0-9\._+]*@[\-_0-9A-Za-z]+(\.[A-Za-z]+)*"""						)
       UpperCamelCase__				=				re.compile(r"""[\(]{0,1}[0-9]{2,4}[\)\-\(]{0,1}[0-9]{2,4}[\)\-]{0,1}[0-9]{3,4}"""						)
       UpperCamelCase__				=				re.compile(
           r"""([12]\d{3}[/\-年])*(0?[1-9]|1[0-2])[/\-月]((0?[1-9]|[12][0-9]|3[01])日?)*(\d{1,2}|:|\d{1,2}時|\d{1,2}分|\(日\)|\(月\)|\(火\)|\(水\)|\(木\)|\(金\)|\(土\)|㈰|㈪|㈫|㈬|㈭|㈮|㈯)*"""						)
       UpperCamelCase__				=				re.compile(
           r"""(明治|大正|昭和|平成|令和|㍾|㍽|㍼|㍻|\u32ff)\d{1,2}年(0?[1-9]|1[0-2])月(0?[1-9]|[12][0-9]|3[01])日(\d{1,2}|:|\d{1,2}時|\d{1,2}分|\(日\)|\(月\)|\(火\)|\(水\)|\(木\)|\(金\)|\(土\)|㈰|㈪|㈫|㈬|㈭|㈮|㈯)*"""						)
       UpperCamelCase__				=				re.compile(
           r"""((0|[1-9]\d*|[1-9]\d{0,2}(,\d{3})+)*億)*((0|[1-9]\d*|[1-9]\d{0,2}(,\d{3})+)*万)*((0|[1-9]\d*|[1-9]\d{0,2}(,\d{3})+)*千)*(0|[1-9]\d*|[1-9]\d{0,2}(,\d{3})+)*(千円|万円|千万円|円|千ドル|万ドル|千万ドル|ドル|千ユーロ|万ユーロ|千万ユーロ|ユーロ)+(\(税込\)|\(税抜\)|\+tax)*"""						)
       UpperCamelCase__				=				"""─━│┃┄┅┆┇┈┉┊┋┌┍┎┏┐┑┒┓└┕┖┗┘┙┚┛├┝┞┟┠┡┢┣┤┥┦┧┨┩┪┫┬┭┮┯┰┱┲┳┴┵┶┷┸┹┺┻┼┽┾┿╀╁╂╃╄╅╆╇╈╉╊╋╌╍╎╏═║╒╓╔╕╖╗╘╙╚╛╜╝╞╟╠╡╢╣╤╥╦╧╨╩╪╫╬╭╮╯╰╱╲╳╴╵╶╷╸╹╺╻╼╽╾╿"""
       UpperCamelCase__				=				"""▀▁▂▃▄▅▆▇█▉▊▋▌▍▎▏▐░▒▓▔▕▖▗▘▙▚▛▜▝▞▟"""
       UpperCamelCase__				=				str.maketrans({k: """<BLOCK>""" for k in keisen + blocks}						)







  def __len__(self						):
       return len(self.ids_to_tokens						)







  def        UpperCAmelCase_					(self       ,			SCREAMING_SNAKE_CASE_						):
       UpperCamelCase__				=				self.content_repattera.sub("""<URL>"""       ,			_A						)
       UpperCamelCase__				=				self.content_repattera.sub("""<EMAIL>"""       ,			_A						)
       UpperCamelCase__				=				self.content_repattera.sub("""<TEL>"""       ,			_A						)
       UpperCamelCase__				=				self.content_repattera.sub("""<DATE>"""       ,			_A						)
       UpperCamelCase__				=				self.content_repattera.sub("""<DATE>"""       ,			_A						)
       UpperCamelCase__				=				self.content_repattera.sub("""<PRICE>"""       ,			_A						)
       UpperCamelCase__				=				content.translate(self.content_transa						)
       while "<BLOCK><BLOCK>" in content:
            UpperCamelCase__				=				content.replace("""<BLOCK><BLOCK>"""       ,			"""<BLOCK>"""						)
       return content







  def        UpperCAmelCase_					(self       ,			SCREAMING_SNAKE_CASE_       ,			SCREAMING_SNAKE_CASE_=False						):
       UpperCamelCase__				=				text.replace(""" """       ,			"""<SP>"""						)
       UpperCamelCase__				=				text.replace("""　"""       ,			"""<SP>"""						)
       UpperCamelCase__				=				text.replace("""\r\n"""       ,			"""<BR>"""						)
       UpperCamelCase__				=				text.replace("""\n"""       ,			"""<BR>"""						)
       UpperCamelCase__				=				text.replace("""\r"""       ,			"""<BR>"""						)
       UpperCamelCase__				=				text.replace("""\t"""       ,			"""<TAB>"""						)
       UpperCamelCase__				=				text.replace("""—"""       ,			"""ー"""						)
       UpperCamelCase__				=				text.replace("""−"""       ,			"""ー"""						)
       for k, v in self.emoji["emoji"].items():
            if k in text:
                 UpperCamelCase__				=				text.replace(_A       ,			_A						)
       if clean:
            UpperCamelCase__				=				self.clean_text(_A						)

       def check_simbol(SCREAMING_SNAKE_CASE_						):
            UpperCamelCase__				=				x.encode()
            if len(_A						) == 1 and len(_A						) == 2:
                 UpperCamelCase__				=				(int(e[0]						) << 8) + int(e[1]						)
                 if (
                     (c >= 0Xc_2_a_1 and c <= 0Xc_2_b_f)
                     or (c >= 0Xc_7_8_0 and c <= 0Xc_7_8_3)
                     or (c >= 0Xc_a_b_9 and c <= 0Xc_b_b_f)
                     or (c >= 0Xc_c_8_0 and c <= 0Xc_d_a_2)
                 ):
                      return True
            return False

       def checkuae(SCREAMING_SNAKE_CASE_						):
            UpperCamelCase__				=				x.encode()
            if len(_A						) == 1 and len(_A						) == 3:
                 UpperCamelCase__				=				(int(e[0]						) << 16) + (int(e[1]						) << 8) + int(e[2]						)
                 if c >= 0Xe_2_8_0_8_0 and c <= 0Xe_2_b_0_7_f:
                      return True
            return False

       UpperCamelCase__				=				0
       UpperCamelCase__				=				[]
       while pos < len(_A						):
            UpperCamelCase__				=				min(len(_A						)       ,			pos + self.maxlen + 1						) if text[pos] == """<""" else pos + 3
            UpperCamelCase__				=				[]  # (token_id, token, pos)
            for e in range(_A       ,			_A       ,			-1						):
                 UpperCamelCase__				=				text[pos:e]
                 if wd in self.vocab:
                      if wd[0] == "<" and len(_A						) > 2:
                           UpperCamelCase__				=				[(self.vocab[wd], wd, e)]
                           break
                      else:
                           candidates.append((self.vocab[wd], wd, e)						)
            if len(_A						) > 0:
                 # the smallest token_id is adopted
                 UpperCamelCase__		,       UpperCamelCase__		,       UpperCamelCase__				=				sorted(_A       ,			key=lambda SCREAMING_SNAKE_CASE_						: x[0]						)[0]
                 result.append(_A						)
                 UpperCamelCase__				=				e
            else:
                 UpperCamelCase__				=				pos + 1
                 UpperCamelCase__				=				text[pos:end]
                 if check_simbol(_A						):
                      result.append("""<KIGOU>"""						)
                 elif checkuae(_A						):
                      result.append("""<U2000U2BFF>"""						)
                 else:
                      for i in wd.encode("""utf-8"""						):
                           result.append("""<|byte%d|>""" % i						)
                 UpperCamelCase__				=				end
       return result







  def        UpperCAmelCase_					(self       ,			SCREAMING_SNAKE_CASE_       ,			SCREAMING_SNAKE_CASE_="\n"						):
       UpperCamelCase__				=				[]
       UpperCamelCase__				=				[]
       UpperCamelCase__				=				self.ids_to_tokens[index][0]
       if word[:6] == "<|byte" and word[-2:] == "|>":
            byte_tokens.append(int(word[6:-2]						)						)
       else:
            if len(_A						) > 0:
                 words.append(bytearray(_A						).decode("""utf-8"""       ,			errors="""replace"""						)						)
                 UpperCamelCase__				=				[]
            if word[:7] == "<|emoji" and word[-2:] == "|>":
                 words.append(self.emoji["""emoji_inv"""][word]						)
            elif word == "<SP>":
                 words.append(""" """						)
            elif word == "<BR>":
                 words.append(_A						)
            elif word == "<TAB>":
                 words.append("""\t"""						)
            elif word == "<BLOCK>":
                 words.append("""▀"""						)
            elif word == "<KIGOU>":
                 words.append("""ǀ"""						)
            elif word == "<U2000U2BFF>":
                 words.append("""‖"""						)
            else:
                 words.append(_A						)
       if len(_A						) > 0:
            words.append(bytearray(_A						).decode("""utf-8"""       ,			errors="""replace"""						)						)
       UpperCamelCase__				=				"""""".join(_A						)
       return text












from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging


if TYPE_CHECKING:
				from ...onnx.config import PatchingSpec
				from ...tokenization_utils_base import PreTrainedTokenizerBase


__A				:    Dict       =   logging.get_logger(__name__)

__A				:    str       =   {
    "allenai/longformer-base-4096": "https://huggingface.co/allenai/longformer-base-4096/resolve/main/config.json",
    "allenai/longformer-large-4096": "https://huggingface.co/allenai/longformer-large-4096/resolve/main/config.json",
    "allenai/longformer-large-4096-finetuned-triviaqa": (
        "https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/config.json"
    ),
    "allenai/longformer-base-4096-extra.pos.embd.only": (
        "https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/config.json"
    ),
    "allenai/longformer-large-4096-extra.pos.embd.only": (
        "https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/config.json"
    ),
}

class 	A_       (a_			):
	UpperCAmelCase__					=			'''longformer'''
	def __init__(    self							,					_A = 5_1_2							,					_A = 2							,					_A = 1							,					_A = 0							,					_A = 2							,					_A = 3_0_5_2_2							,					_A = 7_6_8							,					_A = 1_2							,					_A = 1_2							,					_A = 3_0_7_2							,					_A = "gelu"							,					_A = 0.1							,					_A = 0.1							,					_A = 5_1_2							,					_A = 2							,					_A = 0.02							,					_A = 1E-12							,					_A = False							,					**_A							,					):






				'''simple docstring'''







				super().__init__(pad_token_id=_A							,					**_A		)

				UpperCAmelCase   		=				attention_window
				UpperCAmelCase   		=				sep_token_id
				UpperCAmelCase   		=				bos_token_id
				UpperCAmelCase   		=				eos_token_id
				UpperCAmelCase   		=				vocab_size
				UpperCAmelCase   		=				hidden_size
				UpperCAmelCase   		=				num_hidden_layers
				UpperCAmelCase   		=				num_attention_heads
				UpperCAmelCase   		=				hidden_act
				UpperCAmelCase   		=				intermediate_size
				UpperCAmelCase   		=				hidden_dropout_prob
				UpperCAmelCase   		=				attention_probs_dropout_prob
				UpperCAmelCase   		=				max_position_embeddings
				UpperCAmelCase   		=				type_vocab_size
				UpperCAmelCase   		=				initializer_range
				UpperCAmelCase   		=				layer_norm_eps
				UpperCAmelCase   		=				onnx_export

class 	A_       (a_			):
	def __init__(    self							,					_A							,					_A = "default"							,					_A = None		):






				'''simple docstring'''







				super().__init__(_A							,					_A							,					_A		)
				UpperCAmelCase   		=				True
	@property
	def      _lowercase				(    self		):






				'''simple docstring'''







				if self.task == "multiple-choice":
							UpperCAmelCase   		=				{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
				else:
							UpperCAmelCase   		=				{0: '''batch''', 1: '''sequence'''}
				return OrderedDict(
				    [
				        ('''input_ids''', dynamic_axis),
				        ('''attention_mask''', dynamic_axis),
				        ('''global_attention_mask''', dynamic_axis),
				    ]		)
	@property
	def      _lowercase				(    self		):






				'''simple docstring'''







				UpperCAmelCase   		=				super().outputs
				if self.task == "default":
							UpperCAmelCase   		=				{0: '''batch'''}
				return outputs
	@property
	def      _lowercase				(    self		):






				'''simple docstring'''







				return 1E-4
	@property
	def      _lowercase				(    self		):






				'''simple docstring'''







				return max(super().default_onnx_opset							,					1_4		)







	def      _lowercase				(    self							,					_A							,					_A = -1							,					_A = -1							,					_A = False							,					_A = None							,					):






				'''simple docstring'''







				UpperCAmelCase   		=				super().generate_dummy_inputs(
				    preprocessor=_A							,					batch_size=_A							,					seq_length=_A							,					is_pair=_A							,					framework=_A		)
				import torch

				# for some reason, replacing this code by inputs["global_attention_mask"] = torch.randint(2, inputs["input_ids"].shape, dtype=torch.int64)
				# makes the export fail randomly
				UpperCAmelCase   		=				torch.zeros_like(inputs['''input_ids''']		)
				# make every second token global
				UpperCAmelCase   		=				1

				return inputs



