





"""simple docstring"""





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""": 2_048,
}


def       a__					(					_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


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

		UpperCamelCase   =	collections.OrderedDict()
		UpperCamelCase   =	collections.OrderedDict()
		UpperCamelCase   =	collections.OrderedDict()
		with open(_SCREAMING_SNAKE_CASE  ,	"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(_SCREAMING_SNAKE_CASE    ):
				UpperCamelCase   =	b
				UpperCamelCase   =	idx
				for wd in b:
						UpperCamelCase   =	idx

		return vocab, raw_vocab, ids_to_tokens, emoji





class        _lowerCamelCase      (       _lowerCAmelCase ):
						UpperCAmelCase_ =			VOCAB_FILES_NAMES
						UpperCAmelCase_ =			PRETRAINED_VOCAB_FILES_MAP
						UpperCAmelCase_ =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						UpperCAmelCase_ =			['input_ids', 'attention_mask']


						def __init__(self   ,							__a   ,							__a   ,							__a="<|endoftext|>"   ,							__a="<|endoftext|>"   ,							__a="<|startoftext|>"   ,							__a="<|endoftext|>"   ,							__a=False   ,							**__a   ,							) ->   int:
								super().__init__(
								    unk_token=_lowerCAmelCase   ,							pad_token=_lowerCAmelCase   ,							bos_token=_lowerCAmelCase   ,							eos_token=_lowerCAmelCase   ,							do_clean_text=_lowerCAmelCase   ,							**_lowerCAmelCase   ,							)
								if not os.path.isfile(_lowerCAmelCase		):
										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(_lowerCAmelCase		):
										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(_lowerCAmelCase   ,							_lowerCAmelCase		)
								UpperCamelCase   =	SubWordJapaneseTokenizer(
								    vocab=self.vocab   ,							ids_to_tokens=self.ids_to_tokens   ,							emoji=self.emoji		)


						@property
						def     snake_case_   (self		) ->   Dict:
								return len(self.raw_vocab		)


						def     snake_case_   (self		) ->   int:
								return dict(self.raw_vocab   ,							**self.added_tokens_encoder		)


						def     snake_case_   (self   ,							__a		) ->   Any:
								return self.subword_tokenizer.tokenize(_lowerCAmelCase   ,							clean=self.do_clean_text		)


						def     snake_case_   (self   ,							__a		) ->   List[Any]:
								return self.vocab.get(_lowerCAmelCase   ,							self.vocab.get(self.unk_token		)		)


						def     snake_case_   (self   ,							__a		) ->   str:
								return self.subword_tokenizer.convert_id_to_token(_lowerCAmelCase		)


						def     snake_case_   (self   ,							__a		) ->   Optional[Any]:
								UpperCamelCase   =	"".join(_lowerCAmelCase		).strip()
								return out_string


						def     snake_case_   (self   ,							__a		) ->   List[int]:
								UpperCamelCase   =	[]
								for is_user, text in conversation.iter_texts():
										input_ids.extend(self.encode(_lowerCAmelCase   ,							add_special_tokens=_lowerCAmelCase		) + [self.eos_token_id]		)

								if len(_lowerCAmelCase		) > self.model_max_length:
										UpperCamelCase   =	input_ids[-self.model_max_length :]
								return input_ids




						def     snake_case_   (self   ,							__a   ,							__a = None		) ->   Tuple[str]:
								UpperCamelCase   =	0
								if os.path.isdir(_lowerCAmelCase		):
										UpperCamelCase   =	os.path.join(
										    _lowerCAmelCase   ,							(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]		)
										UpperCamelCase   =	os.path.join(
										    _lowerCAmelCase   ,							(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(_lowerCAmelCase   ,							"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(_lowerCAmelCase		) + "\n"		)
												index += 1
								with open(_lowerCAmelCase   ,							"w"   ,							encoding="utf-8"		) as writer:
										json.dump(self.emoji   ,							_lowerCAmelCase		)
								return vocab_file, emoji_file





class        _lowerCamelCase      (       _lowerCAmelCase ):


						def __init__(self   ,							__a   ,							__a   ,							__a		) ->   List[Any]:
								UpperCamelCase   =	vocab  # same as swe
								UpperCamelCase   =	ids_to_tokens  # same as bpe
								UpperCamelCase   =	emoji
								UpperCamelCase   =	np.max([len(_lowerCAmelCase		) 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		) ->   Optional[Any]:
								return len(self.ids_to_tokens		)


						def     snake_case_   (self   ,							__a		) ->   int:
								UpperCamelCase   =	self.content_repattera.sub("<URL>"   ,							_lowerCAmelCase		)
								UpperCamelCase   =	self.content_repattera.sub("<EMAIL>"   ,							_lowerCAmelCase		)
								UpperCamelCase   =	self.content_repattera.sub("<TEL>"   ,							_lowerCAmelCase		)
								UpperCamelCase   =	self.content_repattera.sub("<DATE>"   ,							_lowerCAmelCase		)
								UpperCamelCase   =	self.content_repattera.sub("<DATE>"   ,							_lowerCAmelCase		)
								UpperCamelCase   =	self.content_repattera.sub("<PRICE>"   ,							_lowerCAmelCase		)
								UpperCamelCase   =	content.translate(self.content_transa		)
								while "<BLOCK><BLOCK>" in content:
										UpperCamelCase   =	content.replace("<BLOCK><BLOCK>"   ,							"<BLOCK>"		)
								return content


						def     snake_case_   (self   ,							__a   ,							__a=False		) ->   Optional[Any]:
								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(_lowerCAmelCase   ,							_lowerCAmelCase		)
								if clean:
										UpperCamelCase   =	self.clean_text(_lowerCAmelCase		)

								def check_simbol(__a		):
										UpperCamelCase   =	x.encode()
										if len(_lowerCAmelCase		) == 1 and len(_lowerCAmelCase		) == 2:
												UpperCamelCase   =	(int(e[0]		) << 8) + int(e[1]		)
												if (
												    (c >= 0Xc2a1 and c <= 0Xc2bf)
												    or (c >= 0Xc780 and c <= 0Xc783)
												    or (c >= 0Xcab9 and c <= 0Xcbbf)
												    or (c >= 0Xcc80 and c <= 0Xcda2)
												):
														return True
										return False

								def checkuae(__a		):
										UpperCamelCase   =	x.encode()
										if len(_lowerCAmelCase		) == 1 and len(_lowerCAmelCase		) == 3:
												UpperCamelCase   =	(int(e[0]		) << 16) + (int(e[1]		) << 8) + int(e[2]		)
												if c >= 0Xe28080 and c <= 0Xe2b07f:
														return True
										return False

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




						def     snake_case_   (self   ,							__a   ,							__a="\n"		) ->   Optional[int]:
								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(_lowerCAmelCase		) > 0:
												words.append(bytearray(_lowerCAmelCase		).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(_lowerCAmelCase		)
										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(_lowerCAmelCase		)
								if len(_lowerCAmelCase		) > 0:
										words.append(bytearray(_lowerCAmelCase		).decode("utf-8"   ,							errors="replace"		)		)
								UpperCamelCase   =	"".join(_lowerCAmelCase		)
								return text













"""simple docstring"""





from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase__     			=			logging.get_logger(__name__)

lowerCAmelCase__     			=			{
    '''microsoft/swinv2-tiny-patch4-window8-256''': (
        '''https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolve/main/config.json'''
    ),
}





class        _lowerCamelCase      (       _lowercase ):
						UpperCAmelCase_ =			"swinv2"

						UpperCAmelCase_ =			{
						    "num_attention_heads": "num_heads",
						    "num_hidden_layers": "num_layers",
						}


						def __init__(self   ,							__a=2_24   ,							__a=4   ,							__a=3   ,							__a=96   ,							__a=[2, 2, 6, 2]   ,							__a=[3, 6, 12, 24]   ,							__a=7   ,							__a=4.0   ,							__a=True   ,							__a=0.0   ,							__a=0.0   ,							__a=0.1   ,							__a="gelu"   ,							__a=False   ,							__a=0.02   ,							__a=1e-5   ,							__a=32   ,							**__a   ,							) ->   Optional[Any]:
								super().__init__(**__a		)

								UpperCamelCase   =	image_size
								UpperCamelCase   =	patch_size
								UpperCamelCase   =	num_channels
								UpperCamelCase   =	embed_dim
								UpperCamelCase   =	depths
								UpperCamelCase   =	len(__a		)
								UpperCamelCase   =	num_heads
								UpperCamelCase   =	window_size
								UpperCamelCase   =	mlp_ratio
								UpperCamelCase   =	qkv_bias
								UpperCamelCase   =	hidden_dropout_prob
								UpperCamelCase   =	attention_probs_dropout_prob
								UpperCamelCase   =	drop_path_rate
								UpperCamelCase   =	hidden_act
								UpperCamelCase   =	use_absolute_embeddings
								UpperCamelCase   =	layer_norm_eps
								UpperCamelCase   =	initializer_range
								UpperCamelCase   =	encoder_stride
								# we set the hidden_size attribute in order to make Swinv2 work with VisionEncoderDecoderModel
								# this indicates the channel dimension after the last stage of the model
								UpperCamelCase   =	int(embed_dim * 2 ** (len(__a		) - 1)		)
								UpperCamelCase   =	(0, 0, 0, 0)






