



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

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


if TYPE_CHECKING:
				from transformers.pipelines.conversational import Conversation

_lowercase:					Tuple      =						logging.get_logger(__name__)

_lowercase:					int      =						{"vocab_file": "vocab.json", "merges_file": "merges.txt"}

_lowercase:					Optional[Any]      =						{
    "vocab_file": {
        "microsoft/deberta-base": "https://huggingface.co/microsoft/deberta-base/resolve/main/vocab.json",
        "microsoft/deberta-large": "https://huggingface.co/microsoft/deberta-large/resolve/main/vocab.json",
        "microsoft/deberta-xlarge": "https://huggingface.co/microsoft/deberta-xlarge/resolve/main/vocab.json",
        "microsoft/deberta-base-mnli": "https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/vocab.json",
        "microsoft/deberta-large-mnli": "https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/vocab.json",
        "microsoft/deberta-xlarge-mnli": (
            "https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/vocab.json"
        ),
    },
    "merges_file": {
        "microsoft/deberta-base": "https://huggingface.co/microsoft/deberta-base/resolve/main/merges.txt",
        "microsoft/deberta-large": "https://huggingface.co/microsoft/deberta-large/resolve/main/merges.txt",
        "microsoft/deberta-xlarge": "https://huggingface.co/microsoft/deberta-xlarge/resolve/main/merges.txt",
        "microsoft/deberta-base-mnli": "https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/merges.txt",
        "microsoft/deberta-large-mnli": "https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/merges.txt",
        "microsoft/deberta-xlarge-mnli": (
            "https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/merges.txt"
        ),
    },
}

_lowercase:					List[Any]      =						{
    "microsoft/deberta-base": 512,
    "microsoft/deberta-large": 512,
    "microsoft/deberta-xlarge": 512,
    "microsoft/deberta-base-mnli": 512,
    "microsoft/deberta-large-mnli": 512,
    "microsoft/deberta-xlarge-mnli": 512,
}

_lowercase:					List[Any]      =						{
    "microsoft/deberta-base": {"do_lower_case": False},
    "microsoft/deberta-large": {"do_lower_case": False},
}






def        a( )						->			Dict:
					"""simple docstring"""





					a   	=  (
					    list(range(ord("!"			)					,	ord("~"			) + 1			)			) + list(range(ord("¡"			)					,	ord("¬"			) + 1			)			) + list(range(ord("®"			)					,	ord("ÿ"			) + 1			)			)
					)
					a   	=  bs[:]
					a   	=  0
					for b in range(2**8			):
										if b not in bs:
															bs.append(A			)
															cs.append(2**8 + n			)
															n += 1
					a   	=  [chr(A			) for n in cs]
					return dict(zip(A					,	A			)			)






def        a( A			:       Dict			)						->			Tuple:
					"""simple docstring"""





					a   	=  set()
					a   	=  word[0]
					for char in word[1:]:
										pairs.add((prev_char, char)			)
										a   	=  char
					return pairs







class       _lowercase				(  lowerCAmelCase      ):





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




	def __init__(self						,			lowerCamelCase_						,			lowerCamelCase_						,			lowerCamelCase_="replace"						,			lowerCamelCase_="[CLS]"						,			lowerCamelCase_="[SEP]"						,			lowerCamelCase_="[SEP]"						,			lowerCamelCase_="[CLS]"						,			lowerCamelCase_="[UNK]"						,			lowerCamelCase_="[PAD]"						,			lowerCamelCase_="[MASK]"						,			lowerCamelCase_=False						,			lowerCamelCase_=False						,			**lowerCamelCase_						,			):
						"""simple docstring"""

						a   	=  AddedToken(lowerCamelCase_						,			lstrip=lowerCamelCase_						,			rstrip=lowerCamelCase_						) if isinstance(lowerCamelCase_						,			lowerCamelCase_						) else bos_token
						a   	=  AddedToken(lowerCamelCase_						,			lstrip=lowerCamelCase_						,			rstrip=lowerCamelCase_						) if isinstance(lowerCamelCase_						,			lowerCamelCase_						) else eos_token
						a   	=  AddedToken(lowerCamelCase_						,			lstrip=lowerCamelCase_						,			rstrip=lowerCamelCase_						) if isinstance(lowerCamelCase_						,			lowerCamelCase_						) else sep_token
						a   	=  AddedToken(lowerCamelCase_						,			lstrip=lowerCamelCase_						,			rstrip=lowerCamelCase_						) if isinstance(lowerCamelCase_						,			lowerCamelCase_						) else cls_token
						a   	=  AddedToken(lowerCamelCase_						,			lstrip=lowerCamelCase_						,			rstrip=lowerCamelCase_						) if isinstance(lowerCamelCase_						,			lowerCamelCase_						) else unk_token
						a   	=  AddedToken(lowerCamelCase_						,			lstrip=lowerCamelCase_						,			rstrip=lowerCamelCase_						) if isinstance(lowerCamelCase_						,			lowerCamelCase_						) else pad_token

						# Mask token behave like a normal word, i.e. include the space before it
						a   	=  AddedToken(lowerCamelCase_						,			lstrip=lowerCamelCase_						,			rstrip=lowerCamelCase_						) if isinstance(lowerCamelCase_						,			lowerCamelCase_						) else mask_token

						super().__init__(
						    errors=lowerCamelCase_						,			bos_token=lowerCamelCase_						,			eos_token=lowerCamelCase_						,			unk_token=lowerCamelCase_						,			sep_token=lowerCamelCase_						,			cls_token=lowerCamelCase_						,			pad_token=lowerCamelCase_						,			mask_token=lowerCamelCase_						,			add_prefix_space=lowerCamelCase_						,			add_bos_token=lowerCamelCase_						,			**lowerCamelCase_						,			)
						a   	=  add_bos_token

						with open(lowerCamelCase_						,			encoding="utf-8"						) as vocab_handle:
											a   	=  json.load(lowerCamelCase_						)
						a   	=  {v: k for k, v in self.encoder.items()}
						a   	=  errors  # how to handle errors in decoding
						a   	=  bytes_to_unicode()
						a   	=  {v: k for k, v in self.byte_encoder.items()}
						with open(lowerCamelCase_						,			encoding="utf-8"						) as merges_handle:
											a   	=  merges_handle.read().split("\n"						)[1:-1]
						a   	=  [tuple(merge.split()						) for merge in bpe_merges]
						a   	=  dict(zip(lowerCamelCase_						,			range(len(lowerCamelCase_						)						)						)						)
						a   	=  {}
						a   	=  add_prefix_space

						# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
						a   	=  re.compile(R"'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"						)




	@property
	# Copied from transformers.models.gpt2.tokenization_gpt2.GPT2Tokenizer.vocab_size
	def 	UpperCamelCase_			(self						):
						"""simple docstring"""

						return len(self.encoder						)




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

						return dict(self.encoder						,			**self.added_tokens_encoder						)




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

						if token in self.cache:
											return self.cache[token]
						a   	=  tuple(lowerCamelCase_						)
						a   	=  get_pairs(lowerCamelCase_						)

						if not pairs:
											return token

						while True:
											a   	=  min(lowerCamelCase_						,			key=lambda lowerCamelCase_						: self.bpe_ranks.get(lowerCamelCase_						,			float("inf"						)						)						)
											if bigram not in self.bpe_ranks:
																break
											a	,							a   	=  bigram
											a   	=  []
											a   	=  0
											while i < len(lowerCamelCase_						):
																try:
																					a   	=  word.index(lowerCamelCase_						,			lowerCamelCase_						)
																except ValueError:
																					new_word.extend(word[i:]						)
																					break
																else:
																					new_word.extend(word[i:j]						)
																					a   	=  j

																if word[i] == first and i < len(lowerCamelCase_						) - 1 and word[i + 1] == second:
																					new_word.append(first + second						)
																					i += 2
																else:
																					new_word.append(word[i]						)
																					i += 1
											a   	=  tuple(lowerCamelCase_						)
											a   	=  new_word
											if len(lowerCamelCase_						) == 1:
																break
											else:
																a   	=  get_pairs(lowerCamelCase_						)
						a   	=  " ".join(lowerCamelCase_						)
						a   	=  word
						return word




	def 	UpperCamelCase_			(self						,			lowerCamelCase_						,			lowerCamelCase_ = None						):
						"""simple docstring"""

						if token_ids_a is None:
											return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
						a   	=  [self.cls_token_id]
						a   	=  [self.sep_token_id]
						return cls + token_ids_a + sep + token_ids_a + sep




	def 	UpperCamelCase_			(self						,			lowerCamelCase_						,			lowerCamelCase_ = None						,			lowerCamelCase_ = False						):
						"""simple docstring"""

						if already_has_special_tokens:
											return super().get_special_tokens_mask(
											    token_ids_a=lowerCamelCase_						,			token_ids_a=lowerCamelCase_						,			already_has_special_tokens=lowerCamelCase_						)

						if token_ids_a is None:
											return [1] + ([0] * len(lowerCamelCase_						)) + [1]
						return [1] + ([0] * len(lowerCamelCase_						)) + [1] + ([0] * len(lowerCamelCase_						)) + [1]




	def 	UpperCamelCase_			(self						,			lowerCamelCase_						,			lowerCamelCase_ = None						):
						"""simple docstring"""

						a   	=  [self.sep_token_id]
						a   	=  [self.cls_token_id]

						if token_ids_a is None:
											return len(cls + token_ids_a + sep						) * [0]
						return len(cls + token_ids_a + sep						) * [0] + len(token_ids_a + sep						) * [1]




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

						a   	=  []
						for token in re.findall(self.pat						,			lowerCamelCase_						):
											a   	=  "".join(
											    self.byte_encoder[b] for b in token.encode("utf-8"						)						)  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
											bpe_tokens.extend(bpe_token for bpe_token in self.bpe(lowerCamelCase_						).split(" "						)						)
						return bpe_tokens




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

						return self.encoder.get(lowerCamelCase_						,			self.encoder.get(self.unk_token						)						)




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

						return self.decoder.get(lowerCamelCase_						)




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

						a   	=  "".join(lowerCamelCase_						)
						a   	=  bytearray([self.byte_decoder[c] for c in text]						).decode("utf-8"						,			errors=self.errors						)
						return text




	def 	UpperCamelCase_			(self						,			lowerCamelCase_						,			lowerCamelCase_ = None						):
						"""simple docstring"""

						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"]						)
						a   	=  os.path.join(
						    lowerCamelCase_						,			(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]						)

						with open(lowerCamelCase_						,			"w"						,			encoding="utf-8"						) as f:
											f.write(json.dumps(self.encoder						,			indent=2						,			sort_keys=lowerCamelCase_						,			ensure_ascii=lowerCamelCase_						) + "\n"						)

						a   	=  0
						with open(lowerCamelCase_						,			"w"						,			encoding="utf-8"						) as writer:
											writer.write("#version: 0.2\n"						)
											for bpe_tokens, token_index in sorted(self.bpe_ranks.items()						,			key=lambda lowerCamelCase_						: kv[1]						):
																if index != token_index:
																					logger.warning(
																					    F'''Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'''
																					    " Please check that the tokenizer is not corrupted!"						)
																					a   	=  token_index
																writer.write(" ".join(lowerCamelCase_						) + "\n"						)
																index += 1

						return vocab_file, merge_file




	def 	UpperCamelCase_			(self						,			lowerCamelCase_						,			lowerCamelCase_=False						,			**lowerCamelCase_						):
						"""simple docstring"""

						a   	=  kwargs.pop("add_prefix_space"						,			self.add_prefix_space						)
						if (is_split_into_words or add_prefix_space) and (len(lowerCamelCase_						) > 0 and not text[0].isspace()):
											a   	=  " " + text
						return (text, kwargs)




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

						a   	=  []
						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:
											a   	=  input_ids[-self.model_max_length :]
						return input_ids





from __future__ import annotations

from collections import defaultdict
from dataclasses import dataclass



@dataclass
class       _lowercase				:





	"""simple docstring"""
	__A		      =				42
	__A		      =				None
	__A		      =				None






def        a( )						->			TreeNode:
					"""simple docstring"""





					return TreeNode(3					,	TreeNode(9			)					,	TreeNode(20					,	TreeNode(15			)					,	TreeNode(7			)			)			)






def        a( A			:       TreeNode			)						->			list[int]:
					"""simple docstring"""





					def depth_first_search(
					    A			:       TreeNode | None					,	A			:       int					,	A			:       list[int]			) -> None:
										if not root:
															return

										if depth == len(A			):
															right_view.append(root.val			)

										depth_first_search(root.right					,	depth + 1					,	A			)
										depth_first_search(root.left					,	depth + 1					,	A			)

					a   	=  []
					if not root:
										return right_view

					depth_first_search(A					,	0					,	A			)
					return right_view






def        a( A			:       TreeNode			)						->			list[int]:
					"""simple docstring"""





					def depth_first_search(
					    A			:       TreeNode | None					,	A			:       int					,	A			:       list[int]			) -> None:
										if not root:
															return

										if depth == len(A			):
															left_view.append(root.val			)

										depth_first_search(root.left					,	depth + 1					,	A			)
										depth_first_search(root.right					,	depth + 1					,	A			)

					a   	=  []
					if not root:
										return left_view

					depth_first_search(A					,	0					,	A			)
					return left_view






def        a( A			:       TreeNode			)						->			list[int]:
					"""simple docstring"""





					def breadth_first_search(A			:       TreeNode					,	A			:       list[int]			) -> None:
										a   	=  [(root, 0)]
										a   	=  defaultdict(A			)

										while queue:
															a   	=  queue.pop(0			)
															a	,							a   	=  first

															lookup[hd].append(node.val			)

															if node.left:
																				queue.append((node.left, hd - 1)			)
															if node.right:
																				queue.append((node.right, hd + 1)			)

										for pair in sorted(lookup.items()					,	key=lambda A			: each[0]			):
															top_view.append(pair[1][0]			)

					a   	=  []
					if not root:
										return top_view

					breadth_first_search(A					,	A			)
					return top_view






def        a( A			:       TreeNode			)						->			list[int]:
					"""simple docstring"""





					from collections import defaultdict

					def breadth_first_search(A			:       TreeNode					,	A			:       list[int]			) -> None:
										a   	=  [(root, 0)]
										a   	=  defaultdict(A			)

										while queue:
															a   	=  queue.pop(0			)
															a	,							a   	=  first
															lookup[hd].append(node.val			)

															if node.left:
																				queue.append((node.left, hd - 1)			)
															if node.right:
																				queue.append((node.right, hd + 1)			)

										for pair in sorted(lookup.items()					,	key=lambda A			: each[0]			):
															bottom_view.append(pair[1][-1]			)

					a   	=  []
					if not root:
										return bottom_view

					breadth_first_search(A					,	A			)
					return bottom_view


if __name__ == "__main__":
				import doctest

				doctest.testmod()
