



def    UpperCAmelCase					(  lowercase__						:					str				,					lowercase__						:					str				,					lowercase__						:					int				,					lowercase__						:					int				,					lowercase__						:					int				,					lowercase__						:					int				,					):



			'''simple docstring'''





			a__					=  list(lowercase__	)
			a__					=  list(lowercase__	)
			a__					=  len(lowercase__	)
			a__					=  len(lowercase__	)

			a__					=  [
			    [0 for _ in range(len_destination_seq + 1	)] for _ in range(len_source_seq + 1	)
			]
			a__					=  [
			    ["""0""" for _ in range(len_destination_seq + 1	)] for _ in range(len_source_seq + 1	)
			]

			for i in range(1				,					len_source_seq + 1	):
						a__					=  i * delete_cost
						a__					=  f'D{source_seq[i - 1]:c}'

			for i in range(1				,					len_destination_seq + 1	):
						a__					=  i * insert_cost
						a__					=  f'I{destination_seq[i - 1]:c}'

			for i in range(1				,					len_source_seq + 1	):
						for j in range(1				,					len_destination_seq + 1	):
									if source_seq[i - 1] == destination_seq[j - 1]:
												a__					=  costs[i - 1][j - 1] + copy_cost
												a__					=  f'C{source_seq[i - 1]:c}'
									else:
												a__					=  costs[i - 1][j - 1] + replace_cost
												a__					=  f'R{source_seq[i - 1]:c}' + str(destination_seq[j - 1]	)

									if costs[i - 1][j] + delete_cost < costs[i][j]:
												a__					=  costs[i - 1][j] + delete_cost
												a__					=  f'D{source_seq[i - 1]:c}'

									if costs[i][j - 1] + insert_cost < costs[i][j]:
												a__					=  costs[i][j - 1] + insert_cost
												a__					=  f'I{destination_seq[j - 1]:c}'

			return costs, ops




def    UpperCAmelCase					(  lowercase__						:					list[list[str]]				,					lowercase__						:					int				,					lowercase__						:					int	):



			'''simple docstring'''





			if i == 0 and j == 0:
						return []
			else:
						if ops[i][j][0] == "C" or ops[i][j][0] == "R":
									a__					=  assemble_transformation(lowercase__				,					i - 1				,					j - 1	)
									seq.append(ops[i][j]	)
									return seq
						elif ops[i][j][0] == "D":
									a__					=  assemble_transformation(lowercase__				,					i - 1				,					lowercase__	)
									seq.append(ops[i][j]	)
									return seq
						else:
									a__					=  assemble_transformation(lowercase__				,					lowercase__				,					j - 1	)
									seq.append(ops[i][j]	)
									return seq


if __name__ == "__main__":
	_lowercase					,    _lowercase				:					str     					=compute_transform_tables("""Python""", """Algorithms""", -1, 1, 2, 2)

	_lowercase				:					Union[str, Any]     					=len(operations)
	_lowercase				:					Optional[int]     					=len(operations[0])
	_lowercase				:					Tuple     					=assemble_transformation(operations, m - 1, n - 1)

	_lowercase				:					Dict     					=list("""Python""")
	_lowercase				:					Union[str, Any]     					=0
	_lowercase				:					Dict     					=0

	with open("""min_cost.txt""", """w""") as file:
		for op in sequence:
			print("""""".join(string))

			if op[0] == "C":
				file.write("""%-16s""" % """Copy %c""" % op[1])
				file.write("""\t\t\t""" + """""".join(string))
				file.write("""\r\n""")

				cost -= 1
			elif op[0] == "R":
				_lowercase				:					List[str]     					=op[2]

				file.write("""%-16s""" % ("""Replace %c""" % op[1] + """ with """ + str(op[2])))
				file.write("""\t\t""" + """""".join(string))
				file.write("""\r\n""")

				cost += 1
			elif op[0] == "D":
				string.pop(i)

				file.write("""%-16s""" % """Delete %c""" % op[1])
				file.write("""\t\t\t""" + """""".join(string))
				file.write("""\r\n""")

				cost += 2
			else:
				string.insert(i, op[1])

				file.write("""%-16s""" % """Insert %c""" % op[1])
				file.write("""\t\t\t""" + """""".join(string))
				file.write("""\r\n""")

				cost += 2

			i += 1

		print("""""".join(string))
		print("""Cost: """, cost)

		file.write("""\r\nMinimum cost: """ + str(cost))






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				:					Any     					=logging.get_logger(__name__)

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

_lowercase				:					int     					={
    """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				:					Tuple     					={
    """microsoft/deberta-base""": 5_12,
    """microsoft/deberta-large""": 5_12,
    """microsoft/deberta-xlarge""": 5_12,
    """microsoft/deberta-base-mnli""": 5_12,
    """microsoft/deberta-large-mnli""": 5_12,
    """microsoft/deberta-xlarge-mnli""": 5_12,
}

_lowercase				:					str     					={
    """microsoft/deberta-base""": {"""do_lower_case""": False},
    """microsoft/deberta-large""": {"""do_lower_case""": False},
}




def    UpperCAmelCase					(  ):



			'''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(lowercase__	)
									cs.append(2**8 + n	)
									n += 1
			a__					=  [chr(lowercase__	) for n in cs]
			return dict(zip(lowercase__				,					lowercase__	)	)




def    UpperCAmelCase					(  lowercase__						:					Optional[Any]	):



			'''simple docstring'''





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





class lowerCAmelCase_       (   A_			):







	'''simple docstring'''




	A_       :     List[str]									=		VOCAB_FILES_NAMES
	A_       :     str									=		PRETRAINED_VOCAB_FILES_MAP
	A_       :     List[str]									=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	A_       :     Optional[int]									=		['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 				_A			(	self       ):



				'''simple docstring'''


				return len(self.encoder       )

	def 				_A			(	self       ):



				'''simple docstring'''


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

	def 				_A			(	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 				_A			(	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 				_A			(	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 				_A			(	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 				_A			(	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 				_A			(	self   ,       lowerCamelCase       ):



				'''simple docstring'''


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

	def 				_A			(	self   ,       lowerCamelCase       ):



				'''simple docstring'''


				return self.decoder.get(lowerCamelCase       )

	def 				_A			(	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 				_A			(	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 				_A			(	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 				_A			(	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

