




"""simple docstring"""





import itertools
from dataclasses import dataclass
from typing import Optional

import pyarrow as pa

import datasets
from datasets.table import table_cast


_lowercase	      =    datasets.utils.logging.get_logger(__name__)

@dataclass
class       __lowercase       (			datasets.BuilderConfig	):


				'''simple docstring'''


				_lowerCAmelCase				=None







class       __lowercase       (			datasets.ArrowBasedBuilder	):


				'''simple docstring'''


				_lowerCAmelCase				=ArrowConfig

				def       _lowerCamelCase					(   self   :     Dict      ):
										return datasets.DatasetInfo(features=self.config.features      )

				def       _lowerCamelCase					(   self   :     Tuple      ,SCREAMING_SNAKE_CASE_   :     Dict      ):
										if not self.config.data_files:
																raise ValueError(F'''At least one data file must be specified, but got data_files={self.config.data_files}'''      )
										snake_case__       :					Any										=					dl_manager.download_and_extract(self.config.data_files      )
										if isinstance(SCREAMING_SNAKE_CASE_      ,(str, list, tuple)      ):
																snake_case__       :					str										=					data_files
																if isinstance(SCREAMING_SNAKE_CASE_      ,SCREAMING_SNAKE_CASE_      ):
																						snake_case__       :					Optional[Any]										=					[files]
																# Use `dl_manager.iter_files` to skip hidden files in an extracted archive
																snake_case__       :					List[Any]										=					[dl_manager.iter_files(SCREAMING_SNAKE_CASE_      ) for file in files]
																return [datasets.SplitGenerator(name=datasets.Split.TRAIN      ,gen_kwargs={'''files''': files}      )]
										snake_case__       :					int										=					[]
										for split_name, files in data_files.items():
																if isinstance(SCREAMING_SNAKE_CASE_      ,SCREAMING_SNAKE_CASE_      ):
																						snake_case__       :					List[str]										=					[files]
																# Use `dl_manager.iter_files` to skip hidden files in an extracted archive
																snake_case__       :					List[str]										=					[dl_manager.iter_files(SCREAMING_SNAKE_CASE_      ) for file in files]
																# Infer features is they are stoed in the arrow schema
																if self.info.features is None:
																						for file in itertools.chain.from_iterable(SCREAMING_SNAKE_CASE_      ):
																												with open(SCREAMING_SNAKE_CASE_      ,'''rb'''      ) as f:
																																		snake_case__       :					Tuple										=					datasets.Features.from_arrow_schema(pa.ipc.open_stream(SCREAMING_SNAKE_CASE_      ).schema      )
																												break
																splits.append(datasets.SplitGenerator(name=SCREAMING_SNAKE_CASE_      ,gen_kwargs={'''files''': files}      )      )
										return splits

				def       _lowerCamelCase					(   self   :     Optional[Any]      ,SCREAMING_SNAKE_CASE_   :     pa.Table      ):
										if self.info.features is not None:
																# more expensive cast to support nested features with keys in a different order
																# allows str <-> int/float or str to Audio for example
																snake_case__       :					Union[str, Any]										=					table_cast(SCREAMING_SNAKE_CASE_      ,self.info.features.arrow_schema      )
										return pa_table





				def       _lowerCamelCase					(   self   :     Tuple      ,SCREAMING_SNAKE_CASE_   :     Any      ):
										for file_idx, file in enumerate(itertools.chain.from_iterable(SCREAMING_SNAKE_CASE_      )      ):
																with open(SCREAMING_SNAKE_CASE_      ,'''rb'''      ) as f:
																						try:
																												for batch_idx, record_batch in enumerate(pa.ipc.open_stream(SCREAMING_SNAKE_CASE_      )      ):
																																		snake_case__       :					List[str]										=					pa.Table.from_batches([record_batch]      )
																																		# Uncomment for debugging (will print the Arrow table size and elements)
																																		# logger.warning(f"pa_table: {pa_table} num rows: {pa_table.num_rows}")
																																		# logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
																																		yield F'''{file_idx}_{batch_idx}''', self._cast_table(SCREAMING_SNAKE_CASE_      )
																						except ValueError as e:
																												logger.error(F'''Failed to read file \'{file}\' with error {type(SCREAMING_SNAKE_CASE_      )}: {e}'''      )
																												raise








"""simple docstring"""





import json
import os
from functools import lru_cache
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	      =    logging.get_logger(__name__)

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

_lowercase	      =    {
    """vocab_file""": {
        """gpt2""": """https://huggingface.co/gpt2/resolve/main/vocab.json""",
        """gpt2-medium""": """https://huggingface.co/gpt2-medium/resolve/main/vocab.json""",
        """gpt2-large""": """https://huggingface.co/gpt2-large/resolve/main/vocab.json""",
        """gpt2-xl""": """https://huggingface.co/gpt2-xl/resolve/main/vocab.json""",
        """distilgpt2""": """https://huggingface.co/distilgpt2/resolve/main/vocab.json""",
    },
    """merges_file""": {
        """gpt2""": """https://huggingface.co/gpt2/resolve/main/merges.txt""",
        """gpt2-medium""": """https://huggingface.co/gpt2-medium/resolve/main/merges.txt""",
        """gpt2-large""": """https://huggingface.co/gpt2-large/resolve/main/merges.txt""",
        """gpt2-xl""": """https://huggingface.co/gpt2-xl/resolve/main/merges.txt""",
        """distilgpt2""": """https://huggingface.co/distilgpt2/resolve/main/merges.txt""",
    },
}

_lowercase	      =    {
    """gpt2""": 10_24,
    """gpt2-medium""": 10_24,
    """gpt2-large""": 10_24,
    """gpt2-xl""": 10_24,
    """distilgpt2""": 10_24,
}

@lru_cache()
def 		lowerCAmelCase							( ):
						'''simple docstring'''


						snake_case__       :					Optional[int]										=					(
						    list(range(ord('''!'''		)      ,			ord('''~'''		) + 1		)		) + list(range(ord('''¡'''		)      ,			ord('''¬'''		) + 1		)		) + list(range(ord('''®'''		)      ,			ord('''ÿ'''		) + 1		)		)
						)
						snake_case__       :					Optional[Any]										=					bs[:]
						snake_case__       :					Union[str, Any]										=					0
						for b in range(2**8		):
												if b not in bs:
																		bs.append(lowerCamelCase		)
																		cs.append(2**8 + n		)
																		n += 1
						snake_case__       :					Dict										=					[chr(lowerCamelCase		) for n in cs]
						return dict(zip(lowerCamelCase      ,			lowerCamelCase		)		)

def 		lowerCAmelCase							( lowerCamelCase		):
						'''simple docstring'''


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

class       __lowercase       (			snake_case_	):


				'''simple docstring'''


				_lowerCAmelCase				=VOCAB_FILES_NAMES
				_lowerCAmelCase				=PRETRAINED_VOCAB_FILES_MAP
				_lowerCAmelCase				=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				_lowerCAmelCase				=["input_ids", "attention_mask"]

				def __init__(   self   :     List[str]      ,SCREAMING_SNAKE_CASE_   :     Dict      ,SCREAMING_SNAKE_CASE_   :     Any      ,SCREAMING_SNAKE_CASE_   :     str="replace"      ,SCREAMING_SNAKE_CASE_   :     Dict="<|endoftext|>"      ,SCREAMING_SNAKE_CASE_   :     List[Any]="<|endoftext|>"      ,SCREAMING_SNAKE_CASE_   :     Any="<|endoftext|>"      ,SCREAMING_SNAKE_CASE_   :     Optional[int]=None      ,SCREAMING_SNAKE_CASE_   :     str=False      ,SCREAMING_SNAKE_CASE_   :     Union[str, Any]=False      ,**SCREAMING_SNAKE_CASE_   :     Dict      ,):
										snake_case__       :					Dict										=					AddedToken(SCREAMING_SNAKE_CASE_      ,lstrip=SCREAMING_SNAKE_CASE_      ,rstrip=SCREAMING_SNAKE_CASE_      ) if isinstance(SCREAMING_SNAKE_CASE_      ,SCREAMING_SNAKE_CASE_      ) else bos_token
										snake_case__       :					Union[str, Any]										=					AddedToken(SCREAMING_SNAKE_CASE_      ,lstrip=SCREAMING_SNAKE_CASE_      ,rstrip=SCREAMING_SNAKE_CASE_      ) if isinstance(SCREAMING_SNAKE_CASE_      ,SCREAMING_SNAKE_CASE_      ) else eos_token
										snake_case__       :					Union[str, Any]										=					AddedToken(SCREAMING_SNAKE_CASE_      ,lstrip=SCREAMING_SNAKE_CASE_      ,rstrip=SCREAMING_SNAKE_CASE_      ) if isinstance(SCREAMING_SNAKE_CASE_      ,SCREAMING_SNAKE_CASE_      ) else unk_token
										snake_case__       :					List[str]										=					AddedToken(SCREAMING_SNAKE_CASE_      ,lstrip=SCREAMING_SNAKE_CASE_      ,rstrip=SCREAMING_SNAKE_CASE_      ) if isinstance(SCREAMING_SNAKE_CASE_      ,SCREAMING_SNAKE_CASE_      ) else pad_token
										super().__init__(
										    errors=SCREAMING_SNAKE_CASE_      ,unk_token=SCREAMING_SNAKE_CASE_      ,bos_token=SCREAMING_SNAKE_CASE_      ,eos_token=SCREAMING_SNAKE_CASE_      ,pad_token=SCREAMING_SNAKE_CASE_      ,add_prefix_space=SCREAMING_SNAKE_CASE_      ,add_bos_token=SCREAMING_SNAKE_CASE_      ,**SCREAMING_SNAKE_CASE_      ,)
										snake_case__       :					Tuple										=					add_bos_token

										with open(SCREAMING_SNAKE_CASE_      ,encoding='''utf-8'''      ) as vocab_handle:
																snake_case__       :					List[Any]										=					json.load(SCREAMING_SNAKE_CASE_      )
										snake_case__       :					List[str]										=					{v: k for k, v in self.encoder.items()}
										snake_case__       :					Optional[int]										=					errors  # how to handle errors in decoding
										snake_case__       :					List[str]										=					bytes_to_unicode()
										snake_case__       :					Any										=					{v: k for k, v in self.byte_encoder.items()}
										with open(SCREAMING_SNAKE_CASE_      ,encoding='''utf-8'''      ) as merges_handle:
																snake_case__       :					Tuple										=					merges_handle.read().split('''\n'''      )[1:-1]
										snake_case__       :					Union[str, Any]										=					[tuple(merge.split()      ) for merge in bpe_merges]
										snake_case__       :					Optional[Any]										=					dict(zip(SCREAMING_SNAKE_CASE_      ,range(len(SCREAMING_SNAKE_CASE_      )      )      )      )
										snake_case__       :					int										=					{}
										snake_case__       :					Dict										=					add_prefix_space

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

				@property
				def       _lowerCamelCase					(   self   :     Union[str, Any]      ):
										return len(self.encoder      )

				def       _lowerCamelCase					(   self   :     List[str]      ):
										return dict(self.encoder      ,**self.added_tokens_encoder      )

				def       _lowerCamelCase					(   self   :     Union[str, Any]      ,SCREAMING_SNAKE_CASE_   :     Union[str, Any]      ):
										if token in self.cache:
																return self.cache[token]
										snake_case__       :					Optional[int]										=					tuple(SCREAMING_SNAKE_CASE_      )
										snake_case__       :					str										=					get_pairs(SCREAMING_SNAKE_CASE_      )

										if not pairs:
																return token

										while True:
																snake_case__       :					Any										=					min(SCREAMING_SNAKE_CASE_      ,key=lambda SCREAMING_SNAKE_CASE_      : self.bpe_ranks.get(SCREAMING_SNAKE_CASE_      ,float('''inf'''      )      )      )
																if bigram not in self.bpe_ranks:
																						break
																snake_case__			,	snake_case__       :					List[Any]										=					bigram
																snake_case__       :					Tuple										=					[]
																snake_case__       :					int										=					0
																while i < len(SCREAMING_SNAKE_CASE_      ):
																						try:
																												snake_case__       :					Optional[Any]										=					word.index(SCREAMING_SNAKE_CASE_      ,SCREAMING_SNAKE_CASE_      )
																						except ValueError:
																												new_word.extend(word[i:]      )
																												break
																						else:
																												new_word.extend(word[i:j]      )
																												snake_case__       :					Union[str, Any]										=					j

																						if word[i] == first and i < len(SCREAMING_SNAKE_CASE_      ) - 1 and word[i + 1] == second:
																												new_word.append(first + second      )
																												i += 2
																						else:
																												new_word.append(word[i]      )
																												i += 1
																snake_case__       :					str										=					tuple(SCREAMING_SNAKE_CASE_      )
																snake_case__       :					Optional[Any]										=					new_word
																if len(SCREAMING_SNAKE_CASE_      ) == 1:
																						break
																else:
																						snake_case__       :					Tuple										=					get_pairs(SCREAMING_SNAKE_CASE_      )
										snake_case__       :					str										=					''' '''.join(SCREAMING_SNAKE_CASE_      )
										snake_case__       :					List[Any]										=					word
										return word

				def       _lowerCamelCase					(   self   :     List[str]      ,SCREAMING_SNAKE_CASE_   :     Tuple      ,SCREAMING_SNAKE_CASE_   :     Tuple=None      ):
										if self.add_bos_token:
																snake_case__       :					int										=					[self.bos_token_id]
										else:
																snake_case__       :					Tuple										=					[]

										snake_case__       :					List[str]										=					bos_token_ids + token_ids_a

										if token_ids_a is None:
																return output

										return output + bos_token_ids + token_ids_a

				def       _lowerCamelCase					(   self   :     List[Any]      ,SCREAMING_SNAKE_CASE_   :     List[int]      ,SCREAMING_SNAKE_CASE_   :     Optional[List[int]] = None      ,SCREAMING_SNAKE_CASE_   :     bool = False      ):
										if already_has_special_tokens:
																return super().get_special_tokens_mask(
																    token_ids_a=SCREAMING_SNAKE_CASE_      ,token_ids_a=SCREAMING_SNAKE_CASE_      ,already_has_special_tokens=SCREAMING_SNAKE_CASE_      )

										if not self.add_bos_token:
																return super().get_special_tokens_mask(
																    token_ids_a=SCREAMING_SNAKE_CASE_      ,token_ids_a=SCREAMING_SNAKE_CASE_      ,already_has_special_tokens=SCREAMING_SNAKE_CASE_      )

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

				def       _lowerCamelCase					(   self   :     Dict      ,SCREAMING_SNAKE_CASE_   :     int      ):
										snake_case__       :					Dict										=					[]
										for token in re.findall(self.pat      ,SCREAMING_SNAKE_CASE_      ):
																snake_case__       :					Union[str, Any]										=					''''''.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(SCREAMING_SNAKE_CASE_      ).split(''' '''      )      )
										return bpe_tokens

				def       _lowerCamelCase					(   self   :     int      ,SCREAMING_SNAKE_CASE_   :     str      ):
										return self.encoder.get(SCREAMING_SNAKE_CASE_      ,self.encoder.get(self.unk_token      )      )

				def       _lowerCamelCase					(   self   :     Any      ,SCREAMING_SNAKE_CASE_   :     Tuple      ):
										return self.decoder.get(SCREAMING_SNAKE_CASE_      )

				def       _lowerCamelCase					(   self   :     List[Any]      ,SCREAMING_SNAKE_CASE_   :     str      ):
										snake_case__       :					List[str]										=					''''''.join(SCREAMING_SNAKE_CASE_      )
										snake_case__       :					Union[str, Any]										=					bytearray([self.byte_decoder[c] for c in text]      ).decode('''utf-8'''      ,errors=self.errors      )
										return text

				def       _lowerCamelCase					(   self   :     Optional[Any]      ,SCREAMING_SNAKE_CASE_   :     str      ,SCREAMING_SNAKE_CASE_   :     Optional[str] = None      ):
										if not os.path.isdir(SCREAMING_SNAKE_CASE_      ):
																logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''      )
																return
										snake_case__       :					Optional[Any]										=					os.path.join(
										    SCREAMING_SNAKE_CASE_      ,(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']      )
										snake_case__       :					List[str]										=					os.path.join(
										    SCREAMING_SNAKE_CASE_      ,(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''merges_file''']      )

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

										snake_case__       :					Optional[int]										=					0
										with open(SCREAMING_SNAKE_CASE_      ,'''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 SCREAMING_SNAKE_CASE_      : 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!'''      )
																												snake_case__       :					List[str]										=					token_index
																						writer.write(''' '''.join(SCREAMING_SNAKE_CASE_      ) + '''\n'''      )
																						index += 1

										return vocab_file, merge_file

				def       _lowerCamelCase					(   self   :     str      ,SCREAMING_SNAKE_CASE_   :     Any      ,SCREAMING_SNAKE_CASE_   :     int=False      ,**SCREAMING_SNAKE_CASE_   :     Optional[Any]      ):
										snake_case__       :					List[Any]										=					kwargs.pop('''add_prefix_space'''      ,self.add_prefix_space      )
										if is_split_into_words or add_prefix_space:
																snake_case__       :					Optional[Any]										=					''' ''' + text
										return (text, kwargs)





				def       _lowerCamelCase					(   self   :     int      ,SCREAMING_SNAKE_CASE_   :     "Conversation"      ):
										snake_case__       :					Dict										=					[]
										for is_user, text in conversation.iter_texts():
																input_ids.extend(self.encode(SCREAMING_SNAKE_CASE_      ,add_special_tokens=SCREAMING_SNAKE_CASE_      ) + [self.eos_token_id]      )
										if len(SCREAMING_SNAKE_CASE_      ) > self.model_max_length:
																snake_case__       :					Dict										=					input_ids[-self.model_max_length :]
										return input_ids


