"""simple docstring"""







import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type

from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import ThreadedIterator
from tqdm import tqdm


SCREAMING_SNAKE_CASE									=						re.compile('[^A-Za-z_0-9]')
# parameters used in DuplicationIndex
SCREAMING_SNAKE_CASE									=						10
SCREAMING_SNAKE_CASE									=						256


def      __lowerCAmelCase(		__UpperCAmelCase			):






	"""simple docstring"""





	if len(__UpperCAmelCase			) < MIN_NUM_TOKENS:
		return None
	_lowercase :    List[Any]							=							MinHash(num_perm=__UpperCAmelCase			)
	for token in set(__UpperCAmelCase			):
		min_hash.update(token.encode()			)
	return min_hash


def      __lowerCAmelCase(		__UpperCAmelCase			):






	"""simple docstring"""





	return {t for t in NON_ALPHA.split(__UpperCAmelCase			) if len(t.strip()			) > 0}



class  _lowerCamelCase			:







				def __init__( self    :       Any			,					*,
				    lowerCamelCase_    :       float = 0.85			,					):

					"""simple docstring"""






					_lowercase :    str							=							duplication_jaccard_threshold
					_lowercase :    Union[str, Any]							=							NUM_PERM
					_lowercase :    Dict							=							MinHashLSH(threshold=self._duplication_jaccard_threshold			,					num_perm=self._num_perm						)

					_lowercase :    List[str]							=							defaultdict(lowerCamelCase_						)







				def 							__UpperCAmelCase					( self    :       str			,					lowerCamelCase_    :       Tuple			,					lowerCamelCase_    :       MinHash						):

					"""simple docstring"""






					_lowercase :    Optional[int]							=							self._index.query(lowerCamelCase_						)
					if code_key in self._index.keys:
						print(F'''Duplicate key {code_key}'''						)
						return

					self._index.insert(lowerCamelCase_			,					lowerCamelCase_						)
					if len(lowerCamelCase_						) > 0:
						for base_duplicate in close_duplicates:
							if base_duplicate in self._duplicate_clusters:
								self._duplicate_clusters[base_duplicate].add(lowerCamelCase_						)
								break
						else:
							self._duplicate_clusters[close_duplicates[0]].add(lowerCamelCase_						)







				def 							__UpperCAmelCase					( self    :       Tuple						):

					"""simple docstring"""






					_lowercase :    str							=							[]
					for base, duplicates in self._duplicate_clusters.items():
						_lowercase :    int							=							[base] + list(lowerCamelCase_						)
						# reformat the cluster to be a list of dict
						_lowercase :    int							=							[{'base_index': el[0], 'repo_name': el[1], 'path': el[2]} for el in cluster]
						duplicate_clusters.append(lowerCamelCase_						)
					return duplicate_clusters







				def 							__UpperCAmelCase					( self    :       int			,					lowerCamelCase_    :       Tuple						):

					"""simple docstring"""






					_lowercase :    Dict							=							self.get_duplicate_clusters()
					with open(lowerCamelCase_			,					'w'						) as f:
						json.dump(lowerCamelCase_			,					lowerCamelCase_						)



def      __lowerCAmelCase(		__UpperCAmelCase			):






	"""simple docstring"""





	_lowercase				,      _lowercase :    str							=							element
	_lowercase :    List[Any]							=							get_min_hash([t for t in NON_ALPHA.split(data['content']			) if len(t.strip()			) > 0]			)
	if min_hash is not None:
		return (index, data["repo_name"], data["path"]), min_hash


def      __lowerCAmelCase(		__UpperCAmelCase			):






	"""simple docstring"""





	with mp.Pool() as pool:
		for data in pool.imap_unordered(
		    _compute_min_hash     ,ThreadedIterator(__UpperCAmelCase     ,max_queue_size=10_000			)     ,chunksize=100     ,):
			if data is not None:
				yield data


def      __lowerCAmelCase(		__UpperCAmelCase     ,__UpperCAmelCase			):






	"""simple docstring"""





	_lowercase :    Optional[int]							=							DuplicationIndex(duplication_jaccard_threshold=__UpperCAmelCase			)

	for filename, min_hash in tqdm(ThreadedIterator(minhash_iter(enumerate(__UpperCAmelCase			)			)     ,max_queue_size=100			)			):
		di.add(__UpperCAmelCase     ,__UpperCAmelCase			)

	# Returns a List[Cluster] where Cluster is List[str] with the filenames.
	return di.get_duplicate_clusters()


def      __lowerCAmelCase(		__UpperCAmelCase     ,__UpperCAmelCase			):






	"""simple docstring"""





	_lowercase :    List[Any]							=							get_tokens(__UpperCAmelCase			)
	_lowercase :    str							=							get_tokens(__UpperCAmelCase			)
	return len(tokensa & tokensa			) / len(tokensa | tokensa			)


SCREAMING_SNAKE_CASE									=						None


def      __lowerCAmelCase(		__UpperCAmelCase     ,__UpperCAmelCase			):






	"""simple docstring"""





	_lowercase :    int							=							[]
	for elementa in cluster:
		_lowercase :    Tuple							=							_shared_dataset[elementa['base_index']]['content']
		for elementa in extremes:
			_lowercase :    Optional[int]							=							_shared_dataset[elementa['base_index']]['content']
			if jaccard_similarity(__UpperCAmelCase     ,__UpperCAmelCase			) >= jaccard_threshold:
				elementa["copies"] += 1
				break
		else:
			_lowercase :    List[str]							=							1
			extremes.append(__UpperCAmelCase			)
	return extremes


def      __lowerCAmelCase(		__UpperCAmelCase     ,__UpperCAmelCase     ,__UpperCAmelCase			):






	"""simple docstring"""





	global _shared_dataset
	_lowercase :    str							=							dataset
	_lowercase :    int							=							[]
	_lowercase :    Dict							=							partial(_find_cluster_extremes_shared     ,jaccard_threshold=__UpperCAmelCase			)
	with mp.Pool() as pool:
		for extremes in tqdm(
		    pool.imap_unordered(
		        __UpperCAmelCase     ,__UpperCAmelCase     ,)     ,total=len(__UpperCAmelCase			)     ,):
			extremes_list.append(__UpperCAmelCase			)
	return extremes_list







def      __lowerCAmelCase(		__UpperCAmelCase     ,__UpperCAmelCase = 0.8_5			):






	"""simple docstring"""





	_lowercase :    str							=							make_duplicate_clusters(__UpperCAmelCase     ,__UpperCAmelCase			)
	_lowercase :    Dict							=							{x['base_index'] for cluster in duplicate_clusters for x in cluster}
	_lowercase :    Optional[Any]							=							{}
	_lowercase :    Union[str, Any]							=							find_extremes(__UpperCAmelCase     ,__UpperCAmelCase     ,__UpperCAmelCase			)
	for extremes in extremes_clusters:
		for element in extremes:
			_lowercase :    Union[str, Any]							=							element
	_lowercase :    Union[str, Any]							=							duplicate_indices - set(extreme_dict.keys()			)
	_lowercase :    Tuple							=							dataset.filter(lambda __UpperCAmelCase     ,__UpperCAmelCase			: idx not in remove_indices     ,with_indices=__UpperCAmelCase			)

	# update duplicate_clusters
	for cluster in duplicate_clusters:
		for element in cluster:
			_lowercase :    Tuple							=							element['base_index'] in extreme_dict
			if element["is_extreme"]:
				_lowercase :    Optional[Any]							=							extreme_dict[element['base_index']]['copies']

	print(F'''Original dataset size: {len(__UpperCAmelCase			)}'''			)
	print(F'''Number of duplicate clusters: {len(__UpperCAmelCase			)}'''			)
	print(F'''Files in duplicate cluster: {len(__UpperCAmelCase			)}'''			)
	print(F'''Unique files in duplicate cluster: {len(__UpperCAmelCase			)}'''			)
	print(F'''Filtered dataset size: {len(__UpperCAmelCase			)}'''			)

	return ds_filter, duplicate_clusters




"""simple docstring"""







import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

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


SCREAMING_SNAKE_CASE									=						logging.get_logger(__name__)


SCREAMING_SNAKE_CASE									=						{'vocab_file': 'vocab.json', 'merges_file': 'merges.txt'}

# See all BART models at https://huggingface.co/models?filter=bart
SCREAMING_SNAKE_CASE									=						{
    'vocab_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/vocab.json',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/vocab.json',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json',
    },
    'merges_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/merges.txt',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/merges.txt',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt',
    },
}

SCREAMING_SNAKE_CASE									=						{
    'facebook/bart-base': 1024,
    'facebook/bart-large': 1024,
    'facebook/bart-large-mnli': 1024,
    'facebook/bart-large-cnn': 1024,
    'facebook/bart-large-xsum': 1024,
    'yjernite/bart_eli5': 1024,
}


@lru_cache()
def      __lowerCAmelCase(		):






	"""simple docstring"""





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


def      __lowerCAmelCase(		__UpperCAmelCase			):






	"""simple docstring"""





	_lowercase :    Tuple							=							set()
	_lowercase :    int							=							word[0]
	for char in word[1:]:
		pairs.add((prev_char, char)			)
		_lowercase :    Union[str, Any]							=							char
	return pairs







class  _lowerCamelCase			(__lowerCamelCase     ):
				_snake_case     =  VOCAB_FILES_NAMES
				_snake_case     =  PRETRAINED_VOCAB_FILES_MAP
				_snake_case     =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				_snake_case     =  ["input_ids", "attention_mask"]







				def __init__( self    :       int			,					lowerCamelCase_    :       Dict			,					lowerCamelCase_    :       List[str]			,					lowerCamelCase_    :       List[Any]="replace"			,					lowerCamelCase_    :       List[str]="<s>"			,					lowerCamelCase_    :       Optional[int]="</s>"			,					lowerCamelCase_    :       Tuple="</s>"			,					lowerCamelCase_    :       str="<s>"			,					lowerCamelCase_    :       Dict="<unk>"			,					lowerCamelCase_    :       Optional[Any]="<pad>"			,					lowerCamelCase_    :       List[Any]="<mask>"			,					lowerCamelCase_    :       str=False			,					**lowerCamelCase_    :       str			,					):

					"""simple docstring"""






					_lowercase :    int							=							AddedToken(lowerCamelCase_			,					lstrip=lowerCamelCase_			,					rstrip=lowerCamelCase_						) if isinstance(lowerCamelCase_			,					lowerCamelCase_						) else bos_token
					_lowercase :    int							=							AddedToken(lowerCamelCase_			,					lstrip=lowerCamelCase_			,					rstrip=lowerCamelCase_						) if isinstance(lowerCamelCase_			,					lowerCamelCase_						) else eos_token
					_lowercase :    Dict							=							AddedToken(lowerCamelCase_			,					lstrip=lowerCamelCase_			,					rstrip=lowerCamelCase_						) if isinstance(lowerCamelCase_			,					lowerCamelCase_						) else sep_token
					_lowercase :    Optional[int]							=							AddedToken(lowerCamelCase_			,					lstrip=lowerCamelCase_			,					rstrip=lowerCamelCase_						) if isinstance(lowerCamelCase_			,					lowerCamelCase_						) else cls_token
					_lowercase :    Any							=							AddedToken(lowerCamelCase_			,					lstrip=lowerCamelCase_			,					rstrip=lowerCamelCase_						) if isinstance(lowerCamelCase_			,					lowerCamelCase_						) else unk_token
					_lowercase :    Union[str, Any]							=							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
					_lowercase :    str							=							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_			,					**lowerCamelCase_			,					)

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

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







				@property
				def 							__UpperCAmelCase					( self    :       Dict						):

					"""simple docstring"""






					return len(self.encoder						)







				def 							__UpperCAmelCase					( self    :       int						):

					"""simple docstring"""






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







				def 							__UpperCAmelCase					( self    :       Optional[int]			,					lowerCamelCase_    :       Optional[int]						):

					"""simple docstring"""






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

					if not pairs:
						return token

					while True:
						_lowercase :    List[str]							=							min(lowerCamelCase_			,					key=lambda lowerCamelCase_						: self.bpe_ranks.get(lowerCamelCase_			,					float('inf'						)						)						)
						if bigram not in self.bpe_ranks:
							break
						_lowercase				,      _lowercase :    List[Any]							=							bigram
						_lowercase :    Optional[int]							=							[]
						_lowercase :    Optional[Any]							=							0
						while i < len(lowerCamelCase_						):
							try:
								_lowercase :    int							=							word.index(lowerCamelCase_			,					lowerCamelCase_						)
							except ValueError:
								new_word.extend(word[i:]						)
								break
							else:
								new_word.extend(word[i:j]						)
								_lowercase :    Dict							=							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
						_lowercase :    Tuple							=							tuple(lowerCamelCase_						)
						_lowercase :    Dict							=							new_word
						if len(lowerCamelCase_						) == 1:
							break
						else:
							_lowercase :    str							=							get_pairs(lowerCamelCase_						)
					_lowercase :    str							=							' '.join(lowerCamelCase_						)
					_lowercase :    List[str]							=							word
					return word







				def 							__UpperCAmelCase					( self    :       Tuple			,					lowerCamelCase_    :       str						):

					"""simple docstring"""






					_lowercase :    Union[str, Any]							=							[]
					for token in re.findall(self.pat			,					lowerCamelCase_						):
						_lowercase :    List[str]							=							''.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    :       int			,					lowerCamelCase_    :       Optional[Any]						):

					"""simple docstring"""






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







				def 							__UpperCAmelCase					( self    :       List[Any]			,					lowerCamelCase_    :       Dict						):

					"""simple docstring"""






					return self.decoder.get(lowerCamelCase_						)







				def 							__UpperCAmelCase					( self    :       Optional[int]			,					lowerCamelCase_    :       Any						):

					"""simple docstring"""






					_lowercase :    Dict							=							''.join(lowerCamelCase_						)
					_lowercase :    Optional[Any]							=							bytearray([self.byte_decoder[c] for c in text]						).decode('utf-8'			,					errors=self.errors						)
					return text







				def 							__UpperCAmelCase					( self    :       int			,					lowerCamelCase_    :       str			,					lowerCamelCase_    :       Optional[str] = None						):

					"""simple docstring"""






					if not os.path.isdir(lowerCamelCase_						):
						logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''						)
						return
					_lowercase :    Union[str, Any]							=							os.path.join(
					    lowerCamelCase_			,					(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']						)
					_lowercase :    List[Any]							=							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'						)

					_lowercase :    Optional[int]							=							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!'						)
								_lowercase :    int							=							token_index
							writer.write(' '.join(lowerCamelCase_						) + '\n'						)
							index += 1

					return vocab_file, merge_file







				def 							__UpperCAmelCase					( self    :       Any			,					lowerCamelCase_    :       List[int]			,					lowerCamelCase_    :       Optional[List[int]] = None						):

					"""simple docstring"""






					if token_ids_a is None:
						return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
					_lowercase :    Optional[Any]							=							[self.cls_token_id]
					_lowercase :    List[Any]							=							[self.sep_token_id]
					return cls + token_ids_a + sep + sep + token_ids_a + sep







				def 							__UpperCAmelCase					( self    :       Optional[Any]			,					lowerCamelCase_    :       List[int]			,					lowerCamelCase_    :       Optional[List[int]] = None			,					lowerCamelCase_    :       bool = 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, 1] + ([0] * len(lowerCamelCase_						)) + [1]







				def 							__UpperCAmelCase					( self    :       List[Any]			,					lowerCamelCase_    :       List[int]			,					lowerCamelCase_    :       Optional[List[int]] = None						):

					"""simple docstring"""






					_lowercase :    int							=							[self.sep_token_id]
					_lowercase :    Optional[Any]							=							[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 + sep + token_ids_a + sep						) * [0]







				def 							__UpperCAmelCase					( self    :       Tuple			,					lowerCamelCase_    :       Optional[Any]			,					lowerCamelCase_    :       str=False			,					**lowerCamelCase_    :       int						):

					"""simple docstring"""






					_lowercase :    Dict							=							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()):
						_lowercase :    Dict							=							' ' + text
					return (text, kwargs)



