


'''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


UpperCAmelCase_      :		int          =		re.compile("[^A-Za-z_0-9]")
# parameters used in DuplicationIndex
UpperCAmelCase_      :		Tuple          =		10
UpperCAmelCase_      :		Dict          =		256


def    UpperCAmelCase_  (       A      ):
   '''simple docstring'''





   if len(A      ) < MIN_NUM_TOKENS:
      return None
   _a					:  Union[str, Any]						=  MinHash(num_perm=A      )
   for token in set(A      ):
      min_hash.update(token.encode()      )
   return min_hash


def    UpperCAmelCase_  (       A      ):
   '''simple docstring'''





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







class 					a			:
 '''simple docstring'''




 def __init__(    self		,      *,
     lowerCamelCase_ = 0.85		,      )      ->    List[Any]:
    _a					:  int						=  duplication_jaccard_threshold
    _a					:  Dict						=  NUM_PERM
    _a					:  List[Any]						=  MinHashLSH(threshold=self._duplication_jaccard_threshold		,      num_perm=self._num_perm      )

    _a					:  Optional[Any]						=  defaultdict(lowerCamelCase_      )




 def   __UpperCamelCase   (    self		,      lowerCamelCase_		,      lowerCamelCase_      )      ->    None:
    _a					:  List[Any]						=  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      )      ->    List[List[Dict]]:
    _a					:  Union[str, Any]						=  []
    for base, duplicates in self._duplicate_clusters.items():
       _a					:  Union[str, Any]						=  [base] + list(lowerCamelCase_      )
       # reformat the cluster to be a list of dict
       _a					:  List[str]						=  [{'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		,      lowerCamelCase_      )      ->    None:
    _a					:  Tuple						=  self.get_duplicate_clusters()
    with open(lowerCamelCase_		,      'w'      ) as f:
       json.dump(lowerCamelCase_		,      lowerCamelCase_      )





def    UpperCAmelCase_  (       A      ):
   '''simple docstring'''





   _a		,						_a					:  List[Any]						=  element
   _a					:  Union[str, 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    UpperCAmelCase_  (       A      ):
   '''simple docstring'''





   with mp.Pool() as pool:
      for data in pool.imap_unordered(
          _compute_min_hash		,	ThreadedIterator(A		,	max_queue_size=1_0_0_0_0      )		,	chunksize=1_0_0		,	):
         if data is not None:
            yield data


def    UpperCAmelCase_  (       A		,	A      ):
   '''simple docstring'''





   _a					:  int						=  DuplicationIndex(duplication_jaccard_threshold=A      )

   for filename, min_hash in tqdm(ThreadedIterator(minhash_iter(enumerate(A      )      )		,	max_queue_size=1_0_0      )      ):
      di.add(A		,	A      )

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


def    UpperCAmelCase_  (       A		,	A      ):
   '''simple docstring'''





   _a					:  Optional[int]						=  get_tokens(A      )
   _a					:  Union[str, Any]						=  get_tokens(A      )
   return len(tokensa & tokensa      ) / len(tokensa | tokensa      )


UpperCAmelCase_      :		Optional[Any]          =		None


def    UpperCAmelCase_  (       A		,	A      ):
   '''simple docstring'''





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


def    UpperCAmelCase_  (       A		,	A		,	A      ):
   '''simple docstring'''





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







def    UpperCAmelCase_  (       A		,	A = 0.85      ):
   '''simple docstring'''





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

   # update duplicate_clusters
   for cluster in duplicate_clusters:
      for element in cluster:
         _a					:  Union[str, Any]						=  element['base_index'] in extreme_dict
         if element["is_extreme"]:
            _a					:  Optional[int]						=  extreme_dict[element['base_index']]['copies']

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

   return ds_filter, duplicate_clusters






'''simple docstring'''




from math import cos, sin, sqrt, tau

from audio_filters.iir_filter import IIRFilter


def    UpperCAmelCase_  (       A		,	A		,	A = 1 / sqrt(2      )      ):
   '''simple docstring'''





   _a					:  List[Any]						=  tau * frequency / samplerate
   _a					:  Tuple						=  sin(A      )
   _a					:  List[Any]						=  cos(A      )
   _a					:  Union[str, Any]						=  _sin / (2 * q_factor)

   _a					:  Dict						=  (1 - _cos) / 2
   _a					:  Any						=  1 - _cos

   _a					:  Any						=  1 + alpha
   _a					:  int						=  -2 * _cos
   _a					:  str						=  1 - alpha

   _a					:  Optional[Any]						=  IIRFilter(2      )
   filt.set_coefficients([aa, aa, aa]		,	[ba, ba, ba]      )
   return filt


def    UpperCAmelCase_  (       A		,	A		,	A = 1 / sqrt(2      )      ):
   '''simple docstring'''





   _a					:  int						=  tau * frequency / samplerate
   _a					:  int						=  sin(A      )
   _a					:  Union[str, Any]						=  cos(A      )
   _a					:  int						=  _sin / (2 * q_factor)

   _a					:  Dict						=  (1 + _cos) / 2
   _a					:  int						=  -1 - _cos

   _a					:  Optional[int]						=  1 + alpha
   _a					:  str						=  -2 * _cos
   _a					:  Dict						=  1 - alpha

   _a					:  List[str]						=  IIRFilter(2      )
   filt.set_coefficients([aa, aa, aa]		,	[ba, ba, ba]      )
   return filt


def    UpperCAmelCase_  (       A		,	A		,	A = 1 / sqrt(2      )      ):
   '''simple docstring'''





   _a					:  str						=  tau * frequency / samplerate
   _a					:  Dict						=  sin(A      )
   _a					:  int						=  cos(A      )
   _a					:  Dict						=  _sin / (2 * q_factor)

   _a					:  List[Any]						=  _sin / 2
   _a					:  List[str]						=  0
   _a					:  Dict						=  -ba

   _a					:  List[Any]						=  1 + alpha
   _a					:  Union[str, Any]						=  -2 * _cos
   _a					:  List[Any]						=  1 - alpha

   _a					:  int						=  IIRFilter(2      )
   filt.set_coefficients([aa, aa, aa]		,	[ba, ba, ba]      )
   return filt


def    UpperCAmelCase_  (       A		,	A		,	A = 1 / sqrt(2      )      ):
   '''simple docstring'''





   _a					:  Optional[Any]						=  tau * frequency / samplerate
   _a					:  Tuple						=  sin(A      )
   _a					:  Tuple						=  cos(A      )
   _a					:  Dict						=  _sin / (2 * q_factor)

   _a					:  List[Any]						=  1 - alpha
   _a					:  int						=  -2 * _cos
   _a					:  List[Any]						=  1 + alpha

   _a					:  str						=  IIRFilter(2      )
   filt.set_coefficients([ba, ba, ba]		,	[ba, ba, ba]      )
   return filt


def    UpperCAmelCase_  (       A		,	A		,	A		,	A = 1 / sqrt(2      )		,	):
   '''simple docstring'''





   _a					:  Union[str, Any]						=  tau * frequency / samplerate
   _a					:  str						=  sin(A      )
   _a					:  str						=  cos(A      )
   _a					:  List[Any]						=  _sin / (2 * q_factor)
   _a					:  Optional[Any]						=  1_0 ** (gain_db / 4_0)

   _a					:  Dict						=  1 + alpha * big_a
   _a					:  str						=  -2 * _cos
   _a					:  Tuple						=  1 - alpha * big_a
   _a					:  Tuple						=  1 + alpha / big_a
   _a					:  str						=  -2 * _cos
   _a					:  Union[str, Any]						=  1 - alpha / big_a

   _a					:  Optional[int]						=  IIRFilter(2      )
   filt.set_coefficients([aa, aa, aa]		,	[ba, ba, ba]      )
   return filt


def    UpperCAmelCase_  (       A		,	A		,	A		,	A = 1 / sqrt(2      )		,	):
   '''simple docstring'''





   _a					:  Optional[int]						=  tau * frequency / samplerate
   _a					:  List[str]						=  sin(A      )
   _a					:  Tuple						=  cos(A      )
   _a					:  Union[str, Any]						=  _sin / (2 * q_factor)
   _a					:  str						=  1_0 ** (gain_db / 4_0)
   _a					:  Optional[Any]						=  (big_a + 1) - (big_a - 1) * _cos
   _a					:  List[str]						=  (big_a + 1) + (big_a - 1) * _cos
   _a					:  List[Any]						=  (big_a - 1) - (big_a + 1) * _cos
   _a					:  Dict						=  (big_a - 1) + (big_a + 1) * _cos
   _a					:  Tuple						=  2 * sqrt(A      ) * alpha

   _a					:  Any						=  big_a * (pmc + aaa)
   _a					:  Optional[int]						=  2 * big_a * mpc
   _a					:  Dict						=  big_a * (pmc - aaa)
   _a					:  List[str]						=  ppmc + aaa
   _a					:  int						=  -2 * pmpc
   _a					:  Tuple						=  ppmc - aaa

   _a					:  Tuple						=  IIRFilter(2      )
   filt.set_coefficients([aa, aa, aa]		,	[ba, ba, ba]      )
   return filt







def    UpperCAmelCase_  (       A		,	A		,	A		,	A = 1 / sqrt(2      )		,	):
   '''simple docstring'''





   _a					:  Dict						=  tau * frequency / samplerate
   _a					:  Tuple						=  sin(A      )
   _a					:  Any						=  cos(A      )
   _a					:  int						=  _sin / (2 * q_factor)
   _a					:  str						=  1_0 ** (gain_db / 4_0)
   _a					:  List[Any]						=  (big_a + 1) - (big_a - 1) * _cos
   _a					:  Union[str, Any]						=  (big_a + 1) + (big_a - 1) * _cos
   _a					:  List[Any]						=  (big_a - 1) - (big_a + 1) * _cos
   _a					:  List[str]						=  (big_a - 1) + (big_a + 1) * _cos
   _a					:  Union[str, Any]						=  2 * sqrt(A      ) * alpha

   _a					:  Optional[Any]						=  big_a * (ppmc + aaa)
   _a					:  List[str]						=  -2 * big_a * pmpc
   _a					:  Any						=  big_a * (ppmc - aaa)
   _a					:  List[Any]						=  pmc + aaa
   _a					:  Tuple						=  2 * mpc
   _a					:  List[Any]						=  pmc - aaa

   _a					:  str						=  IIRFilter(2      )
   filt.set_coefficients([aa, aa, aa]		,	[ba, ba, ba]      )
   return filt


