





'''simple docstring'''




import gzip
import hashlib
import json
import multiprocessing
import os
import re
import shutil
import time
from pathlib import Path

import numpy as np
from arguments import PreprocessingArguments
from datasets import load_dataset
from minhash_deduplication import deduplicate_dataset

from transformers import AutoTokenizer, HfArgumentParser


_A:					Dict				=				re.compile(r"""\s+""")







def _lowerCAmelCase     (      _lowerCAmelCase    )->     List[Any]:
 return {"hash": hashlib.mda(re.sub(lowercase_       ,    ''       ,    example['content']    ).encode('utf-8'    )    ).hexdigest()}







def _lowerCAmelCase     (      _lowerCAmelCase    )->     int:
 __UpperCAmelCase					=   [len(lowercase_    ) for line in example["""content"""].splitlines()]
 return {"line_mean": np.mean(lowercase_    ), "line_max": max(lowercase_    )}







def _lowerCAmelCase     (      _lowerCAmelCase    )->     Union[str, Any]:
 __UpperCAmelCase					=   np.mean([c.isalnum() for c in example['content']]    )
 return {"alpha_frac": alpha_frac}







def _lowerCAmelCase     (      _lowerCAmelCase       ,    _lowerCAmelCase    )->     int:
 if example["hash"] in uniques:
  uniques.remove(example['hash']    )
  return True
 else:
  return False







def _lowerCAmelCase     (      _lowerCAmelCase       ,    _lowerCAmelCase=5    )->     List[str]:
 __UpperCAmelCase					=   ["""auto-generated""", """autogenerated""", """automatically generated"""]
 __UpperCAmelCase					=   example["""content"""].splitlines()
 for _, line in zip(range(lowercase_    )       ,    lowercase_    ):
  for keyword in keywords:
   if keyword in line.lower():
    return {"autogenerated": True}
 else:
  return {"autogenerated": False}







def _lowerCAmelCase     (      _lowerCAmelCase       ,    _lowerCAmelCase=5       ,    _lowerCAmelCase=0.05    )->     Union[str, Any]:
 __UpperCAmelCase					=   ["""unit tests""", """test file""", """configuration file"""]
 __UpperCAmelCase					=   example["""content"""].splitlines()
 __UpperCAmelCase					=   0
 __UpperCAmelCase					=   0
 # first test
 for _, line in zip(range(lowercase_    )       ,    lowercase_    ):
  for keyword in keywords:
   if keyword in line.lower():
    return {"config_or_test": True}
    # second test
 __UpperCAmelCase					=   example["""content"""].count('\n'    )
 __UpperCAmelCase					=   int(coeff * nlines    )
 for line in lines:
  count_config += line.lower().count('config'    )
  count_test += line.lower().count('test'    )
  if count_config > threshold or count_test > threshold:
   return {"config_or_test": True}
 return {"config_or_test": False}







def _lowerCAmelCase     (      _lowerCAmelCase    )->     List[str]:
 __UpperCAmelCase					=   ["""def """, """class """, """for """, """while """]
 __UpperCAmelCase					=   example["""content"""].splitlines()
 for line in lines:
  for keyword in keywords:
   if keyword in line.lower():
    return {"has_no_keywords": False}
 return {"has_no_keywords": True}







def _lowerCAmelCase     (      _lowerCAmelCase       ,    _lowerCAmelCase=4    )->     List[str]:
 __UpperCAmelCase					=   example["""content"""].splitlines()
 __UpperCAmelCase					=   0
 for line in lines:
  counter += line.lower().count('='    )
  if counter > minimum:
   return {"has_few_assignments": False}
 return {"has_few_assignments": True}







def _lowerCAmelCase     (      _lowerCAmelCase    )->     int:
 __UpperCAmelCase					=   tokenizer(example['content']       ,    truncation=lowercase_    )["""input_ids"""]
 __UpperCAmelCase					=   len(example['content']    ) / len(lowercase_    )
 return {"ratio": ratio}







def _lowerCAmelCase     (      _lowerCAmelCase    )->     Optional[Any]:
 __UpperCAmelCase					=   {}
 results.update(get_hash(lowercase_    )    )
 results.update(line_stats(lowercase_    )    )
 results.update(alpha_stats(lowercase_    )    )
 results.update(char_token_ratio(lowercase_    )    )
 results.update(is_autogenerated(lowercase_    )    )
 results.update(is_config_or_test(lowercase_    )    )
 results.update(has_no_keywords(lowercase_    )    )
 results.update(has_few_assignments(lowercase_    )    )
 return results







def _lowerCAmelCase     (      _lowerCAmelCase       ,    _lowerCAmelCase       ,    _lowerCAmelCase    )->     Tuple:
 if not check_uniques(lowercase_       ,    lowercase_    ):
  return False
 elif example["autogenerated"]:
  return False
 elif example["line_max"] > args.line_max:
  return False
 elif example["line_mean"] > args.line_mean:
  return False
 elif example["alpha_frac"] < args.alpha_frac:
  return False
 elif example["ratio"] < args.min_token_ratio:
  return False
 elif example["config_or_test"] and np.random.rand() <= args.filter_proba:
  return False
 elif example["has_no_keywords"] and np.random.rand() <= args.filter_proba:
  return False
 elif example["has_few_assignments"]:
  return False
 else:
  return True







def _lowerCAmelCase     (      _lowerCAmelCase    )->     Optional[int]:
 with open(lowercase_       ,    'rb'    ) as f_in:
  with gzip.open(str(lowercase_    ) + '.gz'       ,    'wb'       ,    compresslevel=6    ) as f_out:
   shutil.copyfileobj(lowercase_       ,    lowercase_    )
 os.unlink(lowercase_    )


# Settings
_A:					Any				=				HfArgumentParser(PreprocessingArguments)
_A:					Union[str, Any]				=				parser.parse_args()
if args.num_workers is None:
    _A:					Union[str, Any]				=				multiprocessing.cpu_count()
_A:					Any				=				AutoTokenizer.from_pretrained(args.tokenizer_dir)

# Load dataset
_A:					Union[str, Any]				=				time.time()
_A:					int				=				load_dataset(args.dataset_name, split="""train""")
print(F"""Time to load dataset: {time.time()-t_start:.2f}""")

# Run preprocessing
_A:					Union[str, Any]				=				time.time()
_A:					Optional[int]				=				ds.map(preprocess, num_proc=args.num_workers)
print(F"""Time to preprocess dataset: {time.time()-t_start:.2f}""")

# Deduplicate hashes
_A:					Optional[int]				=				set(ds.unique("""hash"""))
_A:					Optional[Any]				=				len(uniques) / len(ds)
print(F"""Fraction of duplicates: {1-frac:.2%}""")

# Deduplicate data and apply heuristics
_A:					Optional[int]				=				time.time()
_A:					List[str]				=				ds.filter(filter, fn_kwargs={"""uniques""": uniques, """args""": args})
print(F"""Time to filter dataset: {time.time()-t_start:.2f}""")
print(F"""Size of filtered dataset: {len(ds_filter)}""")

# Deduplicate with minhash and jaccard similarity
if args.near_deduplication:
    _A:					Any				=				time.time()
    _A:					Dict				=				deduplicate_dataset(ds_filter, args.jaccard_threshold)
    print(F"""Time to deduplicate dataset: {time.time()-t_start:.2f}""")
    print(F"""Size of deduplicate dataset: {len(ds_filter)}""")

# Save data in batches of samples_per_file
_A:					Dict				=				Path(args.output_dir)
output_dir.mkdir(exist_ok=True)

# save duplicate_clusters in the output_dir as artifacts
# not sure it is the right place the save it
if args.near_deduplication:
    with open(output_dir / """duplicate_clusters.json""", """w""") as f:
        json.dump(duplicate_clusters, f)

_A:					List[Any]				=				output_dir / 'data'
data_dir.mkdir(exist_ok=True)

_A:					Union[str, Any]				=				time.time()
for file_number, index in enumerate(range(0, len(ds_filter), args.samples_per_file)):
    _A:					Any				=				str(data_dir / F"""file-{file_number+1:012}.json""")
    _A:					Union[str, Any]				=				min(len(ds_filter), index + args.samples_per_file)
    ds_filter.select(list(range(index, end_index))).to_json(file_path)
    compress_file(file_path)

print(F"""Time to save dataset: {time.time()-t_start:.2f}""")












'''simple docstring'''




from __future__ import annotations

from collections.abc import Sequence
from typing import Literal







def _lowerCAmelCase     (      _lowerCAmelCase       ,    _lowerCAmelCase    )->     str | Literal[False]:
 __UpperCAmelCase					=   list(_lowerCAmelCase    )
 __UpperCAmelCase					=   list(_lowerCAmelCase    )
 __UpperCAmelCase					=   0
 for i in range(len(_lowerCAmelCase    )    ):
  if lista[i] != lista[i]:
   count += 1
   __UpperCAmelCase					=   '_'
 if count > 1:
  return False
 else:
  return "".join(_lowerCAmelCase    )







def _lowerCAmelCase     (      _lowerCAmelCase    )->     list[str]:
 __UpperCAmelCase					=   []
 while True:
  __UpperCAmelCase					=   ['$'] * len(_lowerCAmelCase    )
  __UpperCAmelCase					=   []
  for i in range(len(_lowerCAmelCase    )    ):
   for j in range(i + 1       ,    len(_lowerCAmelCase    )    ):
    __UpperCAmelCase					=   compare_string(binary[i]       ,    binary[j]    )
    if k is False:
     __UpperCAmelCase					=   '*'
     __UpperCAmelCase					=   '*'
     temp.append('X'    )
  for i in range(len(_lowerCAmelCase    )    ):
   if checka[i] == "$":
    pi.append(binary[i]    )
  if len(_lowerCAmelCase    ) == 0:
   return pi
  __UpperCAmelCase					=   list(set(_lowerCAmelCase    )    )







def _lowerCAmelCase     (      _lowerCAmelCase       ,    _lowerCAmelCase    )->     list[str]:
 __UpperCAmelCase					=   []
 for minterm in minterms:
  __UpperCAmelCase					=   ''
  for _ in range(_lowerCAmelCase    ):
   __UpperCAmelCase					=   str(minterm % 2    ) + string
   minterm //= 2
  temp.append(_lowerCAmelCase    )
 return temp







def _lowerCAmelCase     (      _lowerCAmelCase       ,    _lowerCAmelCase       ,    _lowerCAmelCase    )->     bool:
 __UpperCAmelCase					=   list(_lowerCAmelCase    )
 __UpperCAmelCase					=   list(_lowerCAmelCase    )
 __UpperCAmelCase					=   0
 for i in range(len(_lowerCAmelCase    )    ):
  if lista[i] != lista[i]:
   count_n += 1
 return count_n == count







def _lowerCAmelCase     (      _lowerCAmelCase       ,    _lowerCAmelCase    )->     list[str]:
 __UpperCAmelCase					=   []
 __UpperCAmelCase					=   [0] * len(_lowerCAmelCase    )
 for i in range(len(chart[0]    )    ):
  __UpperCAmelCase					=   0
  __UpperCAmelCase					=   -1
  for j in range(len(_lowerCAmelCase    )    ):
   if chart[j][i] == 1:
    count += 1
    __UpperCAmelCase					=   j
  if count == 1:
   __UpperCAmelCase					=   1
 for i in range(len(_lowerCAmelCase    )    ):
  if select[i] == 1:
   for j in range(len(chart[0]    )    ):
    if chart[i][j] == 1:
     for k in range(len(_lowerCAmelCase    )    ):
      __UpperCAmelCase					=   0
   temp.append(prime_implicants[i]    )
 while True:
  __UpperCAmelCase					=   0
  __UpperCAmelCase					=   -1
  __UpperCAmelCase					=   0
  for i in range(len(_lowerCAmelCase    )    ):
   __UpperCAmelCase					=   chart[i].count(1    )
   if count_n > max_n:
    __UpperCAmelCase					=   count_n
    __UpperCAmelCase					=   i

  if max_n == 0:
   return temp

  temp.append(prime_implicants[rem]    )

  for i in range(len(chart[0]    )    ):
   if chart[rem][i] == 1:
    for j in range(len(_lowerCAmelCase    )    ):
     __UpperCAmelCase					=   0







def _lowerCAmelCase     (      _lowerCAmelCase       ,    _lowerCAmelCase    )->     list[list[int]]:
 __UpperCAmelCase					=   [[0 for x in range(len(_lowerCAmelCase    )    )] for x in range(len(_lowerCAmelCase    )    )]
 for i in range(len(_lowerCAmelCase    )    ):
  __UpperCAmelCase					=   prime_implicants[i].count('_'    )
  for j in range(len(_lowerCAmelCase    )    ):
   if is_for_table(prime_implicants[i]       ,    binary[j]       ,    _lowerCAmelCase    ):
    __UpperCAmelCase					=   1

 return chart







def _lowerCAmelCase     (      )->     None:
 __UpperCAmelCase					=   int(input('Enter the no. of variables\n'    )    )
 __UpperCAmelCase					=   [
     float(_lowerCAmelCase    )
     for x in input(
         'Enter the decimal representation of Minterms \'Spaces Separated\'\n'    ).split()
 ]
 __UpperCAmelCase					=   decimal_to_binary(_lowerCAmelCase       ,    _lowerCAmelCase    )

 __UpperCAmelCase					=   check(_lowerCAmelCase    )
 print('Prime Implicants are:'    )
 print(_lowerCAmelCase    )
 __UpperCAmelCase					=   prime_implicant_chart(_lowerCAmelCase       ,    _lowerCAmelCase    )

 __UpperCAmelCase					=   selection(_lowerCAmelCase       ,    _lowerCAmelCase    )
 print('Essential Prime Implicants are:'    )
 print(_lowerCAmelCase    )


if __name__ == "__main__":
    import doctest

    doctest.testmod()
    main()





