


'''simple docstring'''




import contextlib
import csv
import json
import os
import sqlitea
import tarfile
import textwrap
import zipfile

import pyarrow as pa
import pyarrow.parquet as pq
import pytest

import datasets
import datasets.config





@pytest.fixture(scope='session'				)
def 	a_					( ):
   lowerCAmelCase     =			10
   lowerCAmelCase     =			datasets.Features(
       {
           'tokens': datasets.Sequence(datasets.Value('string'				)				),
           'labels': datasets.Sequence(datasets.ClassLabel(names=['negative', 'positive']				)				),
           'answers': datasets.Sequence(
               {
                   'text': datasets.Value('string'				),
                   'answer_start': datasets.Value('int32'				),
               }				),
           'id': datasets.Value('int64'				),
       }				)
   lowerCAmelCase     =			datasets.Dataset.from_dict(
       {
           'tokens': [['foo'] * 5] * n,
           'labels': [[1] * 5] * n,
           'answers': [{'answer_start': [97], 'text': ['1976']}] * 10,
           'id': list(range(lowerCamelCase				)				),
       }	, features=lowerCamelCase	, )
   return dataset





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     int	, lowerCamelCase	:     Tuple				):
   lowerCAmelCase     =			str(tmp_path_factory.mktemp('data'				) / 'file.arrow'				)
   dataset.map(cache_file_name=lowerCamelCase				)
   return filename


# FILE_CONTENT + files


__snake_case    						="""\
    Text data.
    Second line of data."""





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     List[str]				):
   lowerCAmelCase     =			tmp_path_factory.mktemp('data'				) / 'file.txt'
   lowerCAmelCase     =			FILE_CONTENT
   with open(lowerCamelCase	, 'w'				) as f:
      f.write(lowerCamelCase				)
   return filename





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     Union[str, Any]				):
   import bza

   lowerCAmelCase     =			tmp_path_factory.mktemp('data'				) / 'file.txt.bz2'
   lowerCAmelCase     =			bytes(lowerCamelCase	, 'utf-8'				)
   with bza.open(lowerCamelCase	, 'wb'				) as f:
      f.write(lowerCamelCase				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     Union[str, Any]				):
   import gzip

   lowerCAmelCase     =			str(tmp_path_factory.mktemp('data'				) / 'file.txt.gz'				)
   lowerCAmelCase     =			bytes(lowerCamelCase	, 'utf-8'				)
   with gzip.open(lowerCamelCase	, 'wb'				) as f:
      f.write(lowerCamelCase				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     Any				):
   if datasets.config.LZ4_AVAILABLE:
      import lza.frame

      lowerCAmelCase     =			tmp_path_factory.mktemp('data'				) / 'file.txt.lz4'
      lowerCAmelCase     =			bytes(lowerCamelCase	, 'utf-8'				)
      with lza.frame.open(lowerCamelCase	, 'wb'				) as f:
         f.write(lowerCamelCase				)
      return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     Dict	, lowerCamelCase	:     List[Any]				):
   if datasets.config.PY7ZR_AVAILABLE:
      import pyazr

      lowerCAmelCase     =			tmp_path_factory.mktemp('data'				) / 'file.txt.7z'
      with pyazr.SevenZipFile(lowerCamelCase	, 'w'				) as archive:
         archive.write(lowerCamelCase	, arcname=os.path.basename(lowerCamelCase				)				)
      return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     Dict	, lowerCamelCase	:     List[str]				):
   import tarfile

   lowerCAmelCase     =			tmp_path_factory.mktemp('data'				) / 'file.txt.tar'
   with tarfile.TarFile(lowerCamelCase	, 'w'				) as f:
      f.add(lowerCamelCase	, arcname=os.path.basename(lowerCamelCase				)				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     Any				):
   import lzma

   lowerCAmelCase     =			tmp_path_factory.mktemp('data'				) / 'file.txt.xz'
   lowerCAmelCase     =			bytes(lowerCamelCase	, 'utf-8'				)
   with lzma.open(lowerCamelCase	, 'wb'				) as f:
      f.write(lowerCamelCase				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     Tuple	, lowerCamelCase	:     int				):
   import zipfile

   lowerCAmelCase     =			tmp_path_factory.mktemp('data'				) / 'file.txt.zip'
   with zipfile.ZipFile(lowerCamelCase	, 'w'				) as f:
      f.write(lowerCamelCase	, arcname=os.path.basename(lowerCamelCase				)				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     List[Any]				):
   if datasets.config.ZSTANDARD_AVAILABLE:
      import zstandard as zstd

      lowerCAmelCase     =			tmp_path_factory.mktemp('data'				) / 'file.txt.zst'
      lowerCAmelCase     =			bytes(lowerCamelCase	, 'utf-8'				)
      with zstd.open(lowerCamelCase	, 'wb'				) as f:
         f.write(lowerCamelCase				)
      return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     Optional[Any]				):
   lowerCAmelCase     =			tmp_path_factory.mktemp('data'				) / 'file.xml'
   lowerCAmelCase     =			textwrap.dedent(
       '\\n    <?xml version="1.0" encoding="UTF-8" ?>\n    <tmx version="1.4">\n      <header segtype="sentence" srclang="ca" />\n      <body>\n        <tu>\n          <tuv xml:lang="ca"><seg>Contingut 1</seg></tuv>\n          <tuv xml:lang="en"><seg>Content 1</seg></tuv>\n        </tu>\n        <tu>\n          <tuv xml:lang="ca"><seg>Contingut 2</seg></tuv>\n          <tuv xml:lang="en"><seg>Content 2</seg></tuv>\n        </tu>\n        <tu>\n          <tuv xml:lang="ca"><seg>Contingut 3</seg></tuv>\n          <tuv xml:lang="en"><seg>Content 3</seg></tuv>\n        </tu>\n        <tu>\n          <tuv xml:lang="ca"><seg>Contingut 4</seg></tuv>\n          <tuv xml:lang="en"><seg>Content 4</seg></tuv>\n        </tu>\n        <tu>\n          <tuv xml:lang="ca"><seg>Contingut 5</seg></tuv>\n          <tuv xml:lang="en"><seg>Content 5</seg></tuv>\n        </tu>\n      </body>\n    </tmx>'				)
   with open(lowerCamelCase	, 'w'				) as f:
      f.write(lowerCamelCase				)
   return filename


__snake_case    						=[
    {"""col_1""": """0""", """col_2""": 0, """col_3""": 0.0},
    {"""col_1""": """1""", """col_2""": 1, """col_3""": 1.0},
    {"""col_1""": """2""", """col_2""": 2, """col_3""": 2.0},
    {"""col_1""": """3""", """col_2""": 3, """col_3""": 3.0},
]
__snake_case    						=[
    {"""col_1""": """4""", """col_2""": 4, """col_3""": 4.0},
    {"""col_1""": """5""", """col_2""": 5, """col_3""": 5.0},
]
__snake_case    						={
    """col_1""": ["""0""", """1""", """2""", """3"""],
    """col_2""": [0, 1, 2, 3],
    """col_3""": [0.0, 1.0, 2.0, 3.0],
}

__snake_case    						=[
    {"""col_3""": 0.0, """col_1""": """0""", """col_2""": 0},
    {"""col_3""": 1.0, """col_1""": """1""", """col_2""": 1},
]

__snake_case    						=[
    {"""col_1""": """s0""", """col_2""": 0, """col_3""": 0.0},
    {"""col_1""": """s1""", """col_2""": 1, """col_3""": 1.0},
    {"""col_1""": """s2""", """col_2""": 2, """col_3""": 2.0},
    {"""col_1""": """s3""", """col_2""": 3, """col_3""": 3.0},
]





@pytest.fixture(scope='session'				)
def 	a_					( ):
   return DATA_DICT_OF_LISTS





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     List[Any]				):
   lowerCAmelCase     =			datasets.Dataset.from_dict(lowerCamelCase				)
   lowerCAmelCase     =			str(tmp_path_factory.mktemp('data'				) / 'dataset.arrow'				)
   dataset.map(cache_file_name=lowerCamelCase				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     Optional[int]				):
   lowerCAmelCase     =			str(tmp_path_factory.mktemp('data'				) / 'dataset.sqlite'				)
   with contextlib.closing(sqlitea.connect(lowerCamelCase				)				) as con:
      lowerCAmelCase     =			con.cursor()
      cur.execute('CREATE TABLE dataset(col_1 text, col_2 int, col_3 real)'				)
      for item in DATA:
         cur.execute('INSERT INTO dataset(col_1, col_2, col_3) VALUES (?, ?, ?)'	, tuple(item.values()				)				)
      con.commit()
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     Any				):
   lowerCAmelCase     =			str(tmp_path_factory.mktemp('data'				) / 'dataset.csv'				)
   with open(lowerCamelCase	, 'w'	, newline=''				) as f:
      lowerCAmelCase     =			csv.DictWriter(lowerCamelCase	, fieldnames=['col_1', 'col_2', 'col_3']				)
      writer.writeheader()
      for item in DATA:
         writer.writerow(lowerCamelCase				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     Optional[Any]				):
   lowerCAmelCase     =			str(tmp_path_factory.mktemp('data'				) / 'dataset2.csv'				)
   with open(lowerCamelCase	, 'w'	, newline=''				) as f:
      lowerCAmelCase     =			csv.DictWriter(lowerCamelCase	, fieldnames=['col_1', 'col_2', 'col_3']				)
      writer.writeheader()
      for item in DATA:
         writer.writerow(lowerCamelCase				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     List[Any]	, lowerCamelCase	:     List[Any]				):
   import bza

   lowerCAmelCase     =			tmp_path_factory.mktemp('data'				) / 'dataset.csv.bz2'
   with open(lowerCamelCase	, 'rb'				) as f:
      lowerCAmelCase     =			f.read()
   # data = bytes(FILE_CONTENT, "utf-8")
   with bza.open(lowerCamelCase	, 'wb'				) as f:
      f.write(lowerCamelCase				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     str	, lowerCamelCase	:     Dict	, lowerCamelCase	:     Optional[int]				):
   lowerCAmelCase     =			tmp_path_factory.mktemp('data'				) / 'dataset.csv.zip'
   with zipfile.ZipFile(lowerCamelCase	, 'w'				) as f:
      f.write(lowerCamelCase	, arcname=os.path.basename(lowerCamelCase				)				)
      f.write(lowerCamelCase	, arcname=os.path.basename(lowerCamelCase				)				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     List[Any]	, lowerCamelCase	:     Optional[Any]	, lowerCamelCase	:     Any				):
   lowerCAmelCase     =			tmp_path_factory.mktemp('data'				) / 'dataset.csv.zip'
   with zipfile.ZipFile(lowerCamelCase	, 'w'				) as f:
      f.write(lowerCamelCase	, arcname=os.path.basename(csv_path.replace('.csv'	, '.CSV'				)				)				)
      f.write(lowerCamelCase	, arcname=os.path.basename(csva_path.replace('.csv'	, '.CSV'				)				)				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     int	, lowerCamelCase	:     int	, lowerCamelCase	:     Union[str, Any]				):
   lowerCAmelCase     =			tmp_path_factory.mktemp('data'				) / 'dataset_with_dir.csv.zip'
   with zipfile.ZipFile(lowerCamelCase	, 'w'				) as f:
      f.write(lowerCamelCase	, arcname=os.path.join('main_dir'	, os.path.basename(lowerCamelCase				)				)				)
      f.write(lowerCamelCase	, arcname=os.path.join('main_dir'	, os.path.basename(lowerCamelCase				)				)				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     Dict				):
   lowerCAmelCase     =			str(tmp_path_factory.mktemp('data'				) / 'dataset.parquet'				)
   lowerCAmelCase     =			pa.schema(
       {
           'col_1': pa.string(),
           'col_2': pa.intaa(),
           'col_3': pa.floataa(),
       }				)
   with open(lowerCamelCase	, 'wb'				) as f:
      lowerCAmelCase     =			pq.ParquetWriter(lowerCamelCase	, schema=lowerCamelCase				)
      lowerCAmelCase     =			pa.Table.from_pydict({k: [DATA[i][k] for i in range(len(lowerCamelCase				)				)] for k in DATA[0]}	, schema=lowerCamelCase				)
      writer.write_table(lowerCamelCase				)
      writer.close()
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     Union[str, Any]				):
   lowerCAmelCase     =			str(tmp_path_factory.mktemp('data'				) / 'dataset.json'				)
   lowerCAmelCase     =			{'data': DATA}
   with open(lowerCamelCase	, 'w'				) as f:
      json.dump(lowerCamelCase	, lowerCamelCase				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     Optional[int]				):
   lowerCAmelCase     =			str(tmp_path_factory.mktemp('data'				) / 'dataset.json'				)
   lowerCAmelCase     =			{'data': DATA_DICT_OF_LISTS}
   with open(lowerCamelCase	, 'w'				) as f:
      json.dump(lowerCamelCase	, lowerCamelCase				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     str				):
   lowerCAmelCase     =			str(tmp_path_factory.mktemp('data'				) / 'dataset.jsonl'				)
   with open(lowerCamelCase	, 'w'				) as f:
      for item in DATA:
         f.write(json.dumps(lowerCamelCase				) + '\n'				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     List[Any]				):
   lowerCAmelCase     =			str(tmp_path_factory.mktemp('data'				) / 'dataset2.jsonl'				)
   with open(lowerCamelCase	, 'w'				) as f:
      for item in DATA:
         f.write(json.dumps(lowerCamelCase				) + '\n'				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     Dict				):
   lowerCAmelCase     =			str(tmp_path_factory.mktemp('data'				) / 'dataset_312.jsonl'				)
   with open(lowerCamelCase	, 'w'				) as f:
      for item in DATA_312:
         f.write(json.dumps(lowerCamelCase				) + '\n'				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     List[str]				):
   lowerCAmelCase     =			str(tmp_path_factory.mktemp('data'				) / 'dataset-str.jsonl'				)
   with open(lowerCamelCase	, 'w'				) as f:
      for item in DATA_STR:
         f.write(json.dumps(lowerCamelCase				) + '\n'				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     Tuple	, lowerCamelCase	:     Tuple				):
   import gzip

   lowerCAmelCase     =			str(tmp_path_factory.mktemp('data'				) / 'dataset.txt.gz'				)
   with open(lowerCamelCase	, 'rb'				) as orig_file:
      with gzip.open(lowerCamelCase	, 'wb'				) as zipped_file:
         zipped_file.writelines(lowerCamelCase				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     Dict	, lowerCamelCase	:     int				):
   import gzip

   lowerCAmelCase     =			str(tmp_path_factory.mktemp('data'				) / 'dataset.jsonl.gz'				)
   with open(lowerCamelCase	, 'rb'				) as orig_file:
      with gzip.open(lowerCamelCase	, 'wb'				) as zipped_file:
         zipped_file.writelines(lowerCamelCase				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     List[str]	, lowerCamelCase	:     str	, lowerCamelCase	:     int				):
   lowerCAmelCase     =			tmp_path_factory.mktemp('data'				) / 'dataset.jsonl.zip'
   with zipfile.ZipFile(lowerCamelCase	, 'w'				) as f:
      f.write(lowerCamelCase	, arcname=os.path.basename(lowerCamelCase				)				)
      f.write(lowerCamelCase	, arcname=os.path.basename(lowerCamelCase				)				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     Optional[Any]	, lowerCamelCase	:     Union[str, Any]	, lowerCamelCase	:     Optional[Any]	, lowerCamelCase	:     Any				):
   lowerCAmelCase     =			tmp_path_factory.mktemp('data'				) / 'dataset_nested.jsonl.zip'
   with zipfile.ZipFile(lowerCamelCase	, 'w'				) as f:
      f.write(lowerCamelCase	, arcname=os.path.join('nested'	, os.path.basename(lowerCamelCase				)				)				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     List[str]	, lowerCamelCase	:     Any	, lowerCamelCase	:     Union[str, Any]				):
   lowerCAmelCase     =			tmp_path_factory.mktemp('data'				) / 'dataset_with_dir.jsonl.zip'
   with zipfile.ZipFile(lowerCamelCase	, 'w'				) as f:
      f.write(lowerCamelCase	, arcname=os.path.join('main_dir'	, os.path.basename(lowerCamelCase				)				)				)
      f.write(lowerCamelCase	, arcname=os.path.join('main_dir'	, os.path.basename(lowerCamelCase				)				)				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     int	, lowerCamelCase	:     str	, lowerCamelCase	:     Optional[Any]				):
   lowerCAmelCase     =			tmp_path_factory.mktemp('data'				) / 'dataset.jsonl.tar'
   with tarfile.TarFile(lowerCamelCase	, 'w'				) as f:
      f.add(lowerCamelCase	, arcname=os.path.basename(lowerCamelCase				)				)
      f.add(lowerCamelCase	, arcname=os.path.basename(lowerCamelCase				)				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     int	, lowerCamelCase	:     List[Any]	, lowerCamelCase	:     Any	, lowerCamelCase	:     str				):
   lowerCAmelCase     =			tmp_path_factory.mktemp('data'				) / 'dataset_nested.jsonl.tar'
   with tarfile.TarFile(lowerCamelCase	, 'w'				) as f:
      f.add(lowerCamelCase	, arcname=os.path.join('nested'	, os.path.basename(lowerCamelCase				)				)				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     int				):
   lowerCAmelCase     =			['0', '1', '2', '3']
   lowerCAmelCase     =			str(tmp_path_factory.mktemp('data'				) / 'dataset.txt'				)
   with open(lowerCamelCase	, 'w'				) as f:
      for item in data:
         f.write(item + '\n'				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     List[str]				):
   lowerCAmelCase     =			['0', '1', '2', '3']
   lowerCAmelCase     =			str(tmp_path_factory.mktemp('data'				) / 'dataset2.txt'				)
   with open(lowerCamelCase	, 'w'				) as f:
      for item in data:
         f.write(item + '\n'				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     int				):
   lowerCAmelCase     =			['0', '1', '2', '3']
   lowerCAmelCase     =			tmp_path_factory.mktemp('data'				) / 'dataset.abc'
   with open(lowerCamelCase	, 'w'				) as f:
      for item in data:
         f.write(item + '\n'				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     int	, lowerCamelCase	:     Optional[int]	, lowerCamelCase	:     Tuple				):
   lowerCAmelCase     =			tmp_path_factory.mktemp('data'				) / 'dataset.text.zip'
   with zipfile.ZipFile(lowerCamelCase	, 'w'				) as f:
      f.write(lowerCamelCase	, arcname=os.path.basename(lowerCamelCase				)				)
      f.write(lowerCamelCase	, arcname=os.path.basename(lowerCamelCase				)				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     int	, lowerCamelCase	:     Any	, lowerCamelCase	:     int				):
   lowerCAmelCase     =			tmp_path_factory.mktemp('data'				) / 'dataset_with_dir.text.zip'
   with zipfile.ZipFile(lowerCamelCase	, 'w'				) as f:
      f.write(lowerCamelCase	, arcname=os.path.join('main_dir'	, os.path.basename(lowerCamelCase				)				)				)
      f.write(lowerCamelCase	, arcname=os.path.join('main_dir'	, os.path.basename(lowerCamelCase				)				)				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     Tuple	, lowerCamelCase	:     Optional[int]	, lowerCamelCase	:     Tuple				):
   lowerCAmelCase     =			tmp_path_factory.mktemp('data'				) / 'dataset.ext.zip'
   with zipfile.ZipFile(lowerCamelCase	, 'w'				) as f:
      f.write(lowerCamelCase	, arcname=os.path.basename('unsupported.ext'				)				)
      f.write(lowerCamelCase	, arcname=os.path.basename('unsupported_2.ext'				)				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     Dict				):
   lowerCAmelCase     =			'\n'.join(['First', 'Second\u2029with Unicode new line', 'Third']				)
   lowerCAmelCase     =			str(tmp_path_factory.mktemp('data'				) / 'dataset_with_unicode_new_lines.txt'				)
   with open(lowerCamelCase	, 'w'	, encoding='utf-8'				) as f:
      f.write(lowerCamelCase				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( ):
   return os.path.join('tests'	, 'features'	, 'data'	, 'test_image_rgb.jpg'				)





@pytest.fixture(scope='session'				)
def 	a_					( ):
   return os.path.join('tests'	, 'features'	, 'data'	, 'test_audio_44100.wav'				)





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     Optional[int]	, lowerCamelCase	:     Union[str, Any]				):
   lowerCAmelCase     =			tmp_path_factory.mktemp('data'				) / 'dataset.img.zip'
   with zipfile.ZipFile(lowerCamelCase	, 'w'				) as f:
      f.write(lowerCamelCase	, arcname=os.path.basename(lowerCamelCase				)				)
      f.write(lowerCamelCase	, arcname=os.path.basename(lowerCamelCase				).replace('.jpg'	, '2.jpg'				)				)
   return path





@pytest.fixture(scope='session'				)
def 	a_					( lowerCamelCase	:     Union[str, Any]				):
   lowerCAmelCase     =			tmp_path_factory.mktemp('data_dir'				)

   (data_dir / "subdir").mkdir()
   with open(data_dir / 'subdir' / 'train.txt'	, 'w'				) as f:
      f.write('foo\n' * 10				)
   with open(data_dir / 'subdir' / 'test.txt'	, 'w'				) as f:
      f.write('bar\n' * 10				)
   # hidden file
   with open(data_dir / 'subdir' / '.test.txt'	, 'w'				) as f:
      f.write('bar\n' * 10				)

   # hidden directory
   (data_dir / ".subdir").mkdir()
   with open(data_dir / '.subdir' / 'train.txt'	, 'w'				) as f:
      f.write('foo\n' * 10				)
   with open(data_dir / '.subdir' / 'test.txt'	, 'w'				) as f:
      f.write('bar\n' * 10				)

   return data_dir









'''simple docstring'''




import argparse

import torch

from transformers import (
    EncodecConfig,
    EncodecFeatureExtractor,
    EncodecModel,
    logging,
)


# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/facebook/musicgen-small/resolve/main/compression_state_dict.bin
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_48khz-7e698e3e.th


logging.set_verbosity_info()
__snake_case    						=logging.get_logger("""transformers.models.encodec""")

__snake_case    						={
    """quantizer.vq.layers.*._codebook.inited""": """quantizer.layers.*.codebook.inited""",
    """quantizer.vq.layers.*._codebook.cluster_size""": """quantizer.layers.*.codebook.cluster_size""",
    """quantizer.vq.layers.*._codebook.embed""": """quantizer.layers.*.codebook.embed""",
    """quantizer.vq.layers.*._codebook.embed_avg""": """quantizer.layers.*.codebook.embed_avg""",
}
__snake_case    						={
    """encoder.model.0.conv.conv""": """encoder.layers.0.conv""",
    """encoder.model.1.block.1.conv.conv""": """encoder.layers.1.block.1.conv""",
    """encoder.model.1.block.3.conv.conv""": """encoder.layers.1.block.3.conv""",
    """encoder.model.1.shortcut.conv.conv""": """encoder.layers.1.shortcut.conv""",
    """encoder.model.3.conv.conv""": """encoder.layers.3.conv""",
    """encoder.model.4.block.1.conv.conv""": """encoder.layers.4.block.1.conv""",
    """encoder.model.4.block.3.conv.conv""": """encoder.layers.4.block.3.conv""",
    """encoder.model.4.shortcut.conv.conv""": """encoder.layers.4.shortcut.conv""",
    """encoder.model.6.conv.conv""": """encoder.layers.6.conv""",
    """encoder.model.7.block.1.conv.conv""": """encoder.layers.7.block.1.conv""",
    """encoder.model.7.block.3.conv.conv""": """encoder.layers.7.block.3.conv""",
    """encoder.model.7.shortcut.conv.conv""": """encoder.layers.7.shortcut.conv""",
    """encoder.model.9.conv.conv""": """encoder.layers.9.conv""",
    """encoder.model.10.block.1.conv.conv""": """encoder.layers.10.block.1.conv""",
    """encoder.model.10.block.3.conv.conv""": """encoder.layers.10.block.3.conv""",
    """encoder.model.10.shortcut.conv.conv""": """encoder.layers.10.shortcut.conv""",
    """encoder.model.12.conv.conv""": """encoder.layers.12.conv""",
    """encoder.model.13.lstm""": """encoder.layers.13.lstm""",
    """encoder.model.15.conv.conv""": """encoder.layers.15.conv""",
}
__snake_case    						={
    """encoder.model.0.conv.norm""": """encoder.layers.0.norm""",
    """encoder.model.1.block.1.conv.norm""": """encoder.layers.1.block.1.norm""",
    """encoder.model.1.block.3.conv.norm""": """encoder.layers.1.block.3.norm""",
    """encoder.model.1.shortcut.conv.norm""": """encoder.layers.1.shortcut.norm""",
    """encoder.model.3.conv.norm""": """encoder.layers.3.norm""",
    """encoder.model.4.block.1.conv.norm""": """encoder.layers.4.block.1.norm""",
    """encoder.model.4.block.3.conv.norm""": """encoder.layers.4.block.3.norm""",
    """encoder.model.4.shortcut.conv.norm""": """encoder.layers.4.shortcut.norm""",
    """encoder.model.6.conv.norm""": """encoder.layers.6.norm""",
    """encoder.model.7.block.1.conv.norm""": """encoder.layers.7.block.1.norm""",
    """encoder.model.7.block.3.conv.norm""": """encoder.layers.7.block.3.norm""",
    """encoder.model.7.shortcut.conv.norm""": """encoder.layers.7.shortcut.norm""",
    """encoder.model.9.conv.norm""": """encoder.layers.9.norm""",
    """encoder.model.10.block.1.conv.norm""": """encoder.layers.10.block.1.norm""",
    """encoder.model.10.block.3.conv.norm""": """encoder.layers.10.block.3.norm""",
    """encoder.model.10.shortcut.conv.norm""": """encoder.layers.10.shortcut.norm""",
    """encoder.model.12.conv.norm""": """encoder.layers.12.norm""",
    """encoder.model.15.conv.norm""": """encoder.layers.15.norm""",
}
__snake_case    						={
    """decoder.model.0.conv.conv""": """decoder.layers.0.conv""",
    """decoder.model.1.lstm""": """decoder.layers.1.lstm""",
    """decoder.model.3.convtr.convtr""": """decoder.layers.3.conv""",
    """decoder.model.4.block.1.conv.conv""": """decoder.layers.4.block.1.conv""",
    """decoder.model.4.block.3.conv.conv""": """decoder.layers.4.block.3.conv""",
    """decoder.model.4.shortcut.conv.conv""": """decoder.layers.4.shortcut.conv""",
    """decoder.model.6.convtr.convtr""": """decoder.layers.6.conv""",
    """decoder.model.7.block.1.conv.conv""": """decoder.layers.7.block.1.conv""",
    """decoder.model.7.block.3.conv.conv""": """decoder.layers.7.block.3.conv""",
    """decoder.model.7.shortcut.conv.conv""": """decoder.layers.7.shortcut.conv""",
    """decoder.model.9.convtr.convtr""": """decoder.layers.9.conv""",
    """decoder.model.10.block.1.conv.conv""": """decoder.layers.10.block.1.conv""",
    """decoder.model.10.block.3.conv.conv""": """decoder.layers.10.block.3.conv""",
    """decoder.model.10.shortcut.conv.conv""": """decoder.layers.10.shortcut.conv""",
    """decoder.model.12.convtr.convtr""": """decoder.layers.12.conv""",
    """decoder.model.13.block.1.conv.conv""": """decoder.layers.13.block.1.conv""",
    """decoder.model.13.block.3.conv.conv""": """decoder.layers.13.block.3.conv""",
    """decoder.model.13.shortcut.conv.conv""": """decoder.layers.13.shortcut.conv""",
    """decoder.model.15.conv.conv""": """decoder.layers.15.conv""",
}
__snake_case    						={
    """decoder.model.0.conv.norm""": """decoder.layers.0.norm""",
    """decoder.model.3.convtr.norm""": """decoder.layers.3.norm""",
    """decoder.model.4.block.1.conv.norm""": """decoder.layers.4.block.1.norm""",
    """decoder.model.4.block.3.conv.norm""": """decoder.layers.4.block.3.norm""",
    """decoder.model.4.shortcut.conv.norm""": """decoder.layers.4.shortcut.norm""",
    """decoder.model.6.convtr.norm""": """decoder.layers.6.norm""",
    """decoder.model.7.block.1.conv.norm""": """decoder.layers.7.block.1.norm""",
    """decoder.model.7.block.3.conv.norm""": """decoder.layers.7.block.3.norm""",
    """decoder.model.7.shortcut.conv.norm""": """decoder.layers.7.shortcut.norm""",
    """decoder.model.9.convtr.norm""": """decoder.layers.9.norm""",
    """decoder.model.10.block.1.conv.norm""": """decoder.layers.10.block.1.norm""",
    """decoder.model.10.block.3.conv.norm""": """decoder.layers.10.block.3.norm""",
    """decoder.model.10.shortcut.conv.norm""": """decoder.layers.10.shortcut.norm""",
    """decoder.model.12.convtr.norm""": """decoder.layers.12.norm""",
    """decoder.model.13.block.1.conv.norm""": """decoder.layers.13.block.1.norm""",
    """decoder.model.13.block.3.conv.norm""": """decoder.layers.13.block.3.norm""",
    """decoder.model.13.shortcut.conv.norm""": """decoder.layers.13.shortcut.norm""",
    """decoder.model.15.conv.norm""": """decoder.layers.15.norm""",
}
__snake_case    						={
    **MAPPING_QUANTIZER,
    **MAPPING_ENCODER,
    **MAPPING_DECODER,
}
__snake_case    						={
    **MAPPING_QUANTIZER,
    **MAPPING_ENCODER,
    **MAPPING_ENCODER_48K,
    **MAPPING_DECODER,
    **MAPPING_DECODER_48K,
}
__snake_case    						=[]
__snake_case    						=[]





def 	a_					( lowerCamelCase	:     Optional[Any]	, lowerCamelCase	:     Union[str, Any]	, lowerCamelCase	:     int	, lowerCamelCase	:     Any	, lowerCamelCase	:     List[str]				):
   for attribute in key.split('.'				):
      lowerCAmelCase     =			getattr(lowerCamelCase	, lowerCamelCase				)

   if weight_type is not None:
      lowerCAmelCase     =			getattr(lowerCamelCase	, lowerCamelCase				).shape
   else:
      lowerCAmelCase     =			hf_pointer.shape

   if hf_shape != value.shape:
      raise ValueError(
          f'''Shape of hf {key + '.' + weight_type if weight_type is not None else ''} is {hf_shape}, but should be'''
          f''' {value.shape} for {full_name}'''				)

   if weight_type == "weight":
      lowerCAmelCase     =			value
   elif weight_type == "weight_g":
      lowerCAmelCase     =			value
   elif weight_type == "weight_v":
      lowerCAmelCase     =			value
   elif weight_type == "bias":
      lowerCAmelCase     =			value
   elif weight_type == "running_mean":
      lowerCAmelCase     =			value
   elif weight_type == "running_var":
      lowerCAmelCase     =			value
   elif weight_type == "num_batches_tracked":
      lowerCAmelCase     =			value
   elif weight_type == "weight_ih_l0":
      lowerCAmelCase     =			value
   elif weight_type == "weight_hh_l0":
      lowerCAmelCase     =			value
   elif weight_type == "bias_ih_l0":
      lowerCAmelCase     =			value
   elif weight_type == "bias_hh_l0":
      lowerCAmelCase     =			value
   elif weight_type == "weight_ih_l1":
      lowerCAmelCase     =			value
   elif weight_type == "weight_hh_l1":
      lowerCAmelCase     =			value
   elif weight_type == "bias_ih_l1":
      lowerCAmelCase     =			value
   elif weight_type == "bias_hh_l1":
      lowerCAmelCase     =			value
   else:
      lowerCAmelCase     =			value

   logger.info(f'''{key + ('.' + weight_type if weight_type is not None else '')} was initialized from {full_name}.'''				)





def 	a_					( lowerCamelCase	:     Optional[Any]	, lowerCamelCase	:     Optional[Any]				):
   for key in ignore_keys:
      if key.endswith('.*'				):
         if name.startswith(key[:-1]				):
            return True
      elif ".*." in key:
         lowerCAmelCase     ,  lowerCAmelCase     =			key.split('.*.'				)
         if prefix in name and suffix in name:
            return True
      elif key in name:
         return True
   return False





def 	a_					( lowerCamelCase	:     List[Any]	, lowerCamelCase	:     Any	, lowerCamelCase	:     str				):
   lowerCAmelCase     =			[]

   if model_name == "encodec_24khz" or "encodec_32khz":
      lowerCAmelCase     =			MAPPING_24K
   elif model_name == "encodec_48khz":
      lowerCAmelCase     =			MAPPING_48K
   else:
      raise ValueError(f'''Unsupported model: {model_name}'''				)

   for name, value in orig_dict.items():
      if should_ignore(lowerCamelCase	, lowerCamelCase				):
         logger.info(f'''{name} was ignored'''				)
         continue

      lowerCAmelCase     =			False
      for key, mapped_key in MAPPING.items():
         if "*" in key:
            lowerCAmelCase     ,  lowerCAmelCase     =			key.split('.*.'				)
            if prefix in name and suffix in name:
               lowerCAmelCase     =			suffix

         if key in name:
            # HACK otherwise .embed gets initialized with .embed_avg too
            if key.endswith('embed'				) and name.endswith('embed_avg'				):
               continue

            lowerCAmelCase     =			True
            if "*" in mapped_key:
               lowerCAmelCase     =			name.split(lowerCamelCase				)[0].split('.'				)[-2]
               lowerCAmelCase     =			mapped_key.replace('*'	, lowerCamelCase				)
            if "weight_g" in name:
               lowerCAmelCase     =			'weight_g'
            elif "weight_v" in name:
               lowerCAmelCase     =			'weight_v'
            elif "weight_ih_l0" in name:
               lowerCAmelCase     =			'weight_ih_l0'
            elif "weight_hh_l0" in name:
               lowerCAmelCase     =			'weight_hh_l0'
            elif "bias_ih_l0" in name:
               lowerCAmelCase     =			'bias_ih_l0'
            elif "bias_hh_l0" in name:
               lowerCAmelCase     =			'bias_hh_l0'
            elif "weight_ih_l1" in name:
               lowerCAmelCase     =			'weight_ih_l1'
            elif "weight_hh_l1" in name:
               lowerCAmelCase     =			'weight_hh_l1'
            elif "bias_ih_l1" in name:
               lowerCAmelCase     =			'bias_ih_l1'
            elif "bias_hh_l1" in name:
               lowerCAmelCase     =			'bias_hh_l1'
            elif "bias" in name:
               lowerCAmelCase     =			'bias'
            elif "weight" in name:
               lowerCAmelCase     =			'weight'
            elif "running_mean" in name:
               lowerCAmelCase     =			'running_mean'
            elif "running_var" in name:
               lowerCAmelCase     =			'running_var'
            elif "num_batches_tracked" in name:
               lowerCAmelCase     =			'num_batches_tracked'
            else:
               lowerCAmelCase     =			None
            set_recursively(lowerCamelCase	, lowerCamelCase	, lowerCamelCase	, lowerCamelCase	, lowerCamelCase				)
         continue
      if not is_used:
         unused_weights.append(lowerCamelCase				)

   logger.warning(f'''Unused weights: {unused_weights}'''				)





@torch.no_grad()
def 	a_					( lowerCamelCase	:     Optional[int]	, lowerCamelCase	:     Union[str, Any]	, lowerCamelCase	:     str	, lowerCamelCase	:     Dict=None	, lowerCamelCase	:     Union[str, Any]=None	, ):
   if config_path is not None:
      lowerCAmelCase     =			EncodecConfig.from_pretrained(lowerCamelCase				)
   else:
      lowerCAmelCase     =			EncodecConfig()

   if model_name == "encodec_24khz":
      pass  # config is already correct
   elif model_name == "encodec_32khz":
      lowerCAmelCase     =			[8, 5, 4, 4]
      lowerCAmelCase     =			[2.2]
      lowerCAmelCase     =			64
      lowerCAmelCase     =			32000
      lowerCAmelCase     =			2048
      lowerCAmelCase     =			False
      lowerCAmelCase     =			False
      lowerCAmelCase     =			False
   elif model_name == "encodec_48khz":
      lowerCAmelCase     =			[8, 5, 4, 2]
      lowerCAmelCase     =			[3.0, 6.0, 12.0, 24.0]
      lowerCAmelCase     =			48000
      lowerCAmelCase     =			2
      lowerCAmelCase     =			False
      lowerCAmelCase     =			'time_group_norm'
      lowerCAmelCase     =			True
      lowerCAmelCase     =			1.0
      lowerCAmelCase     =			0.01
   else:
      raise ValueError(f'''Unknown model name: {model_name}'''				)

   lowerCAmelCase     =			EncodecModel(lowerCamelCase				)

   lowerCAmelCase     =			EncodecFeatureExtractor(
       feature_size=config.audio_channels	, sampling_rate=config.sampling_rate	, chunk_length_s=config.chunk_length_s	, overlap=config.overlap	, )
   feature_extractor.save_pretrained(lowerCamelCase				)

   lowerCAmelCase     =			torch.load(lowerCamelCase				)
   if "best_state" in original_checkpoint:
      # we might have a training state saved, in which case discard the yaml results and just retain the weights
      lowerCAmelCase     =			original_checkpoint['best_state']
   recursively_load_weights(lowerCamelCase	, lowerCamelCase	, lowerCamelCase				)
   model.save_pretrained(lowerCamelCase				)

   if repo_id:
      print('Pushing to the hub...'				)
      feature_extractor.push_to_hub(lowerCamelCase				)
      model.push_to_hub(lowerCamelCase				)


if __name__ == "__main__":
       __snake_case    						=argparse.ArgumentParser()
       parser.add_argument(
           """--model""",
           default="""encodec_24khz""",
           type=str,
           help="""The model to convert. Should be one of 'encodec_24khz', 'encodec_32khz', 'encodec_48khz'.""",
       )
       parser.add_argument("""--checkpoint_path""", required=True, default=None, type=str, help="""Path to original checkpoint""")
       parser.add_argument("""--config_path""", default=None, type=str, help="""Path to hf config.json of model to convert""")
       parser.add_argument(
           """--pytorch_dump_folder_path""", required=True, default=None, type=str, help="""Path to the output PyTorch model."""
       )
       parser.add_argument(
           """--push_to_hub""", default=None, type=str, help="""Where to upload the converted model on the 🤗 hub."""
       )

       __snake_case    						=parser.parse_args()
       convert_checkpoint(
           args.model,
           args.checkpoint_path,
           args.pytorch_dump_folder_path,
           args.config_path,
           args.push_to_hub,
       )





