






"""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 					lowerCAmelCase				(    ):




  """simple docstring"""







  __A									= 1_0
  __A									= 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''' ),
      } )
  __A									= datasets.Dataset.from_dict(
      {
          '''tokens''': [['''foo'''] * 5] * n,
          '''labels''': [[1] * 5] * n,
          '''answers''': [{'''answer_start''': [9_7], '''text''': ['''1976''']}] * 1_0,
          '''id''': list(range(__UpperCamelCase ) ),
      }		,       features=__UpperCamelCase		,       )
  return dataset



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase		,       __UpperCamelCase ):




  """simple docstring"""







  __A									= str(tmp_path_factory.mktemp('''data''' ) / '''file.arrow''' )
  dataset.map(cache_file_name=__UpperCamelCase )
  return filename


# FILE_CONTENT + files


lowercase_				     =     '\\n    Text data.\n    Second line of data.'



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase ):




  """simple docstring"""







  __A									= tmp_path_factory.mktemp('''data''' ) / '''file.txt'''
  __A									= FILE_CONTENT
  with open(__UpperCamelCase		,       '''w''' ) as f:
    f.write(__UpperCamelCase )
  return filename



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase ):




  """simple docstring"""







  import bza

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



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase ):




  """simple docstring"""







  import gzip

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



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase ):




  """simple docstring"""







  if datasets.config.LZ4_AVAILABLE:
    import lza.frame

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



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase		,       __UpperCamelCase ):




  """simple docstring"""







  if datasets.config.PY7ZR_AVAILABLE:
    import pyazr

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



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase		,       __UpperCamelCase ):




  """simple docstring"""







  import tarfile

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



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase ):




  """simple docstring"""







  import lzma

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



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase		,       __UpperCamelCase ):




  """simple docstring"""







  import zipfile

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



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase ):




  """simple docstring"""







  if datasets.config.ZSTANDARD_AVAILABLE:
    import zstandard as zstd

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



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase ):




  """simple docstring"""







  __A									= tmp_path_factory.mktemp('''data''' ) / '''file.xml'''
  __A									= textwrap.dedent(
      '''\
    <?xml version="1.0" encoding="UTF-8" ?>
    <tmx version="1.4">
      <header segtype="sentence" srclang="ca" />
      <body>
        <tu>
          <tuv xml:lang="ca"><seg>Contingut 1</seg></tuv>
          <tuv xml:lang="en"><seg>Content 1</seg></tuv>
        </tu>
        <tu>
          <tuv xml:lang="ca"><seg>Contingut 2</seg></tuv>
          <tuv xml:lang="en"><seg>Content 2</seg></tuv>
        </tu>
        <tu>
          <tuv xml:lang="ca"><seg>Contingut 3</seg></tuv>
          <tuv xml:lang="en"><seg>Content 3</seg></tuv>
        </tu>
        <tu>
          <tuv xml:lang="ca"><seg>Contingut 4</seg></tuv>
          <tuv xml:lang="en"><seg>Content 4</seg></tuv>
        </tu>
        <tu>
          <tuv xml:lang="ca"><seg>Contingut 5</seg></tuv>
          <tuv xml:lang="en"><seg>Content 5</seg></tuv>
        </tu>
      </body>
    </tmx>''' )
  with open(__UpperCamelCase		,       '''w''' ) as f:
    f.write(__UpperCamelCase )
  return filename


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

lowercase_				     =     [
    {'col_3': 0.0, 'col_1': '0', 'col_2': 0},
    {'col_3': 1.0, 'col_1': '1', 'col_2': 1},
]

lowercase_				     =     [
    {'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 					lowerCAmelCase				(    ):




  """simple docstring"""







  return DATA_DICT_OF_LISTS



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase ):




  """simple docstring"""







  __A									= datasets.Dataset.from_dict(__UpperCamelCase )
  __A									= str(tmp_path_factory.mktemp('''data''' ) / '''dataset.arrow''' )
  dataset.map(cache_file_name=__UpperCamelCase )
  return path



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase ):




  """simple docstring"""







  __A									= str(tmp_path_factory.mktemp('''data''' ) / '''dataset.sqlite''' )
  with contextlib.closing(sqlitea.connect(__UpperCamelCase ) ) as con:
    __A									= 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 					lowerCAmelCase				(    __UpperCamelCase ):




  """simple docstring"""







  __A									= str(tmp_path_factory.mktemp('''data''' ) / '''dataset.csv''' )
  with open(__UpperCamelCase		,       '''w'''		,       newline='''''' ) as f:
    __A									= csv.DictWriter(__UpperCamelCase		,       fieldnames=['''col_1''', '''col_2''', '''col_3'''] )
    writer.writeheader()
    for item in DATA:
      writer.writerow(__UpperCamelCase )
  return path



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase ):




  """simple docstring"""







  __A									= str(tmp_path_factory.mktemp('''data''' ) / '''dataset2.csv''' )
  with open(__UpperCamelCase		,       '''w'''		,       newline='''''' ) as f:
    __A									= csv.DictWriter(__UpperCamelCase		,       fieldnames=['''col_1''', '''col_2''', '''col_3'''] )
    writer.writeheader()
    for item in DATA:
      writer.writerow(__UpperCamelCase )
  return path



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase		,       __UpperCamelCase ):




  """simple docstring"""







  import bza

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



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase		,       __UpperCamelCase		,       __UpperCamelCase ):




  """simple docstring"""







  __A									= tmp_path_factory.mktemp('''data''' ) / '''dataset.csv.zip'''
  with zipfile.ZipFile(__UpperCamelCase		,       '''w''' ) as f:
    f.write(__UpperCamelCase		,       arcname=os.path.basename(__UpperCamelCase ) )
    f.write(__UpperCamelCase		,       arcname=os.path.basename(__UpperCamelCase ) )
  return path



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase		,       __UpperCamelCase		,       __UpperCamelCase ):




  """simple docstring"""







  __A									= tmp_path_factory.mktemp('''data''' ) / '''dataset.csv.zip'''
  with zipfile.ZipFile(__UpperCamelCase		,       '''w''' ) as f:
    f.write(__UpperCamelCase		,       arcname=os.path.basename(csv_path.replace('''.csv'''		,       '''.CSV''' ) ) )
    f.write(__UpperCamelCase		,       arcname=os.path.basename(csva_path.replace('''.csv'''		,       '''.CSV''' ) ) )
  return path



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase		,       __UpperCamelCase		,       __UpperCamelCase ):




  """simple docstring"""







  __A									= tmp_path_factory.mktemp('''data''' ) / '''dataset_with_dir.csv.zip'''
  with zipfile.ZipFile(__UpperCamelCase		,       '''w''' ) as f:
    f.write(__UpperCamelCase		,       arcname=os.path.join('''main_dir'''		,       os.path.basename(__UpperCamelCase ) ) )
    f.write(__UpperCamelCase		,       arcname=os.path.join('''main_dir'''		,       os.path.basename(__UpperCamelCase ) ) )
  return path



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase ):




  """simple docstring"""







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



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase ):




  """simple docstring"""







  __A									= str(tmp_path_factory.mktemp('''data''' ) / '''dataset.json''' )
  __A									= {'''data''': DATA}
  with open(__UpperCamelCase		,       '''w''' ) as f:
    json.dump(__UpperCamelCase		,       __UpperCamelCase )
  return path



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase ):




  """simple docstring"""







  __A									= str(tmp_path_factory.mktemp('''data''' ) / '''dataset.json''' )
  __A									= {'''data''': DATA_DICT_OF_LISTS}
  with open(__UpperCamelCase		,       '''w''' ) as f:
    json.dump(__UpperCamelCase		,       __UpperCamelCase )
  return path



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase ):




  """simple docstring"""







  __A									= str(tmp_path_factory.mktemp('''data''' ) / '''dataset.jsonl''' )
  with open(__UpperCamelCase		,       '''w''' ) as f:
    for item in DATA:
      f.write(json.dumps(__UpperCamelCase ) + '''\n''' )
  return path



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase ):




  """simple docstring"""







  __A									= str(tmp_path_factory.mktemp('''data''' ) / '''dataset2.jsonl''' )
  with open(__UpperCamelCase		,       '''w''' ) as f:
    for item in DATA:
      f.write(json.dumps(__UpperCamelCase ) + '''\n''' )
  return path



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase ):




  """simple docstring"""







  __A									= str(tmp_path_factory.mktemp('''data''' ) / '''dataset_312.jsonl''' )
  with open(__UpperCamelCase		,       '''w''' ) as f:
    for item in DATA_312:
      f.write(json.dumps(__UpperCamelCase ) + '''\n''' )
  return path



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase ):




  """simple docstring"""







  __A									= str(tmp_path_factory.mktemp('''data''' ) / '''dataset-str.jsonl''' )
  with open(__UpperCamelCase		,       '''w''' ) as f:
    for item in DATA_STR:
      f.write(json.dumps(__UpperCamelCase ) + '''\n''' )
  return path



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase		,       __UpperCamelCase ):




  """simple docstring"""







  import gzip

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



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase		,       __UpperCamelCase ):




  """simple docstring"""







  import gzip

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



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase		,       __UpperCamelCase		,       __UpperCamelCase ):




  """simple docstring"""







  __A									= tmp_path_factory.mktemp('''data''' ) / '''dataset.jsonl.zip'''
  with zipfile.ZipFile(__UpperCamelCase		,       '''w''' ) as f:
    f.write(__UpperCamelCase		,       arcname=os.path.basename(__UpperCamelCase ) )
    f.write(__UpperCamelCase		,       arcname=os.path.basename(__UpperCamelCase ) )
  return path



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase		,       __UpperCamelCase		,       __UpperCamelCase		,       __UpperCamelCase ):




  """simple docstring"""







  __A									= tmp_path_factory.mktemp('''data''' ) / '''dataset_nested.jsonl.zip'''
  with zipfile.ZipFile(__UpperCamelCase		,       '''w''' ) as f:
    f.write(__UpperCamelCase		,       arcname=os.path.join('''nested'''		,       os.path.basename(__UpperCamelCase ) ) )
  return path



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase		,       __UpperCamelCase		,       __UpperCamelCase ):




  """simple docstring"""







  __A									= tmp_path_factory.mktemp('''data''' ) / '''dataset_with_dir.jsonl.zip'''
  with zipfile.ZipFile(__UpperCamelCase		,       '''w''' ) as f:
    f.write(__UpperCamelCase		,       arcname=os.path.join('''main_dir'''		,       os.path.basename(__UpperCamelCase ) ) )
    f.write(__UpperCamelCase		,       arcname=os.path.join('''main_dir'''		,       os.path.basename(__UpperCamelCase ) ) )
  return path



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase		,       __UpperCamelCase		,       __UpperCamelCase ):




  """simple docstring"""







  __A									= tmp_path_factory.mktemp('''data''' ) / '''dataset.jsonl.tar'''
  with tarfile.TarFile(__UpperCamelCase		,       '''w''' ) as f:
    f.add(__UpperCamelCase		,       arcname=os.path.basename(__UpperCamelCase ) )
    f.add(__UpperCamelCase		,       arcname=os.path.basename(__UpperCamelCase ) )
  return path



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase		,       __UpperCamelCase		,       __UpperCamelCase		,       __UpperCamelCase ):




  """simple docstring"""







  __A									= tmp_path_factory.mktemp('''data''' ) / '''dataset_nested.jsonl.tar'''
  with tarfile.TarFile(__UpperCamelCase		,       '''w''' ) as f:
    f.add(__UpperCamelCase		,       arcname=os.path.join('''nested'''		,       os.path.basename(__UpperCamelCase ) ) )
  return path



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase ):




  """simple docstring"""







  __A									= ['''0''', '''1''', '''2''', '''3''']
  __A									= str(tmp_path_factory.mktemp('''data''' ) / '''dataset.txt''' )
  with open(__UpperCamelCase		,       '''w''' ) as f:
    for item in data:
      f.write(item + '''\n''' )
  return path



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase ):




  """simple docstring"""







  __A									= ['''0''', '''1''', '''2''', '''3''']
  __A									= str(tmp_path_factory.mktemp('''data''' ) / '''dataset2.txt''' )
  with open(__UpperCamelCase		,       '''w''' ) as f:
    for item in data:
      f.write(item + '''\n''' )
  return path



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase ):




  """simple docstring"""







  __A									= ['''0''', '''1''', '''2''', '''3''']
  __A									= tmp_path_factory.mktemp('''data''' ) / '''dataset.abc'''
  with open(__UpperCamelCase		,       '''w''' ) as f:
    for item in data:
      f.write(item + '''\n''' )
  return path



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase		,       __UpperCamelCase		,       __UpperCamelCase ):




  """simple docstring"""







  __A									= tmp_path_factory.mktemp('''data''' ) / '''dataset.text.zip'''
  with zipfile.ZipFile(__UpperCamelCase		,       '''w''' ) as f:
    f.write(__UpperCamelCase		,       arcname=os.path.basename(__UpperCamelCase ) )
    f.write(__UpperCamelCase		,       arcname=os.path.basename(__UpperCamelCase ) )
  return path



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase		,       __UpperCamelCase		,       __UpperCamelCase ):




  """simple docstring"""







  __A									= tmp_path_factory.mktemp('''data''' ) / '''dataset_with_dir.text.zip'''
  with zipfile.ZipFile(__UpperCamelCase		,       '''w''' ) as f:
    f.write(__UpperCamelCase		,       arcname=os.path.join('''main_dir'''		,       os.path.basename(__UpperCamelCase ) ) )
    f.write(__UpperCamelCase		,       arcname=os.path.join('''main_dir'''		,       os.path.basename(__UpperCamelCase ) ) )
  return path



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase		,       __UpperCamelCase		,       __UpperCamelCase ):




  """simple docstring"""







  __A									= tmp_path_factory.mktemp('''data''' ) / '''dataset.ext.zip'''
  with zipfile.ZipFile(__UpperCamelCase		,       '''w''' ) as f:
    f.write(__UpperCamelCase		,       arcname=os.path.basename('''unsupported.ext''' ) )
    f.write(__UpperCamelCase		,       arcname=os.path.basename('''unsupported_2.ext''' ) )
  return path



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase ):




  """simple docstring"""







  __A									= '''\n'''.join(['''First''', '''Second\u2029with Unicode new line''', '''Third'''] )
  __A									= str(tmp_path_factory.mktemp('''data''' ) / '''dataset_with_unicode_new_lines.txt''' )
  with open(__UpperCamelCase		,       '''w'''		,       encoding='''utf-8''' ) as f:
    f.write(__UpperCamelCase )
  return path



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    ):




  """simple docstring"""







  return os.path.join('''tests'''		,       '''features'''		,       '''data'''		,       '''test_image_rgb.jpg''' )



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    ):




  """simple docstring"""







  return os.path.join('''tests'''		,       '''features'''		,       '''data'''		,       '''test_audio_44100.wav''' )



@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase		,       __UpperCamelCase ):




  """simple docstring"""







  __A									= tmp_path_factory.mktemp('''data''' ) / '''dataset.img.zip'''
  with zipfile.ZipFile(__UpperCamelCase		,       '''w''' ) as f:
    f.write(__UpperCamelCase		,       arcname=os.path.basename(__UpperCamelCase ) )
    f.write(__UpperCamelCase		,       arcname=os.path.basename(__UpperCamelCase ).replace('''.jpg'''		,       '''2.jpg''' ) )
  return path





@pytest.fixture(scope='''session''' )
def 					lowerCAmelCase				(    __UpperCamelCase ):




  """simple docstring"""







  __A									= tmp_path_factory.mktemp('''data_dir''' )

  (data_dir / "subdir").mkdir()
  with open(data_dir / '''subdir''' / '''train.txt'''		,       '''w''' ) as f:
    f.write('''foo\n''' * 1_0 )
  with open(data_dir / '''subdir''' / '''test.txt'''		,       '''w''' ) as f:
    f.write('''bar\n''' * 1_0 )
  # hidden file
  with open(data_dir / '''subdir''' / '''.test.txt'''		,       '''w''' ) as f:
    f.write('''bar\n''' * 1_0 )

  # hidden directory
  (data_dir / ".subdir").mkdir()
  with open(data_dir / '''.subdir''' / '''train.txt'''		,       '''w''' ) as f:
    f.write('''foo\n''' * 1_0 )
  with open(data_dir / '''.subdir''' / '''test.txt'''		,       '''w''' ) as f:
    f.write('''bar\n''' * 1_0 )

  return data_dir












"""simple docstring"""


import unittest

import numpy as np

from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available

from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs


if is_torch_available():
       import torch

if is_vision_available():
       from PIL import Image

       from transformers import ViTImageProcessor


class 					snake_case		(							unittest.TestCase						):


   '''simple docstring'''

   def __init__(	self :     List[str],       _lowerCamelCase :     Optional[Any],       _lowerCamelCase :     Union[str, Any]=13,       _lowerCamelCase :     Any=3,       _lowerCamelCase :     Optional[int]=2_24,       _lowerCamelCase :     str=30,       _lowerCamelCase :     Dict=4_00,       _lowerCamelCase :     Union[str, Any]=True,       _lowerCamelCase :     Any=None,       _lowerCamelCase :     Optional[Any]=True,       _lowerCamelCase :     Any=[0.5, 0.5, 0.5],       _lowerCamelCase :     List[str]=[0.5, 0.5, 0.5],       ):

     '''simple docstring'''
     __A									= size if size is not None else {'''height''': 18, '''width''': 18}
     __A									= parent
     __A									= batch_size
     __A									= num_channels
     __A									= image_size
     __A									= min_resolution
     __A									= max_resolution
     __A									= do_resize
     __A									= size
     __A									= do_normalize
     __A									= image_mean
     __A									= image_std






   def 				_SCREAMING_SNAKE_CASE				(	self :     int  ):

     '''simple docstring'''
     return {
         "image_mean": self.image_mean,
         "image_std": self.image_std,
         "do_normalize": self.do_normalize,
         "do_resize": self.do_resize,
         "size": self.size,
     }





@require_torch
@require_vision
class 					snake_case		(							_lowerCAmelCase   ,	unittest.TestCase						):


   '''simple docstring'''

   A_						:	str						 = ViTImageProcessor if is_vision_available() else None


   def 				_SCREAMING_SNAKE_CASE				(	self :     Optional[int]  ):

     '''simple docstring'''
     __A									= EfficientFormerImageProcessorTester(self  )


   @property
   def 				_SCREAMING_SNAKE_CASE				(	self :     Dict  ):

     '''simple docstring'''
     return self.image_proc_tester.prepare_image_processor_dict()


   def 				_SCREAMING_SNAKE_CASE				(	self :     Optional[Any]  ):

     '''simple docstring'''
     __A									= self.image_processing_class(**self.image_processor_dict  )
     self.assertTrue(hasattr(_lowerCamelCase,       '''image_mean'''  )  )
     self.assertTrue(hasattr(_lowerCamelCase,       '''image_std'''  )  )
     self.assertTrue(hasattr(_lowerCamelCase,       '''do_normalize'''  )  )
     self.assertTrue(hasattr(_lowerCamelCase,       '''do_resize'''  )  )
     self.assertTrue(hasattr(_lowerCamelCase,       '''size'''  )  )


   def 				_SCREAMING_SNAKE_CASE				(	self :     Union[str, Any]  ):

     '''simple docstring'''
     pass


   def 				_SCREAMING_SNAKE_CASE				(	self :     List[Any]  ):

     '''simple docstring'''
     # Initialize image_processor
     __A									= self.image_processing_class(**self.image_processor_dict  )
     # create random PIL images
     __A									= prepare_image_inputs(self.image_proc_tester,       equal_resolution=_lowerCamelCase  )
     for image in image_inputs:
       self.assertIsInstance(_lowerCamelCase,       Image.Image  )

     # Test not batched input
     __A									= image_processor(image_inputs[0],       return_tensors='''pt'''  ).pixel_values
     self.assertEqual(
         encoded_images.shape,       (
             1,
             self.image_proc_tester.num_channels,
             self.image_proc_tester.size['''height'''],
             self.image_proc_tester.size['''width'''],
         ),       )

     # Test batched
     __A									= image_processor(_lowerCamelCase,       return_tensors='''pt'''  ).pixel_values
     self.assertEqual(
         encoded_images.shape,       (
             self.image_proc_tester.batch_size,
             self.image_proc_tester.num_channels,
             self.image_proc_tester.size['''height'''],
             self.image_proc_tester.size['''width'''],
         ),       )


   def 				_SCREAMING_SNAKE_CASE				(	self :     Tuple  ):

     '''simple docstring'''
     # Initialize image_processor
     __A									= self.image_processing_class(**self.image_processor_dict  )
     # create random numpy tensors
     __A									= prepare_image_inputs(self.image_proc_tester,       equal_resolution=_lowerCamelCase,       numpify=_lowerCamelCase  )
     for image in image_inputs:
       self.assertIsInstance(_lowerCamelCase,       np.ndarray  )

     # Test not batched input
     __A									= image_processor(image_inputs[0],       return_tensors='''pt'''  ).pixel_values
     self.assertEqual(
         encoded_images.shape,       (
             1,
             self.image_proc_tester.num_channels,
             self.image_proc_tester.size['''height'''],
             self.image_proc_tester.size['''width'''],
         ),       )

     # Test batched
     __A									= image_processor(_lowerCamelCase,       return_tensors='''pt'''  ).pixel_values
     self.assertEqual(
         encoded_images.shape,       (
             self.image_proc_tester.batch_size,
             self.image_proc_tester.num_channels,
             self.image_proc_tester.size['''height'''],
             self.image_proc_tester.size['''width'''],
         ),       )






   def 				_SCREAMING_SNAKE_CASE				(	self :     str  ):

     '''simple docstring'''
     # Initialize image_processor
     __A									= self.image_processing_class(**self.image_processor_dict  )
     # create random PyTorch tensors
     __A									= prepare_image_inputs(self.image_proc_tester,       equal_resolution=_lowerCamelCase,       torchify=_lowerCamelCase  )
     for image in image_inputs:
       self.assertIsInstance(_lowerCamelCase,       torch.Tensor  )

     # Test not batched input
     __A									= image_processor(image_inputs[0],       return_tensors='''pt'''  ).pixel_values
     self.assertEqual(
         encoded_images.shape,       (
             1,
             self.image_proc_tester.num_channels,
             self.image_proc_tester.size['''height'''],
             self.image_proc_tester.size['''width'''],
         ),       )

     # Test batched
     __A									= image_processor(_lowerCamelCase,       return_tensors='''pt'''  ).pixel_values
     self.assertEqual(
         encoded_images.shape,       (
             self.image_proc_tester.batch_size,
             self.image_proc_tester.num_channels,
             self.image_proc_tester.size['''height'''],
             self.image_proc_tester.size['''width'''],
         ),       )




