




import json
import sys
import tempfile
import unittest
from pathlib import Path

import transformers
from transformers import (
    CONFIG_MAPPING,
    IMAGE_PROCESSOR_MAPPING,
    AutoConfig,
    AutoImageProcessor,
    CLIPConfig,
    CLIPImageProcessor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER


sys.path.append(str(Path(__file__).parent.parent.parent.parent / 'utils'))

from test_module.custom_configuration import CustomConfig  # noqa E402
from test_module.custom_image_processing import CustomImageProcessor  # noqa E402





class        lowerCamelCase_							(      unittest.TestCase					):


 '''simple docstring'''







 def       lowerCAmelCase_  (							self  :		Any						):
       SCREAMING_SNAKE_CASE_							=			0



 def       lowerCAmelCase_  (							self  :		int						):
       SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained('openai/clip-vit-base-patch32'						)
       self.assertIsInstance(_lowerCAmelCase				,				_lowerCAmelCase						)



 def       lowerCAmelCase_  (							self  :		Optional[int]						):
       with tempfile.TemporaryDirectory() as tmpdirname:
             SCREAMING_SNAKE_CASE_							=			Path(_lowerCAmelCase						) / 'preprocessor_config.json'
             SCREAMING_SNAKE_CASE_							=			Path(_lowerCAmelCase						) / 'config.json'
             json.dump(
                 {'image_processor_type': 'CLIPImageProcessor', 'processor_class': 'CLIPProcessor'}				,				open(_lowerCAmelCase				,				'w'						)				,				)
             json.dump({'model_type': 'clip'}				,				open(_lowerCAmelCase				,				'w'						)						)

             SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained(_lowerCAmelCase						)
             self.assertIsInstance(_lowerCAmelCase				,				_lowerCAmelCase						)



 def       lowerCAmelCase_  (							self  :		str						):
       # Ensure we can load the image processor from the feature extractor config
       with tempfile.TemporaryDirectory() as tmpdirname:
             SCREAMING_SNAKE_CASE_							=			Path(_lowerCAmelCase						) / 'preprocessor_config.json'
             SCREAMING_SNAKE_CASE_							=			Path(_lowerCAmelCase						) / 'config.json'
             json.dump(
                 {'feature_extractor_type': 'CLIPFeatureExtractor', 'processor_class': 'CLIPProcessor'}				,				open(_lowerCAmelCase				,				'w'						)				,				)
             json.dump({'model_type': 'clip'}				,				open(_lowerCAmelCase				,				'w'						)						)

             SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained(_lowerCAmelCase						)
             self.assertIsInstance(_lowerCAmelCase				,				_lowerCAmelCase						)



 def       lowerCAmelCase_  (							self  :		Union[str, Any]						):
       with tempfile.TemporaryDirectory() as tmpdirname:
             SCREAMING_SNAKE_CASE_							=			CLIPConfig()

             # Create a dummy config file with image_proceesor_type
             SCREAMING_SNAKE_CASE_							=			Path(_lowerCAmelCase						) / 'preprocessor_config.json'
             SCREAMING_SNAKE_CASE_							=			Path(_lowerCAmelCase						) / 'config.json'
             json.dump(
                 {'image_processor_type': 'CLIPImageProcessor', 'processor_class': 'CLIPProcessor'}				,				open(_lowerCAmelCase				,				'w'						)				,				)
             json.dump({'model_type': 'clip'}				,				open(_lowerCAmelCase				,				'w'						)						)

             # remove image_processor_type to make sure config.json alone is enough to load image processor locally
             SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained(_lowerCAmelCase						).to_dict()

             config_dict.pop('image_processor_type'						)
             SCREAMING_SNAKE_CASE_							=			CLIPImageProcessor(**_lowerCAmelCase						)

             # save in new folder
             model_config.save_pretrained(_lowerCAmelCase						)
             config.save_pretrained(_lowerCAmelCase						)

             SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained(_lowerCAmelCase						)

             # make sure private variable is not incorrectly saved
             SCREAMING_SNAKE_CASE_							=			json.loads(config.to_json_string()						)
             self.assertTrue('_processor_class' not in dict_as_saved						)

       self.assertIsInstance(_lowerCAmelCase				,				_lowerCAmelCase						)



 def       lowerCAmelCase_  (							self  :		str						):
       with tempfile.TemporaryDirectory() as tmpdirname:
             SCREAMING_SNAKE_CASE_							=			Path(_lowerCAmelCase						) / 'preprocessor_config.json'
             json.dump(
                 {'image_processor_type': 'CLIPImageProcessor', 'processor_class': 'CLIPProcessor'}				,				open(_lowerCAmelCase				,				'w'						)				,				)

             SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained(_lowerCAmelCase						)
             self.assertIsInstance(_lowerCAmelCase				,				_lowerCAmelCase						)



 def       lowerCAmelCase_  (							self  :		List[Any]						):
       with self.assertRaisesRegex(
           _lowerCAmelCase				,				'clip-base is not a local folder and is not a valid model identifier'						):
             SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained('clip-base'						)



 def       lowerCAmelCase_  (							self  :		List[Any]						):
       with self.assertRaisesRegex(
           _lowerCAmelCase				,				R'aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'						):
             SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained(_lowerCAmelCase				,				revision='aaaaaa'						)



 def       lowerCAmelCase_  (							self  :		str						):
       with self.assertRaisesRegex(
           _lowerCAmelCase				,				'hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json.'				,				):
             SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained('hf-internal-testing/config-no-model'						)



 def       lowerCAmelCase_  (							self  :		Tuple						):
       # If remote code is not set, we will time out when asking whether to load the model.
       with self.assertRaises(_lowerCAmelCase						):
             SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained('hf-internal-testing/test_dynamic_image_processor'						)
       # If remote code is disabled, we can't load this config.
       with self.assertRaises(_lowerCAmelCase						):
             SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained(
                 'hf-internal-testing/test_dynamic_image_processor'				,				trust_remote_code=_lowerCAmelCase						)

       SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained(
           'hf-internal-testing/test_dynamic_image_processor'				,				trust_remote_code=_lowerCAmelCase						)
       self.assertEqual(image_processor.__class__.__name__				,				'NewImageProcessor'						)

       # Test image processor can be reloaded.
       with tempfile.TemporaryDirectory() as tmp_dir:
             image_processor.save_pretrained(_lowerCAmelCase						)
             SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained(_lowerCAmelCase				,				trust_remote_code=_lowerCAmelCase						)
       self.assertEqual(reloaded_image_processor.__class__.__name__				,				'NewImageProcessor'						)



 def       lowerCAmelCase_  (							self  :		Optional[Any]						):
       try:
             AutoConfig.register('custom'				,				_lowerCAmelCase						)
             AutoImageProcessor.register(_lowerCAmelCase				,				_lowerCAmelCase						)
             # Trying to register something existing in the Transformers library will raise an error
             with self.assertRaises(_lowerCAmelCase						):
                   AutoImageProcessor.register(_lowerCAmelCase				,				_lowerCAmelCase						)

             with tempfile.TemporaryDirectory() as tmpdirname:
                   SCREAMING_SNAKE_CASE_							=			Path(_lowerCAmelCase						) / 'preprocessor_config.json'
                   SCREAMING_SNAKE_CASE_							=			Path(_lowerCAmelCase						) / 'config.json'
                   json.dump(
                       {'feature_extractor_type': 'CLIPFeatureExtractor', 'processor_class': 'CLIPProcessor'}				,				open(_lowerCAmelCase				,				'w'						)				,				)
                   json.dump({'model_type': 'clip'}				,				open(_lowerCAmelCase				,				'w'						)						)

                   SCREAMING_SNAKE_CASE_							=			CustomImageProcessor.from_pretrained(_lowerCAmelCase						)

             # Now that the config is registered, it can be used as any other config with the auto-API
             with tempfile.TemporaryDirectory() as tmp_dir:
                   image_processor.save_pretrained(_lowerCAmelCase						)
                   SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained(_lowerCAmelCase						)
                   self.assertIsInstance(_lowerCAmelCase				,				_lowerCAmelCase						)

       finally:
             if "custom" in CONFIG_MAPPING._extra_content:
                   del CONFIG_MAPPING._extra_content["custom"]
             if CustomConfig in IMAGE_PROCESSOR_MAPPING._extra_content:
                   del IMAGE_PROCESSOR_MAPPING._extra_content[CustomConfig]




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





       class        lowerCamelCase_							(      _SCREAMING_SNAKE_CASE					):


        '''simple docstring'''







        lowercase_				    =    True

       try:
             AutoConfig.register('custom'				,				_lowerCAmelCase						)
             AutoImageProcessor.register(_lowerCAmelCase				,				_lowerCAmelCase						)
             # If remote code is not set, the default is to use local
             SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained('hf-internal-testing/test_dynamic_image_processor'						)
             self.assertEqual(image_processor.__class__.__name__				,				'NewImageProcessor'						)
             self.assertTrue(image_processor.is_local						)

             # If remote code is disabled, we load the local one.
             SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained(
                 'hf-internal-testing/test_dynamic_image_processor'				,				trust_remote_code=_lowerCAmelCase						)
             self.assertEqual(image_processor.__class__.__name__				,				'NewImageProcessor'						)
             self.assertTrue(image_processor.is_local						)

             # If remote is enabled, we load from the Hub
             SCREAMING_SNAKE_CASE_							=			AutoImageProcessor.from_pretrained(
                 'hf-internal-testing/test_dynamic_image_processor'				,				trust_remote_code=_lowerCAmelCase						)
             self.assertEqual(image_processor.__class__.__name__				,				'NewImageProcessor'						)
             self.assertTrue(not hasattr(_lowerCAmelCase				,				'is_local'						)						)

       finally:
             if "custom" in CONFIG_MAPPING._extra_content:
                   del CONFIG_MAPPING._extra_content["custom"]
             if CustomConfig in IMAGE_PROCESSOR_MAPPING._extra_content:
                   del IMAGE_PROCESSOR_MAPPING._extra_content[CustomConfig]





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 					UpperCAmelCase_							(      )					-> str:
      SCREAMING_SNAKE_CASE_							=			10
      SCREAMING_SNAKE_CASE_							=			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'							),
          }							)
      SCREAMING_SNAKE_CASE_							=			datasets.Dataset.from_dict(
          {
              'tokens': [['foo'] * 5] * n,
              'labels': [[1] * 5] * n,
              'answers': [{'answer_start': [97], 'text': ['1976']}] * 10,
              'id': list(range(__UpperCAmelCase							)							),
          }			,			features=__UpperCAmelCase			,			)
      return dataset

@pytest.fixture(scope='session'							)
def 					UpperCAmelCase_							(      __UpperCAmelCase						:	Tuple			,			__UpperCAmelCase						:	str							)					-> int:
      SCREAMING_SNAKE_CASE_							=			str(tmp_path_factory.mktemp('data'							) / 'file.arrow'							)
      dataset.map(cache_file_name=__UpperCAmelCase							)
      return filename


# FILE_CONTENT + files


lowerCamelCase__ :   List[Any]					=							'\\n    Text data.\n    Second line of data.'

@pytest.fixture(scope='session'							)
def 					UpperCAmelCase_							(      __UpperCAmelCase						:	Any							)					-> List[str]:
      SCREAMING_SNAKE_CASE_							=			tmp_path_factory.mktemp('data'							) / 'file.txt'
      SCREAMING_SNAKE_CASE_							=			FILE_CONTENT
      with open(__UpperCAmelCase			,			'w'							) as f:
            f.write(__UpperCAmelCase							)
      return filename

@pytest.fixture(scope='session'							)
def 					UpperCAmelCase_							(      __UpperCAmelCase						:	Dict							)					-> List[str]:
      import bza

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

@pytest.fixture(scope='session'							)
def 					UpperCAmelCase_							(      __UpperCAmelCase						:	List[Any]							)					-> Any:
      import gzip

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

@pytest.fixture(scope='session'							)
def 					UpperCAmelCase_							(      __UpperCAmelCase						:	List[str]							)					-> int:
      if datasets.config.LZ4_AVAILABLE:
            import lza.frame

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

@pytest.fixture(scope='session'							)
def 					UpperCAmelCase_							(      __UpperCAmelCase						:	List[Any]			,			__UpperCAmelCase						:	Union[str, Any]							)					-> Any:
      if datasets.config.PY7ZR_AVAILABLE:
            import pyazr

            SCREAMING_SNAKE_CASE_							=			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 					UpperCAmelCase_							(      __UpperCAmelCase						:	Dict			,			__UpperCAmelCase						:	str							)					-> str:
      import tarfile

      SCREAMING_SNAKE_CASE_							=			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 					UpperCAmelCase_							(      __UpperCAmelCase						:	str							)					-> List[Any]:
      import lzma

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

@pytest.fixture(scope='session'							)
def 					UpperCAmelCase_							(      __UpperCAmelCase						:	Dict			,			__UpperCAmelCase						:	Dict							)					-> str:
      import zipfile

      SCREAMING_SNAKE_CASE_							=			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 					UpperCAmelCase_							(      __UpperCAmelCase						:	Dict							)					-> Any:
      if datasets.config.ZSTANDARD_AVAILABLE:
            import zstandard as zstd

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

@pytest.fixture(scope='session'							)
def 					UpperCAmelCase_							(      __UpperCAmelCase						:	int							)					-> List[Any]:
      SCREAMING_SNAKE_CASE_							=			tmp_path_factory.mktemp('data'							) / 'file.xml'
      SCREAMING_SNAKE_CASE_							=			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(__UpperCAmelCase			,			'w'							) as f:
            f.write(__UpperCAmelCase							)
      return filename


lowerCamelCase__ :   Optional[Any]					=							[
    {'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},
]
lowerCamelCase__ :   Dict					=							[
    {'col_1': '4', 'col_2': 4, 'col_3': 4.0},
    {'col_1': '5', 'col_2': 5, 'col_3': 5.0},
]
lowerCamelCase__ :   Optional[int]					=							{
    'col_1': ['0', '1', '2', '3'],
    'col_2': [0, 1, 2, 3],
    'col_3': [0.0, 1.0, 2.0, 3.0],
}

lowerCamelCase__ :   List[Any]					=							[
    {'col_3': 0.0, 'col_1': '0', 'col_2': 0},
    {'col_3': 1.0, 'col_1': '1', 'col_2': 1},
]

lowerCamelCase__ :   List[Any]					=							[
    {'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 					UpperCAmelCase_							(      )					-> Tuple:
      return DATA_DICT_OF_LISTS

@pytest.fixture(scope='session'							)
def 					UpperCAmelCase_							(      __UpperCAmelCase						:	Optional[Any]							)					-> Union[str, Any]:
      SCREAMING_SNAKE_CASE_							=			datasets.Dataset.from_dict(__UpperCAmelCase							)
      SCREAMING_SNAKE_CASE_							=			str(tmp_path_factory.mktemp('data'							) / 'dataset.arrow'							)
      dataset.map(cache_file_name=__UpperCAmelCase							)
      return path

@pytest.fixture(scope='session'							)
def 					UpperCAmelCase_							(      __UpperCAmelCase						:	List[str]							)					-> List[str]:
      SCREAMING_SNAKE_CASE_							=			str(tmp_path_factory.mktemp('data'							) / 'dataset.sqlite'							)
      with contextlib.closing(sqlitea.connect(__UpperCAmelCase							)							) as con:
            SCREAMING_SNAKE_CASE_							=			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 					UpperCAmelCase_							(      __UpperCAmelCase						:	Optional[int]							)					-> str:
      SCREAMING_SNAKE_CASE_							=			str(tmp_path_factory.mktemp('data'							) / 'dataset.csv'							)
      with open(__UpperCAmelCase			,			'w'			,			newline=''							) as f:
            SCREAMING_SNAKE_CASE_							=			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 					UpperCAmelCase_							(      __UpperCAmelCase						:	Tuple							)					-> Optional[Any]:
      SCREAMING_SNAKE_CASE_							=			str(tmp_path_factory.mktemp('data'							) / 'dataset2.csv'							)
      with open(__UpperCAmelCase			,			'w'			,			newline=''							) as f:
            SCREAMING_SNAKE_CASE_							=			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 					UpperCAmelCase_							(      __UpperCAmelCase						:	str			,			__UpperCAmelCase						:	Tuple							)					-> str:
      import bza

      SCREAMING_SNAKE_CASE_							=			tmp_path_factory.mktemp('data'							) / 'dataset.csv.bz2'
      with open(__UpperCAmelCase			,			'rb'							) as f:
            SCREAMING_SNAKE_CASE_							=			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 					UpperCAmelCase_							(      __UpperCAmelCase						:	Dict			,			__UpperCAmelCase						:	List[str]			,			__UpperCAmelCase						:	str							)					-> Optional[int]:
      SCREAMING_SNAKE_CASE_							=			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 					UpperCAmelCase_							(      __UpperCAmelCase						:	List[Any]			,			__UpperCAmelCase						:	int			,			__UpperCAmelCase						:	str							)					-> Any:
      SCREAMING_SNAKE_CASE_							=			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 					UpperCAmelCase_							(      __UpperCAmelCase						:	int			,			__UpperCAmelCase						:	Tuple			,			__UpperCAmelCase						:	List[Any]							)					-> Union[str, Any]:
      SCREAMING_SNAKE_CASE_							=			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 					UpperCAmelCase_							(      __UpperCAmelCase						:	List[str]							)					-> Optional[Any]:
      SCREAMING_SNAKE_CASE_							=			str(tmp_path_factory.mktemp('data'							) / 'dataset.parquet'							)
      SCREAMING_SNAKE_CASE_							=			pa.schema(
          {
              'col_1': pa.string(),
              'col_2': pa.intaa(),
              'col_3': pa.floataa(),
          }							)
      with open(__UpperCAmelCase			,			'wb'							) as f:
            SCREAMING_SNAKE_CASE_							=			pq.ParquetWriter(__UpperCAmelCase			,			schema=__UpperCAmelCase							)
            SCREAMING_SNAKE_CASE_							=			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 					UpperCAmelCase_							(      __UpperCAmelCase						:	Tuple							)					-> Any:
      SCREAMING_SNAKE_CASE_							=			str(tmp_path_factory.mktemp('data'							) / 'dataset.json'							)
      SCREAMING_SNAKE_CASE_							=			{'data': DATA}
      with open(__UpperCAmelCase			,			'w'							) as f:
            json.dump(__UpperCAmelCase			,			__UpperCAmelCase							)
      return path

@pytest.fixture(scope='session'							)
def 					UpperCAmelCase_							(      __UpperCAmelCase						:	Union[str, Any]							)					-> Optional[Any]:
      SCREAMING_SNAKE_CASE_							=			str(tmp_path_factory.mktemp('data'							) / 'dataset.json'							)
      SCREAMING_SNAKE_CASE_							=			{'data': DATA_DICT_OF_LISTS}
      with open(__UpperCAmelCase			,			'w'							) as f:
            json.dump(__UpperCAmelCase			,			__UpperCAmelCase							)
      return path

@pytest.fixture(scope='session'							)
def 					UpperCAmelCase_							(      __UpperCAmelCase						:	Dict							)					-> List[str]:
      SCREAMING_SNAKE_CASE_							=			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 					UpperCAmelCase_							(      __UpperCAmelCase						:	Optional[Any]							)					-> Optional[Any]:
      SCREAMING_SNAKE_CASE_							=			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 					UpperCAmelCase_							(      __UpperCAmelCase						:	List[Any]							)					-> List[Any]:
      SCREAMING_SNAKE_CASE_							=			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 					UpperCAmelCase_							(      __UpperCAmelCase						:	Optional[Any]							)					-> List[Any]:
      SCREAMING_SNAKE_CASE_							=			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 					UpperCAmelCase_							(      __UpperCAmelCase						:	Union[str, Any]			,			__UpperCAmelCase						:	List[str]							)					-> Union[str, Any]:
      import gzip

      SCREAMING_SNAKE_CASE_							=			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 					UpperCAmelCase_							(      __UpperCAmelCase						:	str			,			__UpperCAmelCase						:	Optional[Any]							)					-> List[str]:
      import gzip

      SCREAMING_SNAKE_CASE_							=			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 					UpperCAmelCase_							(      __UpperCAmelCase						:	Union[str, Any]			,			__UpperCAmelCase						:	Optional[Any]			,			__UpperCAmelCase						:	Dict							)					-> Optional[int]:
      SCREAMING_SNAKE_CASE_							=			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 					UpperCAmelCase_							(      __UpperCAmelCase						:	Optional[Any]			,			__UpperCAmelCase						:	Any			,			__UpperCAmelCase						:	List[str]			,			__UpperCAmelCase						:	List[str]							)					-> Optional[int]:
      SCREAMING_SNAKE_CASE_							=			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 					UpperCAmelCase_							(      __UpperCAmelCase						:	List[str]			,			__UpperCAmelCase						:	Optional[Any]			,			__UpperCAmelCase						:	str							)					-> Any:
      SCREAMING_SNAKE_CASE_							=			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 					UpperCAmelCase_							(      __UpperCAmelCase						:	List[Any]			,			__UpperCAmelCase						:	List[Any]			,			__UpperCAmelCase						:	Tuple							)					-> Dict:
      SCREAMING_SNAKE_CASE_							=			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 					UpperCAmelCase_							(      __UpperCAmelCase						:	Optional[int]			,			__UpperCAmelCase						:	Optional[int]			,			__UpperCAmelCase						:	Optional[Any]			,			__UpperCAmelCase						:	List[Any]							)					-> List[str]:
      SCREAMING_SNAKE_CASE_							=			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 					UpperCAmelCase_							(      __UpperCAmelCase						:	Optional[Any]							)					-> Optional[Any]:
      SCREAMING_SNAKE_CASE_							=			['0', '1', '2', '3']
      SCREAMING_SNAKE_CASE_							=			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 					UpperCAmelCase_							(      __UpperCAmelCase						:	Dict							)					-> Any:
      SCREAMING_SNAKE_CASE_							=			['0', '1', '2', '3']
      SCREAMING_SNAKE_CASE_							=			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 					UpperCAmelCase_							(      __UpperCAmelCase						:	List[Any]							)					-> int:
      SCREAMING_SNAKE_CASE_							=			['0', '1', '2', '3']
      SCREAMING_SNAKE_CASE_							=			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 					UpperCAmelCase_							(      __UpperCAmelCase						:	Any			,			__UpperCAmelCase						:	Dict			,			__UpperCAmelCase						:	Dict							)					-> Union[str, Any]:
      SCREAMING_SNAKE_CASE_							=			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 					UpperCAmelCase_							(      __UpperCAmelCase						:	Tuple			,			__UpperCAmelCase						:	int			,			__UpperCAmelCase						:	Optional[int]							)					-> Any:
      SCREAMING_SNAKE_CASE_							=			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 					UpperCAmelCase_							(      __UpperCAmelCase						:	Union[str, Any]			,			__UpperCAmelCase						:	Any			,			__UpperCAmelCase						:	Union[str, Any]							)					-> Dict:
      SCREAMING_SNAKE_CASE_							=			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 					UpperCAmelCase_							(      __UpperCAmelCase						:	Union[str, Any]							)					-> Dict:
      SCREAMING_SNAKE_CASE_							=			'\n'.join(['First', 'Second\u2029with Unicode new line', 'Third']							)
      SCREAMING_SNAKE_CASE_							=			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 					UpperCAmelCase_							(      )					-> List[Any]:
      return os.path.join('tests'			,			'features'			,			'data'			,			'test_image_rgb.jpg'							)

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

@pytest.fixture(scope='session'							)
def 					UpperCAmelCase_							(      __UpperCAmelCase						:	Dict			,			__UpperCAmelCase						:	Dict							)					-> int:
      SCREAMING_SNAKE_CASE_							=			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 					UpperCAmelCase_							(      __UpperCAmelCase						:	str							)					-> Dict:
      SCREAMING_SNAKE_CASE_							=			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