





from dataclasses import dataclass
from typing import Optional, Tuple, Union

import numpy as np
import torch

from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin

@dataclass
class   A							(						__lowercase    ):
      _snake_case				  =42
      _snake_case				  =42
      _snake_case				  =None

class   A							(						__lowercase		,   __lowercase    ):
      _snake_case				  =2



      @register_to_config
      def __init__(						self:    List[str]		,	_lowerCAmelCase:    float = 0.02		,	_lowerCAmelCase:    float = 100		,	_lowerCAmelCase:    float = 1.0_07		,	_lowerCAmelCase:    float = 80		,	_lowerCAmelCase:    float = 0.05		,	_lowerCAmelCase:    float = 50		,	)    ->     Any:
         '''simple docstring'''

         UpperCAmelCase_           =sigma_max

         # setable values
         UpperCAmelCase_           =None
         UpperCAmelCase_           =None
         UpperCAmelCase_           =None  # sigma(t_i)



      def 						lowerCAmelCase__     (						self:    Any		,	_lowerCAmelCase:    torch.FloatTensor		,	_lowerCAmelCase:    Optional[int] = None							)    ->     torch.FloatTensor:
         '''simple docstring'''

         return sample



      def 						lowerCAmelCase__     (						self:    List[Any]		,	_lowerCAmelCase:    int		,	_lowerCAmelCase:    Union[str, torch.device] = None							)    ->     Optional[Any]:
         '''simple docstring'''

         UpperCAmelCase_           =num_inference_steps
         UpperCAmelCase_           =np.arange(0		,	self.num_inference_steps							)[::-1].copy()
         UpperCAmelCase_           =torch.from_numpy(_lowerCAmelCase							).to(_lowerCAmelCase							)
         UpperCAmelCase_           =[
             (
                 self.config.sigma_max**2
                 * (self.config.sigma_min**2 / self.config.sigma_max**2) ** (i / (num_inference_steps - 1))
             )
             for i in self.timesteps
         ]
         UpperCAmelCase_           =torch.tensor(_lowerCAmelCase		,	dtype=torch.floataa		,	device=_lowerCAmelCase							)



      def 						lowerCAmelCase__     (						self:    List[str]		,	_lowerCAmelCase:    torch.FloatTensor		,	_lowerCAmelCase:    float		,	_lowerCAmelCase:    Optional[torch.Generator] = None							)    ->     Tuple[torch.FloatTensor, float]:
         '''simple docstring'''

         if self.config.s_min <= sigma <= self.config.s_max:
            UpperCAmelCase_           =min(self.config.s_churn / self.num_inference_steps		,	2**0.5 - 1							)
         else:
            UpperCAmelCase_           =0

         # sample eps ~ N(0, S_noise^2 * I)
         UpperCAmelCase_           =self.config.s_noise * randn_tensor(sample.shape		,	generator=_lowerCAmelCase							).to(sample.device							)
         UpperCAmelCase_           =sigma + gamma * sigma
         UpperCAmelCase_           =sample + ((sigma_hat**2 - sigma**2) ** 0.5 * eps)

         return sample_hat, sigma_hat



      def 						lowerCAmelCase__     (						self:    Optional[int]		,	_lowerCAmelCase:    torch.FloatTensor		,	_lowerCAmelCase:    float		,	_lowerCAmelCase:    float		,	_lowerCAmelCase:    torch.FloatTensor		,	_lowerCAmelCase:    bool = True		,	)    ->     Union[KarrasVeOutput, Tuple]:
         '''simple docstring'''

         UpperCAmelCase_           =sample_hat + sigma_hat * model_output
         UpperCAmelCase_           =(sample_hat - pred_original_sample) / sigma_hat
         UpperCAmelCase_           =sample_hat + (sigma_prev - sigma_hat) * derivative

         if not return_dict:
            return (sample_prev, derivative)

         return KarrasVeOutput(
             prev_sample=_lowerCAmelCase		,	derivative=_lowerCAmelCase		,	pred_original_sample=_lowerCAmelCase							)



      def 						lowerCAmelCase__     (						self:    Tuple		,	_lowerCAmelCase:    torch.FloatTensor		,	_lowerCAmelCase:    float		,	_lowerCAmelCase:    float		,	_lowerCAmelCase:    torch.FloatTensor		,	_lowerCAmelCase:    torch.FloatTensor		,	_lowerCAmelCase:    torch.FloatTensor		,	_lowerCAmelCase:    bool = True		,	)    ->     Union[KarrasVeOutput, Tuple]:
         '''simple docstring'''

         UpperCAmelCase_           =sample_prev + sigma_prev * model_output
         UpperCAmelCase_           =(sample_prev - pred_original_sample) / sigma_prev
         UpperCAmelCase_           =sample_hat + (sigma_prev - sigma_hat) * (0.5 * derivative + 0.5 * derivative_corr)

         if not return_dict:
            return (sample_prev, derivative)

         return KarrasVeOutput(
             prev_sample=_lowerCAmelCase		,	derivative=_lowerCAmelCase		,	pred_original_sample=_lowerCAmelCase							)






      def 						lowerCAmelCase__     (						self:    int		,	_lowerCAmelCase:    Dict		,	_lowerCAmelCase:    List[str]		,	_lowerCAmelCase:    Any							)    ->     List[Any]:
         '''simple docstring'''

         raise NotImplementedError()








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_( )       ->		Any:
    _lowercase			:				str 						=						10
    _lowercase			:				List[str] 						=						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'					),
        }					)
    _lowercase			:				Union[str, Any] 						=						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 							UpperCamelCase_( lowerCamelCase_				,					lowerCamelCase_					)       ->		int:
    _lowercase			:				int 						=						str(tmp_path_factory.mktemp('data'					) / 'file.arrow'					)
    dataset.map(cache_file_name=lowerCamelCase_					)
    return filename


# FILE_CONTENT + files


SCREAMING_SNAKE_CASE			: str				   =					"\\n    Text data.\n    Second line of data."



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



@pytest.fixture(scope='session'					)
def 							UpperCamelCase_( lowerCamelCase_					)       ->		Tuple:
    import bza

    _lowercase			:				Any 						=						tmp_path_factory.mktemp('data'					) / 'file.txt.bz2'
    _lowercase			:				Optional[Any] 						=						bytes(lowerCamelCase_				,					'utf-8'					)
    with bza.open(lowerCamelCase_				,					'wb'					) as f:
        f.write(lowerCamelCase_					)
    return path



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

    _lowercase			:				Optional[int] 						=						str(tmp_path_factory.mktemp('data'					) / 'file.txt.gz'					)
    _lowercase			:				Optional[int] 						=						bytes(lowerCamelCase_				,					'utf-8'					)
    with gzip.open(lowerCamelCase_				,					'wb'					) as f:
        f.write(lowerCamelCase_					)
    return path



@pytest.fixture(scope='session'					)
def 							UpperCamelCase_( lowerCamelCase_					)       ->		str:
    if datasets.config.LZ4_AVAILABLE:
        import lza.frame

        _lowercase			:				Any 						=						tmp_path_factory.mktemp('data'					) / 'file.txt.lz4'
        _lowercase			:				Optional[Any] 						=						bytes(lowerCamelCase_				,					'utf-8'					)
        with lza.frame.open(lowerCamelCase_				,					'wb'					) as f:
            f.write(lowerCamelCase_					)
        return path



@pytest.fixture(scope='session'					)
def 							UpperCamelCase_( lowerCamelCase_				,					lowerCamelCase_					)       ->		str:
    if datasets.config.PY7ZR_AVAILABLE:
        import pyazr

        _lowercase			:				int 						=						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 							UpperCamelCase_( lowerCamelCase_				,					lowerCamelCase_					)       ->		List[str]:
    import tarfile

    _lowercase			:				Optional[Any] 						=						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 							UpperCamelCase_( lowerCamelCase_					)       ->		str:
    import lzma

    _lowercase			:				Optional[Any] 						=						tmp_path_factory.mktemp('data'					) / 'file.txt.xz'
    _lowercase			:				int 						=						bytes(lowerCamelCase_				,					'utf-8'					)
    with lzma.open(lowerCamelCase_				,					'wb'					) as f:
        f.write(lowerCamelCase_					)
    return path



@pytest.fixture(scope='session'					)
def 							UpperCamelCase_( lowerCamelCase_				,					lowerCamelCase_					)       ->		str:
    import zipfile

    _lowercase			:				Dict 						=						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 							UpperCamelCase_( lowerCamelCase_					)       ->		Optional[Any]:
    if datasets.config.ZSTANDARD_AVAILABLE:
        import zstandard as zstd

        _lowercase			:				Optional[Any] 						=						tmp_path_factory.mktemp('data'					) / 'file.txt.zst'
        _lowercase			:				Dict 						=						bytes(lowerCamelCase_				,					'utf-8'					)
        with zstd.open(lowerCamelCase_				,					'wb'					) as f:
            f.write(lowerCamelCase_					)
        return path



@pytest.fixture(scope='session'					)
def 							UpperCamelCase_( lowerCamelCase_					)       ->		str:
    _lowercase			:				Union[str, Any] 						=						tmp_path_factory.mktemp('data'					) / 'file.xml'
    _lowercase			:				Optional[Any] 						=						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


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

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

SCREAMING_SNAKE_CASE			: 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_( )       ->		List[str]:
    return DATA_DICT_OF_LISTS



@pytest.fixture(scope='session'					)
def 							UpperCamelCase_( lowerCamelCase_					)       ->		Dict:
    _lowercase			:				Optional[int] 						=						datasets.Dataset.from_dict(lowerCamelCase_					)
    _lowercase			:				List[Any] 						=						str(tmp_path_factory.mktemp('data'					) / 'dataset.arrow'					)
    dataset.map(cache_file_name=lowerCamelCase_					)
    return path



@pytest.fixture(scope='session'					)
def 							UpperCamelCase_( lowerCamelCase_					)       ->		str:
    _lowercase			:				List[str] 						=						str(tmp_path_factory.mktemp('data'					) / 'dataset.sqlite'					)
    with contextlib.closing(sqlitea.connect(lowerCamelCase_					)					) as con:
        _lowercase			:				Union[str, Any] 						=						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_( lowerCamelCase_					)       ->		Dict:
    _lowercase			:				List[str] 						=						str(tmp_path_factory.mktemp('data'					) / 'dataset.csv'					)
    with open(lowerCamelCase_				,					'w'				,					newline=''					) as f:
        _lowercase			:				Tuple 						=						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 							UpperCamelCase_( lowerCamelCase_					)       ->		List[Any]:
    _lowercase			:				Tuple 						=						str(tmp_path_factory.mktemp('data'					) / 'dataset2.csv'					)
    with open(lowerCamelCase_				,					'w'				,					newline=''					) as f:
        _lowercase			:				str 						=						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 							UpperCamelCase_( lowerCamelCase_				,					lowerCamelCase_					)       ->		Any:
    import bza

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



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



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

    _lowercase			:				Tuple 						=						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 							UpperCamelCase_( lowerCamelCase_				,					lowerCamelCase_					)       ->		Dict:
    import gzip

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



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



@pytest.fixture(scope='session'					)
def 							UpperCamelCase_( lowerCamelCase_				,					lowerCamelCase_					)       ->		Any:
    _lowercase			:				Dict 						=						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 							UpperCamelCase_( lowerCamelCase_					)       ->		Optional[Any]:
    _lowercase			:				str 						=						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


