
'''simple docstring'''





import gc
import unittest

import numpy as np
import torch

from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu

from ..pipeline_params import (
    CLASS_CONDITIONED_IMAGE_GENERATION_BATCH_PARAMS,
    CLASS_CONDITIONED_IMAGE_GENERATION_PARAMS,
)
from ..test_pipelines_common import PipelineTesterMixin


enable_full_determinism()

class 						a   (				__magic_name__				,unittest.TestCase    ):
				_snake_case		    = DiTPipeline
				_snake_case		    = CLASS_CONDITIONED_IMAGE_GENERATION_PARAMS
				_snake_case		    = PipelineTesterMixin.required_optional_params - {
				    '''latents''',
				    '''num_images_per_prompt''',
				    '''callback''',
				    '''callback_steps''',
				}
				_snake_case		    = CLASS_CONDITIONED_IMAGE_GENERATION_BATCH_PARAMS
				_snake_case		    = False




				def 	__snake_case							(							self	:				List[Any]      ):
										torch.manual_seed(0      )
										snake_case       :     int =    TransformeraDModel(
										    sample_size=16,    num_layers=2,    patch_size=4,    attention_head_dim=8,    num_attention_heads=2,    in_channels=4,    out_channels=8,    attention_bias=SCREAMING_SNAKE_CASE_,    activation_fn='''gelu-approximate''',    num_embeds_ada_norm=10_00,    norm_type='''ada_norm_zero''',    norm_elementwise_affine=SCREAMING_SNAKE_CASE_,    )
										snake_case       :     Optional[int] =    AutoencoderKL()
										snake_case       :     List[str] =    DDIMScheduler()
										snake_case       :     Union[str, Any] =    {'''transformer''': transformer.eval(), '''vae''': vae.eval(), '''scheduler''': scheduler}
										return components




				def 	__snake_case							(							self	:				Dict,    SCREAMING_SNAKE_CASE_	:				Optional[Any],    SCREAMING_SNAKE_CASE_	:				Dict=0      ):
										if str(SCREAMING_SNAKE_CASE_      ).startswith('''mps'''      ):
																snake_case       :     List[Any] =    torch.manual_seed(SCREAMING_SNAKE_CASE_      )
										else:
																snake_case       :     Dict =    torch.Generator(device=SCREAMING_SNAKE_CASE_      ).manual_seed(SCREAMING_SNAKE_CASE_      )
										snake_case       :     Optional[Any] =    {
										    '''class_labels''': [1],
										    '''generator''': generator,
										    '''num_inference_steps''': 2,
										    '''output_type''': '''numpy''',
										}
										return inputs




				def 	__snake_case							(							self	:				Optional[Any]      ):
										snake_case       :     Optional[int] =    '''cpu'''

										snake_case       :     Dict =    self.get_dummy_components()
										snake_case       :     Any =    self.pipeline_class(**SCREAMING_SNAKE_CASE_      )
										pipe.to(SCREAMING_SNAKE_CASE_      )
										pipe.set_progress_bar_config(disable=SCREAMING_SNAKE_CASE_      )

										snake_case       :     Optional[int] =    self.get_dummy_inputs(SCREAMING_SNAKE_CASE_      )
										snake_case       :     int =    pipe(**SCREAMING_SNAKE_CASE_      ).images
										snake_case       :     List[Any] =    image[0, -3:, -3:, -1]

										self.assertEqual(image.shape,    (1, 16, 16, 3)      )
										snake_case       :     List[str] =    np.array([0.2946, 0.6601, 0.4329, 0.3296, 0.4144, 0.5319, 0.7273, 0.5013, 0.4457]      )
										snake_case       :     Dict =    np.abs(image_slice.flatten() - expected_slice      ).max()
										self.assertLessEqual(SCREAMING_SNAKE_CASE_,    1e-3      )




				def 	__snake_case							(							self	:				List[Any]      ):
										self._test_inference_batch_single_identical(relax_max_difference=SCREAMING_SNAKE_CASE_,    expected_max_diff=1e-3      )




				@unittest.skipIf(
				    torch_device != '''cuda''' or not is_xformers_available(),    reason='''XFormers attention is only available with CUDA and `xformers` installed''',    )
				def 	__snake_case							(							self	:				Optional[Any]      ):
										self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1e-3      )




@require_torch_gpu
@slow
class 						a   (				unittest.TestCase    ):




				def 	__snake_case							(							self	:				Dict      ):
										super().tearDown()
										gc.collect()
										torch.cuda.empty_cache()




				def 	__snake_case							(							self	:				Tuple      ):
										snake_case       :     Dict =    torch.manual_seed(0      )

										snake_case       :     str =    DiTPipeline.from_pretrained('''facebook/DiT-XL-2-256'''      )
										pipe.to('''cuda'''      )

										snake_case       :     Dict =    ['''vase''', '''umbrella''', '''white shark''', '''white wolf''']
										snake_case       :     Any =    pipe.get_label_ids(SCREAMING_SNAKE_CASE_      )

										snake_case       :     str =    pipe(SCREAMING_SNAKE_CASE_,    generator=SCREAMING_SNAKE_CASE_,    num_inference_steps=40,    output_type='''np'''      ).images

										for word, image in zip(SCREAMING_SNAKE_CASE_,    SCREAMING_SNAKE_CASE_      ):
																snake_case       :     List[Any] =    load_numpy(
																    F"""https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/dit/{word}.npy"""      )
																assert np.abs((expected_image - image).max()      ) < 1e-2




				def 	__snake_case							(							self	:				int      ):
										snake_case       :     Optional[int] =    DiTPipeline.from_pretrained('''facebook/DiT-XL-2-512'''      )
										snake_case       :     Tuple =    DPMSolverMultistepScheduler.from_config(pipe.scheduler.config      )
										pipe.to('''cuda'''      )

										snake_case       :     Any =    ['''vase''', '''umbrella''']
										snake_case       :     List[str] =    pipe.get_label_ids(SCREAMING_SNAKE_CASE_      )

										snake_case       :     List[str] =    torch.manual_seed(0      )
										snake_case       :     int =    pipe(SCREAMING_SNAKE_CASE_,    generator=SCREAMING_SNAKE_CASE_,    num_inference_steps=25,    output_type='''np'''      ).images

										for word, image in zip(SCREAMING_SNAKE_CASE_,    SCREAMING_SNAKE_CASE_      ):
																snake_case       :     List[Any] =    load_numpy(
																    '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'''
																    F"""/dit/{word}_512.npy"""      )

																assert np.abs((expected_image - image).max()      ) < 1e-1



'''simple docstring'''





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

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

import datasets
import datasets.config

@pytest.fixture(scope='''session'''       )
def      A (       ):
						snake_case       :     Dict =    10
						snake_case       :     List[Any] =    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'''       ),
						    }       )
						snake_case       :     Dict =    datasets.Dataset.from_dict(
						    {
						        '''tokens''': [['''foo'''] * 5] * n,
						        '''labels''': [[1] * 5] * n,
						        '''answers''': [{'''answer_start''': [97], '''text''': ['''1976''']}] * 10,
						        '''id''': list(range(A_       )       ),
						    }    ,							features=A_    ,							)
						return dataset

@pytest.fixture(scope='''session'''       )
def      A (       A_							:					List[Any]    ,							A_							:					Optional[Any]       ):
						snake_case       :     Any =    str(tmp_path_factory.mktemp('''data'''       ) / '''file.arrow'''       )
						dataset.map(cache_file_name=A_       )
						return filename


# FILE_CONTENT + files


UpperCAmelCase    					=   "\\n    Text data.\n    Second line of data."

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

@pytest.fixture(scope='''session'''       )
def      A (       A_							:					Optional[Any]       ):
						import bza

						snake_case       :     Tuple =    tmp_path_factory.mktemp('''data'''       ) / '''file.txt.bz2'''
						snake_case       :     Union[str, Any] =    bytes(A_    ,							'''utf-8'''       )
						with bza.open(A_    ,							'''wb'''       ) as f:
												f.write(A_       )
						return path

@pytest.fixture(scope='''session'''       )
def      A (       A_							:					List[Any]       ):
						import gzip

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

@pytest.fixture(scope='''session'''       )
def      A (       A_							:					Optional[int]       ):
						if datasets.config.LZ4_AVAILABLE:
												import lza.frame

												snake_case       :     Union[str, Any] =    tmp_path_factory.mktemp('''data'''       ) / '''file.txt.lz4'''
												snake_case       :     Tuple =    bytes(A_    ,							'''utf-8'''       )
												with lza.frame.open(A_    ,							'''wb'''       ) as f:
																		f.write(A_       )
												return path

@pytest.fixture(scope='''session'''       )
def      A (       A_							:					Union[str, Any]    ,							A_							:					str       ):
						if datasets.config.PY7ZR_AVAILABLE:
												import pyazr

												snake_case       :     Optional[Any] =    tmp_path_factory.mktemp('''data'''       ) / '''file.txt.7z'''
												with pyazr.SevenZipFile(A_    ,							'''w'''       ) as archive:
																		archive.write(A_    ,							arcname=os.path.basename(A_       )       )
												return path

@pytest.fixture(scope='''session'''       )
def      A (       A_							:					List[str]    ,							A_							:					Optional[int]       ):
						import tarfile

						snake_case       :     Union[str, Any] =    tmp_path_factory.mktemp('''data'''       ) / '''file.txt.tar'''
						with tarfile.TarFile(A_    ,							'''w'''       ) as f:
												f.add(A_    ,							arcname=os.path.basename(A_       )       )
						return path

@pytest.fixture(scope='''session'''       )
def      A (       A_							:					Any       ):
						import lzma

						snake_case       :     Any =    tmp_path_factory.mktemp('''data'''       ) / '''file.txt.xz'''
						snake_case       :     Union[str, Any] =    bytes(A_    ,							'''utf-8'''       )
						with lzma.open(A_    ,							'''wb'''       ) as f:
												f.write(A_       )
						return path

@pytest.fixture(scope='''session'''       )
def      A (       A_							:					Optional[int]    ,							A_							:					Union[str, Any]       ):
						import zipfile

						snake_case       :     List[str] =    tmp_path_factory.mktemp('''data'''       ) / '''file.txt.zip'''
						with zipfile.ZipFile(A_    ,							'''w'''       ) as f:
												f.write(A_    ,							arcname=os.path.basename(A_       )       )
						return path

@pytest.fixture(scope='''session'''       )
def      A (       A_							:					List[str]       ):
						if datasets.config.ZSTANDARD_AVAILABLE:
												import zstandard as zstd

												snake_case       :     Tuple =    tmp_path_factory.mktemp('''data'''       ) / '''file.txt.zst'''
												snake_case       :     List[str] =    bytes(A_    ,							'''utf-8'''       )
												with zstd.open(A_    ,							'''wb'''       ) as f:
																		f.write(A_       )
												return path

@pytest.fixture(scope='''session'''       )
def      A (       A_							:					str       ):
						snake_case       :     Optional[int] =    tmp_path_factory.mktemp('''data'''       ) / '''file.xml'''
						snake_case       :     Any =    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(A_    ,							'''w'''       ) as f:
												f.write(A_       )
						return filename


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

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

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

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

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

@pytest.fixture(scope='''session'''       )
def      A (       A_							:					str       ):
						snake_case       :     Optional[int] =    str(tmp_path_factory.mktemp('''data'''       ) / '''dataset.sqlite'''       )
						with contextlib.closing(sqlitea.connect(A_       )       ) as con:
												snake_case       :     Optional[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      A (       A_							:					List[str]       ):
						snake_case       :     Any =    str(tmp_path_factory.mktemp('''data'''       ) / '''dataset.csv'''       )
						with open(A_    ,							'''w'''    ,							newline=''''''       ) as f:
												snake_case       :     Optional[int] =    csv.DictWriter(A_    ,							fieldnames=['''col_1''', '''col_2''', '''col_3''']       )
												writer.writeheader()
												for item in DATA:
																		writer.writerow(A_       )
						return path

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

@pytest.fixture(scope='''session'''       )
def      A (       A_							:					Optional[Any]    ,							A_							:					Optional[int]       ):
						import bza

						snake_case       :     Optional[int] =    tmp_path_factory.mktemp('''data'''       ) / '''dataset.csv.bz2'''
						with open(A_    ,							'''rb'''       ) as f:
												snake_case       :     Any =    f.read()
						# data = bytes(FILE_CONTENT, "utf-8")
						with bza.open(A_    ,							'''wb'''       ) as f:
												f.write(A_       )
						return path

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

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

@pytest.fixture(scope='''session'''       )
def      A (       A_							:					Dict    ,							A_							:					Dict    ,							A_							:					Optional[int]       ):
						snake_case       :     Dict =    tmp_path_factory.mktemp('''data'''       ) / '''dataset_with_dir.csv.zip'''
						with zipfile.ZipFile(A_    ,							'''w'''       ) as f:
												f.write(A_    ,							arcname=os.path.join('''main_dir'''    ,							os.path.basename(A_       )       )       )
												f.write(A_    ,							arcname=os.path.join('''main_dir'''    ,							os.path.basename(A_       )       )       )
						return path

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

@pytest.fixture(scope='''session'''       )
def      A (       A_							:					List[str]       ):
						snake_case       :     Any =    str(tmp_path_factory.mktemp('''data'''       ) / '''dataset.json'''       )
						snake_case       :     Optional[int] =    {'''data''': DATA}
						with open(A_    ,							'''w'''       ) as f:
												json.dump(A_    ,							A_       )
						return path

@pytest.fixture(scope='''session'''       )
def      A (       A_							:					str       ):
						snake_case       :     List[str] =    str(tmp_path_factory.mktemp('''data'''       ) / '''dataset.json'''       )
						snake_case       :     Any =    {'''data''': DATA_DICT_OF_LISTS}
						with open(A_    ,							'''w'''       ) as f:
												json.dump(A_    ,							A_       )
						return path

@pytest.fixture(scope='''session'''       )
def      A (       A_							:					Optional[Any]       ):
						snake_case       :     Optional[Any] =    str(tmp_path_factory.mktemp('''data'''       ) / '''dataset.jsonl'''       )
						with open(A_    ,							'''w'''       ) as f:
												for item in DATA:
																		f.write(json.dumps(A_       ) + '''\n'''       )
						return path

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

@pytest.fixture(scope='''session'''       )
def      A (       A_							:					List[Any]       ):
						snake_case       :     Dict =    str(tmp_path_factory.mktemp('''data'''       ) / '''dataset_312.jsonl'''       )
						with open(A_    ,							'''w'''       ) as f:
												for item in DATA_312:
																		f.write(json.dumps(A_       ) + '''\n'''       )
						return path

@pytest.fixture(scope='''session'''       )
def      A (       A_							:					int       ):
						snake_case       :     Dict =    str(tmp_path_factory.mktemp('''data'''       ) / '''dataset-str.jsonl'''       )
						with open(A_    ,							'''w'''       ) as f:
												for item in DATA_STR:
																		f.write(json.dumps(A_       ) + '''\n'''       )
						return path

@pytest.fixture(scope='''session'''       )
def      A (       A_							:					Optional[int]    ,							A_							:					Optional[int]       ):
						import gzip

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

@pytest.fixture(scope='''session'''       )
def      A (       A_							:					Optional[int]    ,							A_							:					Any       ):
						import gzip

						snake_case       :     List[Any] =    str(tmp_path_factory.mktemp('''data'''       ) / '''dataset.jsonl.gz'''       )
						with open(A_    ,							'''rb'''       ) as orig_file:
												with gzip.open(A_    ,							'''wb'''       ) as zipped_file:
																		zipped_file.writelines(A_       )
						return path

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

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

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

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

@pytest.fixture(scope='''session'''       )
def      A (       A_							:					Tuple    ,							A_							:					Any    ,							A_							:					Tuple    ,							A_							:					Optional[Any]       ):
						snake_case       :     List[Any] =    tmp_path_factory.mktemp('''data'''       ) / '''dataset_nested.jsonl.tar'''
						with tarfile.TarFile(A_    ,							'''w'''       ) as f:
												f.add(A_    ,							arcname=os.path.join('''nested'''    ,							os.path.basename(A_       )       )       )
						return path

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

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

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

@pytest.fixture(scope='''session'''       )
def      A (       A_							:					Optional[Any]    ,							A_							:					Any    ,							A_							:					Union[str, Any]       ):
						snake_case       :     Dict =    tmp_path_factory.mktemp('''data'''       ) / '''dataset.text.zip'''
						with zipfile.ZipFile(A_    ,							'''w'''       ) as f:
												f.write(A_    ,							arcname=os.path.basename(A_       )       )
												f.write(A_    ,							arcname=os.path.basename(A_       )       )
						return path

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

@pytest.fixture(scope='''session'''       )
def      A (       A_							:					Any    ,							A_							:					Union[str, Any]    ,							A_							:					str       ):
						snake_case       :     List[Any] =    tmp_path_factory.mktemp('''data'''       ) / '''dataset.ext.zip'''
						with zipfile.ZipFile(A_    ,							'''w'''       ) as f:
												f.write(A_    ,							arcname=os.path.basename('''unsupported.ext'''       )       )
												f.write(A_    ,							arcname=os.path.basename('''unsupported_2.ext'''       )       )
						return path

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

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

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

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





@pytest.fixture(scope='''session'''       )
def      A (       A_							:					Optional[Any]       ):
						snake_case       :     Dict =    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

