




'''simple docstring'''





import gc
import random
import unittest

import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer

import diffusers
from diffusers import (
    AutoencoderKL,
    EulerDiscreteScheduler,
    StableDiffusionLatentUpscalePipeline,
    StableDiffusionPipeline,
    UNetaDConditionModel,
)
from diffusers.schedulers import KarrasDiffusionSchedulers
from diffusers.utils import floats_tensor, load_image, load_numpy, slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu

from ..pipeline_params import TEXT_GUIDED_IMAGE_VARIATION_BATCH_PARAMS, TEXT_GUIDED_IMAGE_VARIATION_PARAMS
from ..test_pipelines_common import PipelineKarrasSchedulerTesterMixin, PipelineLatentTesterMixin, PipelineTesterMixin


enable_full_determinism()



def      __lowerCAmelCase			(					UpperCamelCase      )     ->	Tuple:
  lowerCAmelCase__				:  str		       =     [tensor.shape for tensor in tensor_list]
  return all(shape == shapes[0] for shape in shapes[1:]      )






class  _lowerCAmelCase     (  _lowercase    ,			_lowercase    ,			_lowercase    ,			unittest.TestCase	):
      A__		     =		StableDiffusionLatentUpscalePipeline
      A__		     =		TEXT_GUIDED_IMAGE_VARIATION_PARAMS - {
          'height',
          'width',
          'cross_attention_kwargs',
          'negative_prompt_embeds',
          'prompt_embeds',
      }
      A__		     =		PipelineTesterMixin.required_optional_params - {'num_images_per_prompt'}
      A__		     =		TEXT_GUIDED_IMAGE_VARIATION_BATCH_PARAMS
      A__		     =		frozenset(
          []	)  # TO-DO: update image_params once pipeline is refactored with VaeImageProcessor.preprocess
      A__		     =		frozenset([]	)

      A__		     =		True

      @property
      def 	__magic_name__(   self		):
        lowerCAmelCase__				:  List[str]		       =     1
        lowerCAmelCase__				:  Any		       =     4
        lowerCAmelCase__				:  Optional[int]		       =     (16, 16)

        lowerCAmelCase__				:  Union[str, Any]		       =     floats_tensor((batch_size, num_channels) + sizes      ,				rng=random.Random(0		)		).to(__UpperCAmelCase		)
        return image

      def 	__magic_name__(   self		):
        torch.manual_seed(0		)
        lowerCAmelCase__				:  List[str]		       =     UNetaDConditionModel(
            act_fn='''gelu'''      ,				attention_head_dim=8      ,				norm_num_groups=__UpperCAmelCase      ,				block_out_channels=[32, 32, 64, 64]      ,				time_cond_proj_dim=160      ,				conv_in_kernel=1      ,				conv_out_kernel=1      ,				cross_attention_dim=32      ,				down_block_types=(
                '''KDownBlock2D''',
                '''KCrossAttnDownBlock2D''',
                '''KCrossAttnDownBlock2D''',
                '''KCrossAttnDownBlock2D''',
            )      ,				in_channels=8      ,				mid_block_type=__UpperCAmelCase      ,				only_cross_attention=__UpperCAmelCase      ,				out_channels=5      ,				resnet_time_scale_shift='''scale_shift'''      ,				time_embedding_type='''fourier'''      ,				timestep_post_act='''gelu'''      ,				up_block_types=('''KCrossAttnUpBlock2D''', '''KCrossAttnUpBlock2D''', '''KCrossAttnUpBlock2D''', '''KUpBlock2D''')      ,				)
        lowerCAmelCase__				:  Any		       =     AutoencoderKL(
            block_out_channels=[32, 32, 64, 64]      ,				in_channels=3      ,				out_channels=3      ,				down_block_types=[
                '''DownEncoderBlock2D''',
                '''DownEncoderBlock2D''',
                '''DownEncoderBlock2D''',
                '''DownEncoderBlock2D''',
            ]      ,				up_block_types=['''UpDecoderBlock2D''', '''UpDecoderBlock2D''', '''UpDecoderBlock2D''', '''UpDecoderBlock2D''']      ,				latent_channels=4      ,				)
        lowerCAmelCase__				:  Union[str, Any]		       =     EulerDiscreteScheduler(prediction_type='''sample'''		)
        lowerCAmelCase__				:  Optional[Any]		       =     CLIPTextConfig(
            bos_token_id=0      ,				eos_token_id=2      ,				hidden_size=32      ,				intermediate_size=37      ,				layer_norm_eps=1e-05      ,				num_attention_heads=4      ,				num_hidden_layers=5      ,				pad_token_id=1      ,				vocab_size=1000      ,				hidden_act='''quick_gelu'''      ,				projection_dim=512      ,				)
        lowerCAmelCase__				:  Dict		       =     CLIPTextModel(__UpperCAmelCase		)
        lowerCAmelCase__				:  List[Any]		       =     CLIPTokenizer.from_pretrained('''hf-internal-testing/tiny-random-clip'''		)

        lowerCAmelCase__				:  str		       =     {
            '''unet''': model.eval(),
            '''vae''': vae.eval(),
            '''scheduler''': scheduler,
            '''text_encoder''': text_encoder,
            '''tokenizer''': tokenizer,
        }

        return components

      def 	__magic_name__(   self      ,				__UpperCAmelCase      ,				__UpperCAmelCase=0		):
        if str(__UpperCAmelCase		).startswith('''mps'''		):
          lowerCAmelCase__				:  Dict		       =     torch.manual_seed(__UpperCAmelCase		)
        else:
          lowerCAmelCase__				:  str		       =     torch.Generator(device=__UpperCAmelCase		).manual_seed(__UpperCAmelCase		)
        lowerCAmelCase__				:  Any		       =     {
            '''prompt''': '''A painting of a squirrel eating a burger''',
            '''image''': self.dummy_image.cpu(),
            '''generator''': generator,
            '''num_inference_steps''': 2,
            '''output_type''': '''numpy''',
        }
        return inputs

      def 	__magic_name__(   self		):
        lowerCAmelCase__				:  Any		       =     '''cpu'''

        lowerCAmelCase__				:  Any		       =     self.get_dummy_components()
        lowerCAmelCase__				:  Optional[int]		       =     self.pipeline_class(**__UpperCAmelCase		)
        pipe.to(__UpperCAmelCase		)
        pipe.set_progress_bar_config(disable=__UpperCAmelCase		)

        lowerCAmelCase__				:  Optional[Any]		       =     self.get_dummy_inputs(__UpperCAmelCase		)
        lowerCAmelCase__				:  Optional[int]		       =     pipe(**__UpperCAmelCase		).images
        lowerCAmelCase__				:  Dict		       =     image[0, -3:, -3:, -1]

        self.assertEqual(image.shape      ,				(1, 256, 256, 3)		)
        lowerCAmelCase__				:  Optional[Any]		       =     np.array(
            [0.47222412, 0.41921633, 0.44717434, 0.46874192, 0.42588258, 0.46150726, 0.4677534, 0.45583832, 0.48579055]		)
        lowerCAmelCase__				:  List[Any]		       =     np.abs(image_slice.flatten() - expected_slice		).max()
        self.assertLessEqual(__UpperCAmelCase      ,				1e-3		)

      def 	__magic_name__(   self		):
        super().test_attention_slicing_forward_pass(expected_max_diff=7e-3		)

      def 	__magic_name__(   self		):
        super().test_cpu_offload_forward_pass(expected_max_diff=3e-3		)

      def 	__magic_name__(   self		):
        super().test_dict_tuple_outputs_equivalent(expected_max_difference=3e-3		)

      def 	__magic_name__(   self		):
        super().test_inference_batch_single_identical(expected_max_diff=7e-3		)

      def 	__magic_name__(   self		):
        super().test_pt_np_pil_outputs_equivalent(expected_max_diff=3e-3		)

      def 	__magic_name__(   self		):
        super().test_save_load_local(expected_max_difference=3e-3		)

      def 	__magic_name__(   self		):
        super().test_save_load_optional_components(expected_max_difference=3e-3		)







      def 	__magic_name__(   self		):
        lowerCAmelCase__				:  str		       =     [
            '''DDIMScheduler''',
            '''DDPMScheduler''',
            '''PNDMScheduler''',
            '''HeunDiscreteScheduler''',
            '''EulerAncestralDiscreteScheduler''',
            '''KDPM2DiscreteScheduler''',
            '''KDPM2AncestralDiscreteScheduler''',
            '''DPMSolverSDEScheduler''',
        ]
        lowerCAmelCase__				:  int		       =     self.get_dummy_components()
        lowerCAmelCase__				:  List[Any]		       =     self.pipeline_class(**__UpperCAmelCase		)

        # make sure that PNDM does not need warm-up
        pipe.scheduler.register_to_config(skip_prk_steps=__UpperCAmelCase		)

        pipe.to(__UpperCAmelCase		)
        pipe.set_progress_bar_config(disable=__UpperCAmelCase		)
        lowerCAmelCase__				:  Any		       =     self.get_dummy_inputs(__UpperCAmelCase		)
        lowerCAmelCase__				:  Union[str, Any]		       =     2

        lowerCAmelCase__				:  int		       =     []
        for scheduler_enum in KarrasDiffusionSchedulers:
          if scheduler_enum.name in skip_schedulers:
            # no sigma schedulers are not supported
            # no schedulers
            continue

          lowerCAmelCase__				:  List[str]		       =     getattr(__UpperCAmelCase      ,				scheduler_enum.name		)
          lowerCAmelCase__				:  List[Any]		       =     scheduler_cls.from_config(pipe.scheduler.config		)
          lowerCAmelCase__				:  str		       =     pipe(**__UpperCAmelCase		)[0]
          outputs.append(__UpperCAmelCase		)

        assert check_same_shape(__UpperCAmelCase		)






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

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

      def 	__magic_name__(   self		):
        lowerCAmelCase__				:  Dict		       =     torch.manual_seed(33		)

        lowerCAmelCase__				:  str		       =     StableDiffusionPipeline.from_pretrained('''CompVis/stable-diffusion-v1-4'''      ,				torch_dtype=torch.floataa		)
        pipe.to('''cuda'''		)

        lowerCAmelCase__				:  Any		       =     StableDiffusionLatentUpscalePipeline.from_pretrained(
            '''stabilityai/sd-x2-latent-upscaler'''      ,				torch_dtype=torch.floataa		)
        upscaler.to('''cuda'''		)

        lowerCAmelCase__				:  Union[str, Any]		       =     '''a photo of an astronaut high resolution, unreal engine, ultra realistic'''

        lowerCAmelCase__				:  int		       =     pipe(__UpperCAmelCase      ,				generator=__UpperCAmelCase      ,				output_type='''latent'''		).images

        lowerCAmelCase__				:  List[str]		       =     upscaler(
            prompt=__UpperCAmelCase      ,				image=__UpperCAmelCase      ,				num_inference_steps=20      ,				guidance_scale=0      ,				generator=__UpperCAmelCase      ,				output_type='''np'''      ,				).images[0]

        lowerCAmelCase__				:  Optional[int]		       =     load_numpy(
            '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/latent-upscaler/astronaut_1024.npy'''		)
        assert np.abs((expected_image - image).mean()		) < 5e-2







      def 	__magic_name__(   self		):
        lowerCAmelCase__				:  Any		       =     torch.manual_seed(33		)

        lowerCAmelCase__				:  Any		       =     StableDiffusionLatentUpscalePipeline.from_pretrained(
            '''stabilityai/sd-x2-latent-upscaler'''      ,				torch_dtype=torch.floataa		)
        upscaler.to('''cuda'''		)

        lowerCAmelCase__				:  List[str]		       =     '''the temple of fire by Ross Tran and Gerardo Dottori, oil on canvas'''

        lowerCAmelCase__				:  Union[str, Any]		       =     load_image(
            '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/latent-upscaler/fire_temple_512.png'''		)

        lowerCAmelCase__				:  Any		       =     upscaler(
            prompt=__UpperCAmelCase      ,				image=__UpperCAmelCase      ,				num_inference_steps=20      ,				guidance_scale=0      ,				generator=__UpperCAmelCase      ,				output_type='''np'''      ,				).images[0]

        lowerCAmelCase__				:  List[str]		       =     load_numpy(
            '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/latent-upscaler/fire_temple_1024.npy'''		)
        assert np.abs((expected_image - image).max()		) < 5e-2







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

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

import datasets
import datasets.config



@pytest.fixture(scope='''session'''      )
def      __lowerCAmelCase			(					)     ->	Optional[Any]:
  lowerCAmelCase__				:  List[str]		       =     10
  lowerCAmelCase__				:  Optional[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'''      ),
      }      )
  lowerCAmelCase__				:  List[Any]		       =     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      __lowerCAmelCase			(					UpperCamelCase	,      UpperCamelCase      )     ->	List[Any]:
  lowerCAmelCase__				:  str		       =     str(tmp_path_factory.mktemp('''data'''      ) / '''file.arrow'''      )
  dataset.map(cache_file_name=UpperCamelCase      )
  return filename


# FILE_CONTENT + files


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



@pytest.fixture(scope='''session'''      )
def      __lowerCAmelCase			(					UpperCamelCase      )     ->	Optional[int]:
  lowerCAmelCase__				:  Union[str, Any]		       =     tmp_path_factory.mktemp('''data'''      ) / '''file.txt'''
  lowerCAmelCase__				:  int		       =     FILE_CONTENT
  with open(UpperCamelCase	,      '''w'''      ) as f:
    f.write(UpperCamelCase      )
  return filename



@pytest.fixture(scope='''session'''      )
def      __lowerCAmelCase			(					UpperCamelCase      )     ->	Optional[Any]:
  import bza

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



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

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



@pytest.fixture(scope='''session'''      )
def      __lowerCAmelCase			(					UpperCamelCase      )     ->	Tuple:
  if datasets.config.LZ4_AVAILABLE:
    import lza.frame

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



@pytest.fixture(scope='''session'''      )
def      __lowerCAmelCase			(					UpperCamelCase	,      UpperCamelCase      )     ->	Optional[Any]:
  if datasets.config.PY7ZR_AVAILABLE:
    import pyazr

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



@pytest.fixture(scope='''session'''      )
def      __lowerCAmelCase			(					UpperCamelCase	,      UpperCamelCase      )     ->	Union[str, Any]:
  import tarfile

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



@pytest.fixture(scope='''session'''      )
def      __lowerCAmelCase			(					UpperCamelCase      )     ->	Optional[int]:
  import lzma

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



@pytest.fixture(scope='''session'''      )
def      __lowerCAmelCase			(					UpperCamelCase	,      UpperCamelCase      )     ->	Any:
  import zipfile

  lowerCAmelCase__				:  Optional[int]		       =     tmp_path_factory.mktemp('''data'''      ) / '''file.txt.zip'''
  with zipfile.ZipFile(UpperCamelCase	,      '''w'''      ) as f:
    f.write(UpperCamelCase	,      arcname=os.path.basename(UpperCamelCase      )      )
  return path



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

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



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


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

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

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



@pytest.fixture(scope='''session'''      )
def      __lowerCAmelCase			(					)     ->	Tuple:
  return DATA_DICT_OF_LISTS



@pytest.fixture(scope='''session'''      )
def      __lowerCAmelCase			(					UpperCamelCase      )     ->	Any:
  lowerCAmelCase__				:  str		       =     datasets.Dataset.from_dict(UpperCamelCase      )
  lowerCAmelCase__				:  List[str]		       =     str(tmp_path_factory.mktemp('''data'''      ) / '''dataset.arrow'''      )
  dataset.map(cache_file_name=UpperCamelCase      )
  return path



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



@pytest.fixture(scope='''session'''      )
def      __lowerCAmelCase			(					UpperCamelCase      )     ->	int:
  lowerCAmelCase__				:  List[str]		       =     str(tmp_path_factory.mktemp('''data'''      ) / '''dataset.csv'''      )
  with open(UpperCamelCase	,      '''w'''	,      newline=''''''      ) as f:
    lowerCAmelCase__				:  List[str]		       =     csv.DictWriter(UpperCamelCase	,      fieldnames=['''col_1''', '''col_2''', '''col_3''']      )
    writer.writeheader()
    for item in DATA:
      writer.writerow(UpperCamelCase      )
  return path



@pytest.fixture(scope='''session'''      )
def      __lowerCAmelCase			(					UpperCamelCase      )     ->	List[Any]:
  lowerCAmelCase__				:  Dict		       =     str(tmp_path_factory.mktemp('''data'''      ) / '''dataset2.csv'''      )
  with open(UpperCamelCase	,      '''w'''	,      newline=''''''      ) as f:
    lowerCAmelCase__				:  Tuple		       =     csv.DictWriter(UpperCamelCase	,      fieldnames=['''col_1''', '''col_2''', '''col_3''']      )
    writer.writeheader()
    for item in DATA:
      writer.writerow(UpperCamelCase      )
  return path



@pytest.fixture(scope='''session'''      )
def      __lowerCAmelCase			(					UpperCamelCase	,      UpperCamelCase      )     ->	List[str]:
  import bza

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



@pytest.fixture(scope='''session'''      )
def      __lowerCAmelCase			(					UpperCamelCase	,      UpperCamelCase	,      UpperCamelCase      )     ->	Tuple:
  lowerCAmelCase__				:  Optional[int]		       =     tmp_path_factory.mktemp('''data'''      ) / '''dataset.csv.zip'''
  with zipfile.ZipFile(UpperCamelCase	,      '''w'''      ) as f:
    f.write(UpperCamelCase	,      arcname=os.path.basename(UpperCamelCase      )      )
    f.write(UpperCamelCase	,      arcname=os.path.basename(UpperCamelCase      )      )
  return path



@pytest.fixture(scope='''session'''      )
def      __lowerCAmelCase			(					UpperCamelCase	,      UpperCamelCase	,      UpperCamelCase      )     ->	Tuple:
  lowerCAmelCase__				:  Union[str, Any]		       =     tmp_path_factory.mktemp('''data'''      ) / '''dataset.csv.zip'''
  with zipfile.ZipFile(UpperCamelCase	,      '''w'''      ) as f:
    f.write(UpperCamelCase	,      arcname=os.path.basename(csv_path.replace('''.csv'''	,      '''.CSV'''      )      )      )
    f.write(UpperCamelCase	,      arcname=os.path.basename(csva_path.replace('''.csv'''	,      '''.CSV'''      )      )      )
  return path



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



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



@pytest.fixture(scope='''session'''      )
def      __lowerCAmelCase			(					UpperCamelCase      )     ->	Dict:
  lowerCAmelCase__				:  List[Any]		       =     str(tmp_path_factory.mktemp('''data'''      ) / '''dataset.json'''      )
  lowerCAmelCase__				:  List[str]		       =     {'''data''': DATA}
  with open(UpperCamelCase	,      '''w'''      ) as f:
    json.dump(UpperCamelCase	,      UpperCamelCase      )
  return path



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



@pytest.fixture(scope='''session'''      )
def      __lowerCAmelCase			(					UpperCamelCase      )     ->	int:
  lowerCAmelCase__				:  Union[str, Any]		       =     str(tmp_path_factory.mktemp('''data'''      ) / '''dataset.jsonl'''      )
  with open(UpperCamelCase	,      '''w'''      ) as f:
    for item in DATA:
      f.write(json.dumps(UpperCamelCase      ) + '''\n'''      )
  return path



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



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



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



@pytest.fixture(scope='''session'''      )
def      __lowerCAmelCase			(					UpperCamelCase	,      UpperCamelCase      )     ->	int:
  import gzip

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



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

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



@pytest.fixture(scope='''session'''      )
def      __lowerCAmelCase			(					UpperCamelCase	,      UpperCamelCase	,      UpperCamelCase      )     ->	Union[str, Any]:
  lowerCAmelCase__				:  str		       =     tmp_path_factory.mktemp('''data'''      ) / '''dataset.jsonl.zip'''
  with zipfile.ZipFile(UpperCamelCase	,      '''w'''      ) as f:
    f.write(UpperCamelCase	,      arcname=os.path.basename(UpperCamelCase      )      )
    f.write(UpperCamelCase	,      arcname=os.path.basename(UpperCamelCase      )      )
  return path



@pytest.fixture(scope='''session'''      )
def      __lowerCAmelCase			(					UpperCamelCase	,      UpperCamelCase	,      UpperCamelCase	,      UpperCamelCase      )     ->	Optional[int]:
  lowerCAmelCase__				:  List[Any]		       =     tmp_path_factory.mktemp('''data'''      ) / '''dataset_nested.jsonl.zip'''
  with zipfile.ZipFile(UpperCamelCase	,      '''w'''      ) as f:
    f.write(UpperCamelCase	,      arcname=os.path.join('''nested'''	,      os.path.basename(UpperCamelCase      )      )      )
  return path



@pytest.fixture(scope='''session'''      )
def      __lowerCAmelCase			(					UpperCamelCase	,      UpperCamelCase	,      UpperCamelCase      )     ->	Optional[Any]:
  lowerCAmelCase__				:  Tuple		       =     tmp_path_factory.mktemp('''data'''      ) / '''dataset_with_dir.jsonl.zip'''
  with zipfile.ZipFile(UpperCamelCase	,      '''w'''      ) as f:
    f.write(UpperCamelCase	,      arcname=os.path.join('''main_dir'''	,      os.path.basename(UpperCamelCase      )      )      )
    f.write(UpperCamelCase	,      arcname=os.path.join('''main_dir'''	,      os.path.basename(UpperCamelCase      )      )      )
  return path



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



@pytest.fixture(scope='''session'''      )
def      __lowerCAmelCase			(					UpperCamelCase	,      UpperCamelCase	,      UpperCamelCase	,      UpperCamelCase      )     ->	Optional[int]:
  lowerCAmelCase__				:  Union[str, Any]		       =     tmp_path_factory.mktemp('''data'''      ) / '''dataset_nested.jsonl.tar'''
  with tarfile.TarFile(UpperCamelCase	,      '''w'''      ) as f:
    f.add(UpperCamelCase	,      arcname=os.path.join('''nested'''	,      os.path.basename(UpperCamelCase      )      )      )
  return path



@pytest.fixture(scope='''session'''      )
def      __lowerCAmelCase			(					UpperCamelCase      )     ->	Optional[Any]:
  lowerCAmelCase__				:  Dict		       =     ['''0''', '''1''', '''2''', '''3''']
  lowerCAmelCase__				:  Any		       =     str(tmp_path_factory.mktemp('''data'''      ) / '''dataset.txt'''      )
  with open(UpperCamelCase	,      '''w'''      ) as f:
    for item in data:
      f.write(item + '''\n'''      )
  return path



@pytest.fixture(scope='''session'''      )
def      __lowerCAmelCase			(					UpperCamelCase      )     ->	Any:
  lowerCAmelCase__				:  int		       =     ['''0''', '''1''', '''2''', '''3''']
  lowerCAmelCase__				:  int		       =     str(tmp_path_factory.mktemp('''data'''      ) / '''dataset2.txt'''      )
  with open(UpperCamelCase	,      '''w'''      ) as f:
    for item in data:
      f.write(item + '''\n'''      )
  return path



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



@pytest.fixture(scope='''session'''      )
def      __lowerCAmelCase			(					UpperCamelCase	,      UpperCamelCase	,      UpperCamelCase      )     ->	Any:
  lowerCAmelCase__				:  Optional[int]		       =     tmp_path_factory.mktemp('''data'''      ) / '''dataset.text.zip'''
  with zipfile.ZipFile(UpperCamelCase	,      '''w'''      ) as f:
    f.write(UpperCamelCase	,      arcname=os.path.basename(UpperCamelCase      )      )
    f.write(UpperCamelCase	,      arcname=os.path.basename(UpperCamelCase      )      )
  return path



@pytest.fixture(scope='''session'''      )
def      __lowerCAmelCase			(					UpperCamelCase	,      UpperCamelCase	,      UpperCamelCase      )     ->	Union[str, Any]:
  lowerCAmelCase__				:  Any		       =     tmp_path_factory.mktemp('''data'''      ) / '''dataset_with_dir.text.zip'''
  with zipfile.ZipFile(UpperCamelCase	,      '''w'''      ) as f:
    f.write(UpperCamelCase	,      arcname=os.path.join('''main_dir'''	,      os.path.basename(UpperCamelCase      )      )      )
    f.write(UpperCamelCase	,      arcname=os.path.join('''main_dir'''	,      os.path.basename(UpperCamelCase      )      )      )
  return path



@pytest.fixture(scope='''session'''      )
def      __lowerCAmelCase			(					UpperCamelCase	,      UpperCamelCase	,      UpperCamelCase      )     ->	int:
  lowerCAmelCase__				:  str		       =     tmp_path_factory.mktemp('''data'''      ) / '''dataset.ext.zip'''
  with zipfile.ZipFile(UpperCamelCase	,      '''w'''      ) as f:
    f.write(UpperCamelCase	,      arcname=os.path.basename('''unsupported.ext'''      )      )
    f.write(UpperCamelCase	,      arcname=os.path.basename('''unsupported_2.ext'''      )      )
  return path



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



@pytest.fixture(scope='''session'''      )
def      __lowerCAmelCase			(					)     ->	Optional[int]:
  return os.path.join('''tests'''	,      '''features'''	,      '''data'''	,      '''test_image_rgb.jpg'''      )



@pytest.fixture(scope='''session'''      )
def      __lowerCAmelCase			(					)     ->	Optional[Any]:
  return os.path.join('''tests'''	,      '''features'''	,      '''data'''	,      '''test_audio_44100.wav'''      )



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



@pytest.fixture(scope='''session'''      )
def      __lowerCAmelCase			(					UpperCamelCase      )     ->	Dict:
  lowerCAmelCase__				:  Optional[Any]		       =     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

