



import gc
import random
import unittest

import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast

from diffusers import DDIMScheduler, KandinskyInpaintPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kandinsky.text_encoder import MCLIPConfig, MultilingualCLIP
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 ..test_pipelines_common import PipelineTesterMixin, assert_mean_pixel_difference


enable_full_determinism()



class     _UpperCAmelCase			(       _UpperCAmelCase			,      unittest.TestCase     ):
     UpperCamelCase__		    =				KandinskyInpaintPipeline
     UpperCamelCase__		    =				['''prompt''', '''image_embeds''', '''negative_image_embeds''', '''image''', '''mask_image''']
     UpperCamelCase__		    =				[
         '''prompt''',
         '''negative_prompt''',
         '''image_embeds''',
         '''negative_image_embeds''',
         '''image''',
         '''mask_image''',
     ]
     UpperCamelCase__		    =				[
         '''generator''',
         '''height''',
         '''width''',
         '''latents''',
         '''guidance_scale''',
         '''negative_prompt''',
         '''num_inference_steps''',
         '''return_dict''',
         '''guidance_scale''',
         '''num_images_per_prompt''',
         '''output_type''',
         '''return_dict''',
     ]
     UpperCamelCase__		    =				False




     @property
     def 		snake_case_		(				self):
         return 3_2




     @property
     def 		snake_case_		(				self):
         return 3_2




     @property
     def 		snake_case_		(				self):
         return self.time_input_dim




     @property
     def 		snake_case_		(				self):
         return self.time_input_dim * 4




     @property
     def 		snake_case_		(				self):
         return 1_0_0




     @property
     def 		snake_case_		(				self):
         A__		 =					XLMRobertaTokenizerFast.from_pretrained('''YiYiXu/tiny-random-mclip-base''')
         return tokenizer




     @property
     def 		snake_case_		(				self):
         torch.manual_seed(0)
         A__		 =					MCLIPConfig(
             numDims=self.cross_attention_dim ,						transformerDimensions=self.text_embedder_hidden_size ,						hidden_size=self.text_embedder_hidden_size ,						intermediate_size=3_7 ,						num_attention_heads=4 ,						num_hidden_layers=5 ,						vocab_size=1_0_0_5 ,						)

         A__		 =					MultilingualCLIP(lowercase_)
         A__		 =					text_encoder.eval()

         return text_encoder




     @property
     def 		snake_case_		(				self):
         torch.manual_seed(0)

         A__		 =					{
             """in_channels""": 9,
             # Out channels is double in channels because predicts mean and variance
             """out_channels""": 8,
             """addition_embed_type""": """text_image""",
             """down_block_types""": ("""ResnetDownsampleBlock2D""", """SimpleCrossAttnDownBlock2D"""),
             """up_block_types""": ("""SimpleCrossAttnUpBlock2D""", """ResnetUpsampleBlock2D"""),
             """mid_block_type""": """UNetMidBlock2DSimpleCrossAttn""",
             """block_out_channels""": (self.block_out_channels_a, self.block_out_channels_a * 2),
             """layers_per_block""": 1,
             """encoder_hid_dim""": self.text_embedder_hidden_size,
             """encoder_hid_dim_type""": """text_image_proj""",
             """cross_attention_dim""": self.cross_attention_dim,
             """attention_head_dim""": 4,
             """resnet_time_scale_shift""": """scale_shift""",
             """class_embed_type""": None,
         }

         A__		 =					UNetaDConditionModel(**lowercase_)
         return model




     @property
     def 		snake_case_		(				self):
         return {
             "block_out_channels": [3_2, 6_4],
             "down_block_types": ["DownEncoderBlock2D", "AttnDownEncoderBlock2D"],
             "in_channels": 3,
             "latent_channels": 4,
             "layers_per_block": 1,
             "norm_num_groups": 8,
             "norm_type": "spatial",
             "num_vq_embeddings": 1_2,
             "out_channels": 3,
             "up_block_types": [
                 "AttnUpDecoderBlock2D",
                 "UpDecoderBlock2D",
             ],
             "vq_embed_dim": 4,
         }




     @property
     def 		snake_case_		(				self):
         torch.manual_seed(0)
         A__		 =					VQModel(**self.dummy_movq_kwargs)
         return model




     def 		snake_case_		(				self):
         A__		 =					self.dummy_text_encoder
         A__		 =					self.dummy_tokenizer
         A__		 =					self.dummy_unet
         A__		 =					self.dummy_movq

         A__		 =					DDIMScheduler(
             num_train_timesteps=1_0_0_0 ,						beta_schedule='''linear''' ,						beta_start=0.0_0_0_8_5 ,						beta_end=0.0_1_2 ,						clip_sample=lowercase_ ,						set_alpha_to_one=lowercase_ ,						steps_offset=1 ,						prediction_type='''epsilon''' ,						thresholding=lowercase_ ,						)

         A__		 =					{
             """text_encoder""": text_encoder,
             """tokenizer""": tokenizer,
             """unet""": unet,
             """scheduler""": scheduler,
             """movq""": movq,
         }

         return components




     def 		snake_case_		(				self ,						a__ ,						a__=0):
         A__		 =					floats_tensor((1, self.cross_attention_dim) ,						rng=random.Random(lowercase_)).to(lowercase_)
         A__		 =					floats_tensor((1, self.cross_attention_dim) ,						rng=random.Random(seed + 1)).to(lowercase_)
         # create init_image
         A__		 =					floats_tensor((1, 3, 6_4, 6_4) ,						rng=random.Random(lowercase_)).to(lowercase_)
         A__		 =					image.cpu().permute(0 ,						2 ,						3 ,						1)[0]
         A__		 =					Image.fromarray(np.uinta(lowercase_)).convert('''RGB''').resize((2_5_6, 2_5_6))
         # create mask
         A__		 =					np.ones((6_4, 6_4) ,						dtype=np.floataa)
         A__		 =					0

         if str(lowercase_).startswith('''mps'''):
             A__		 =					torch.manual_seed(lowercase_)
         else:
             A__		 =					torch.Generator(device=lowercase_).manual_seed(lowercase_)
         A__		 =					{
             """prompt""": """horse""",
             """image""": init_image,
             """mask_image""": mask,
             """image_embeds""": image_embeds,
             """negative_image_embeds""": negative_image_embeds,
             """generator""": generator,
             """height""": 6_4,
             """width""": 6_4,
             """num_inference_steps""": 2,
             """guidance_scale""": 4.0,
             """output_type""": """np""",
         }
         return inputs




     def 		snake_case_		(				self):
         A__		 =					"""cpu"""

         A__		 =					self.get_dummy_components()

         A__		 =					self.pipeline_class(**lowercase_)
         A__		 =					pipe.to(lowercase_)

         pipe.set_progress_bar_config(disable=lowercase_)

         A__		 =					pipe(**self.get_dummy_inputs(lowercase_))
         A__		 =					output.images

         A__		 =					pipe(
             **self.get_dummy_inputs(lowercase_) ,						return_dict=lowercase_ ,						)[0]

         A__		 =					image[0, -3:, -3:, -1]
         A__		 =					image_from_tuple[0, -3:, -3:, -1]

         print(F"image.shape {image.shape}")

         assert image.shape == (1, 6_4, 6_4, 3)

         A__		 =					np.array(
             [0.8_3_2_6_9_1_9, 0.7_3_7_9_0_4_6_7, 0.2_0_9_1_8_5_8_1, 0.9_3_0_9_6_1_2, 0.5_5_1_1_7_9_1, 0.4_3_7_1_3_3_2_8, 0.5_5_1_3_3_2_1, 0.4_9_9_2_2_9_3_4, 0.5_9_4_9_7_7_8_6])

         assert (
             np.abs(image_slice.flatten() - expected_slice).max() < 1e-2
         ), F" expected_slice {expected_slice}, but got {image_slice.flatten()}"
         assert (
             np.abs(image_from_tuple_slice.flatten() - expected_slice).max() < 1e-2
         ), F" expected_slice {expected_slice}, but got {image_from_tuple_slice.flatten()}"




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







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




     def 		snake_case_		(				self):
         # clean up the VRAM after each test
         super().tearDown()
         gc.collect()
         torch.cuda.empty_cache()




     def 		snake_case_		(				self):
         A__		 =					load_numpy(
             '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'''
             '''/kandinsky/kandinsky_inpaint_cat_with_hat_fp16.npy''')

         A__		 =					load_image(
             '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main''' '''/kandinsky/cat.png''')
         A__		 =					np.ones((7_6_8, 7_6_8) ,						dtype=np.floataa)
         A__		 =					0

         A__		 =					"""a hat"""

         A__		 =					KandinskyPriorPipeline.from_pretrained(
             '''kandinsky-community/kandinsky-2-1-prior''' ,						torch_dtype=torch.floataa)
         pipe_prior.to(lowercase_)

         A__		 =					KandinskyInpaintPipeline.from_pretrained(
             '''kandinsky-community/kandinsky-2-1-inpaint''' ,						torch_dtype=torch.floataa)
         A__		 =					pipeline.to(lowercase_)
         pipeline.set_progress_bar_config(disable=lowercase_)

         A__		 =					torch.Generator(device='''cpu''').manual_seed(0)
         A__		 =					pipe_prior(
             lowercase_ ,						generator=lowercase_ ,						num_inference_steps=5 ,						negative_prompt='''''' ,						).to_tuple()

         A__		 =					pipeline(
             lowercase_ ,						image=lowercase_ ,						mask_image=lowercase_ ,						image_embeds=lowercase_ ,						negative_image_embeds=lowercase_ ,						generator=lowercase_ ,						num_inference_steps=1_0_0 ,						height=7_6_8 ,						width=7_6_8 ,						output_type='''np''' ,						)

         A__		 =					output.images[0]

         assert image.shape == (7_6_8, 7_6_8, 3)

         assert_mean_pixel_difference(lowercase_ ,						lowercase_)





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__    (					)->  str:
    A__		 =					1_0
    A__		 =					datasets.Features(
        {
            '''tokens''': datasets.Sequence(datasets.Value('''string'''	)	),
            '''labels''': datasets.Sequence(datasets.ClassLabel(names=['''negative''', '''positive''']	)	),
            '''answers''': datasets.Sequence(
                {
                    '''text''': datasets.Value('''string'''	),
                    '''answer_start''': datasets.Value('''int32'''	),
                }	),
            '''id''': datasets.Value('''int64'''	),
        }	)
    A__		 =					datasets.Dataset.from_dict(
        {
            '''tokens''': [['''foo'''] * 5] * n,
            '''labels''': [[1] * 5] * n,
            '''answers''': [{'''answer_start''': [9_7], '''text''': ['''1976''']}] * 1_0,
            '''id''': list(range(UpperCamelCase_	)	),
        } ,       features=UpperCamelCase_ ,       )
    return dataset



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


# FILE_CONTENT + files


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



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



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

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



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

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



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

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



@pytest.fixture(scope='''session'''	)
def 		lowerCAmelCase__    (					UpperCamelCase_				:       List[Any] ,       UpperCamelCase_				:       Tuple	)->  int:
    if datasets.config.PY7ZR_AVAILABLE:
        import pyazr

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



@pytest.fixture(scope='''session'''	)
def 		lowerCAmelCase__    (					UpperCamelCase_				:       Tuple ,       UpperCamelCase_				:       int	)->  Optional[Any]:
    import tarfile

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



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

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



@pytest.fixture(scope='''session'''	)
def 		lowerCAmelCase__    (					UpperCamelCase_				:       Optional[int] ,       UpperCamelCase_				:       List[str]	)->  List[str]:
    import zipfile

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



@pytest.fixture(scope='''session'''	)
def 		lowerCAmelCase__    (					UpperCamelCase_				:       Tuple	)->  str:
    if datasets.config.ZSTANDARD_AVAILABLE:
        import zstandard as zstd

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



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


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

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

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



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



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



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



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



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



@pytest.fixture(scope='''session'''	)
def 		lowerCAmelCase__    (					UpperCamelCase_				:       int ,       UpperCamelCase_				:       Optional[int]	)->  List[str]:
    import bza

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



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



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



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



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



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



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



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



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



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



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



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

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



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

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



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



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



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



@pytest.fixture(scope='''session'''	)
def 		lowerCAmelCase__    (					UpperCamelCase_				:       Dict ,       UpperCamelCase_				:       Any ,       UpperCamelCase_				:       str	)->  Tuple:
    A__		 =					tmp_path_factory.mktemp('''data'''	) / '''dataset.jsonl.tar'''
    with tarfile.TarFile(UpperCamelCase_ ,       '''w'''	) as f:
        f.add(UpperCamelCase_ ,       arcname=os.path.basename(UpperCamelCase_	)	)
        f.add(UpperCamelCase_ ,       arcname=os.path.basename(UpperCamelCase_	)	)
    return path



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



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



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



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



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



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



@pytest.fixture(scope='''session'''	)
def 		lowerCAmelCase__    (					UpperCamelCase_				:       Optional[Any] ,       UpperCamelCase_				:       Tuple ,       UpperCamelCase_				:       Tuple	)->  Any:
    A__		 =					tmp_path_factory.mktemp('''data'''	) / '''dataset.ext.zip'''
    with zipfile.ZipFile(UpperCamelCase_ ,       '''w'''	) as f:
        f.write(UpperCamelCase_ ,       arcname=os.path.basename('''unsupported.ext'''	)	)
        f.write(UpperCamelCase_ ,       arcname=os.path.basename('''unsupported_2.ext'''	)	)
    return path



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



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



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



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



@pytest.fixture(scope='''session'''	)
def 		lowerCAmelCase__    (					UpperCamelCase_				:       Optional[Any]	)->  str:
    A__		 =					tmp_path_factory.mktemp('''data_dir'''	)

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

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

    return data_dir
