




"""simple docstring"""







import math
from typing import Any, Callable, List, Optional, Tuple, Union

import numpy as np
import torch

from ...models import TaFilmDecoder
from ...schedulers import DDPMScheduler
from ...utils import is_onnx_available, logging, randn_tensor


if is_onnx_available():
		from ..onnx_utils import OnnxRuntimeModel

from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
from .continous_encoder import SpectrogramContEncoder
from .notes_encoder import SpectrogramNotesEncoder


a            =							logging.get_logger(__name__)  # pylint: disable=invalid-name

a            =							2_5_6






class 					SCREAMING_SNAKE_CASE__    (    _snake_case    ):
						_a			  =  ['''melgan''']


						def __init__(							self :	Optional[int]  ,  lowerCAmelCase :	int  ,  lowerCAmelCase :	Any  ,  lowerCAmelCase :	List[Any]  ,  lowerCAmelCase :	int  ,  lowerCAmelCase :	List[Any]  ,  ):
										super().__init__()

										# From MELGAN
										lowerCAmelCase              = math.log(1e-5    )  # Matches MelGAN training.
										lowerCAmelCase              = 4.0  # Largest value for most examples
										lowerCAmelCase              = 128

										self.register_modules(
										    notes_encoder=_UpperCamelCase  ,  continuous_encoder=_UpperCamelCase  ,  decoder=_UpperCamelCase  ,  scheduler=_UpperCamelCase  ,  melgan=_UpperCamelCase  ,  )


						def      __lowercase       (							self :	int  ,  lowerCAmelCase :	Dict  ,  lowerCAmelCase :	List[str]=(-1.0, 1.0)  ,  lowerCAmelCase :	Any=False    ):
										lowerCAmelCase              = output_range
										if clip:
														lowerCAmelCase              = torch.clip(_UpperCamelCase  ,  self.min_value  ,  self.max_value    )
										# Scale to [0, 1].
										lowerCAmelCase              = (features - self.min_value) / (self.max_value - self.min_value)
										# Scale to [min_out, max_out].
										return zero_one * (max_out - min_out) + min_out


						def      __lowercase       (							self :	Union[str, Any]  ,  lowerCAmelCase :	Any  ,  lowerCAmelCase :	Dict=(-1.0, 1.0)  ,  lowerCAmelCase :	Optional[Any]=False    ):
										lowerCAmelCase              = input_range
										lowerCAmelCase              = torch.clip(_UpperCamelCase  ,  _UpperCamelCase  ,  _UpperCamelCase    ) if clip else outputs
										# Scale to [0, 1].
										lowerCAmelCase              = (outputs - min_out) / (max_out - min_out)
										# Scale to [self.min_value, self.max_value].
										return zero_one * (self.max_value - self.min_value) + self.min_value


						def      __lowercase       (							self :	Dict  ,  lowerCAmelCase :	Optional[int]  ,  lowerCAmelCase :	Tuple  ,  lowerCAmelCase :	Tuple    ):
										lowerCAmelCase              = input_tokens > 0
										lowerCAmelCase              = self.notes_encoder(
										    encoder_input_tokens=_UpperCamelCase  ,  encoder_inputs_mask=_UpperCamelCase    )

										lowerCAmelCase              = self.continuous_encoder(
										    encoder_inputs=_UpperCamelCase  ,  encoder_inputs_mask=_UpperCamelCase    )

										return [(tokens_encoded, tokens_mask), (continuous_encoded, continuous_mask)]


						def      __lowercase       (							self :	Union[str, Any]  ,  lowerCAmelCase :	Optional[Any]  ,  lowerCAmelCase :	str  ,  lowerCAmelCase :	Any    ):
										lowerCAmelCase              = noise_time
										if not torch.is_tensor(_UpperCamelCase    ):
														lowerCAmelCase              = torch.tensor([timesteps]  ,  dtype=torch.long  ,  device=input_tokens.device    )
										elif torch.is_tensor(_UpperCamelCase    ) and len(timesteps.shape    ) == 0:
														lowerCAmelCase              = timesteps[None].to(input_tokens.device    )

										# broadcast to batch dimension in a way that's compatible with ONNX/Core ML
										lowerCAmelCase              = timesteps * torch.ones(input_tokens.shape[0]  ,  dtype=timesteps.dtype  ,  device=timesteps.device    )

										lowerCAmelCase              = self.decoder(
										    encodings_and_masks=_UpperCamelCase  ,  decoder_input_tokens=_UpperCamelCase  ,  decoder_noise_time=_UpperCamelCase    )
										return logits




						@torch.no_grad()
						def __call__(							self :	Union[str, Any]  ,  lowerCAmelCase :	Optional[int]  ,  lowerCAmelCase :	List[str] = None  ,  lowerCAmelCase :	Tuple = 100  ,  lowerCAmelCase :	Any = True  ,  lowerCAmelCase :	List[str] = "numpy"  ,  lowerCAmelCase :	Optional[int] = None  ,  lowerCAmelCase :	Optional[int] = 1  ,  ):
										if (callback_steps is None) or (
										    callback_steps is not None and (not isinstance(_UpperCamelCase  ,  _UpperCamelCase    ) or callback_steps <= 0)
										):
														raise ValueError(
														    f'''`callback_steps` has to be a positive integer but is {callback_steps} of type'''
														    f''' {type(_UpperCamelCase    )}.'''    )

										lowerCAmelCase              = np.zeros([1, TARGET_FEATURE_LENGTH, self.n_dims]  ,  dtype=np.floataa    )
										lowerCAmelCase              = np.zeros([1, 0, self.n_dims]  ,  np.floataa    )
										lowerCAmelCase              = torch.ones((1, TARGET_FEATURE_LENGTH)  ,  dtype=_UpperCamelCase  ,  device=self.device    )

										for i, encoder_input_tokens in enumerate(_UpperCamelCase    ):
														if i == 0:
																		lowerCAmelCase              = torch.from_numpy(pred_mel[:1].copy()    ).to(
																		    device=self.device  ,  dtype=self.decoder.dtype    )
																		# The first chunk has no previous context.
																		lowerCAmelCase              = torch.zeros((1, TARGET_FEATURE_LENGTH)  ,  dtype=_UpperCamelCase  ,  device=self.device    )
														else:
																		# The full song pipeline does not feed in a context feature, so the mask
																		# will be all 0s after the feature converter. Because we know we're
																		# feeding in a full context chunk from the previous prediction, set it
																		# to all 1s.
																		lowerCAmelCase              = ones

														lowerCAmelCase              = self.scale_features(
														    _UpperCamelCase  ,  output_range=[-1.0, 1.0]  ,  clip=_UpperCamelCase    )

														lowerCAmelCase              = self.encode(
														    input_tokens=torch.IntTensor([encoder_input_tokens]    ).to(device=self.device    )  ,  continuous_inputs=_UpperCamelCase  ,  continuous_mask=_UpperCamelCase  ,  )

														# Sample encoder_continuous_inputs shaped gaussian noise to begin loop
														lowerCAmelCase              = randn_tensor(
														    shape=encoder_continuous_inputs.shape  ,  generator=_UpperCamelCase  ,  device=self.device  ,  dtype=self.decoder.dtype  ,  )

														# set step values
														self.scheduler.set_timesteps(_UpperCamelCase    )

														# Denoising diffusion loop
														for j, t in enumerate(self.progress_bar(self.scheduler.timesteps    )    ):
																		lowerCAmelCase              = self.decode(
																		    encodings_and_masks=_UpperCamelCase  ,  input_tokens=_UpperCamelCase  ,  noise_time=t / self.scheduler.config.num_train_timesteps  ,  )

																		# Compute previous output: x_t -> x_t-1
																		lowerCAmelCase              = self.scheduler.step(_UpperCamelCase  ,  _UpperCamelCase  ,  _UpperCamelCase  ,  generator=_UpperCamelCase    ).prev_sample

														lowerCAmelCase              = self.scale_to_features(_UpperCamelCase  ,  input_range=[-1.0, 1.0]    )
														lowerCAmelCase              = mel[:1]
														lowerCAmelCase              = mel.cpu().float().numpy()

														lowerCAmelCase              = np.concatenate([full_pred_mel, pred_mel[:1]]  ,  axis=1    )

														# call the callback, if provided
														if callback is not None and i % callback_steps == 0:
																		callback(_UpperCamelCase  ,  _UpperCamelCase    )

														logger.info("""Generated segment"""  ,  _UpperCamelCase    )

										if output_type == "numpy" and not is_onnx_available():
														raise ValueError(
														    """Cannot return output in \'np\' format if ONNX is not available. Make sure to have ONNX installed or set \'output_type\' to \'mel\'."""    )
										elif output_type == "numpy" and self.melgan is None:
														raise ValueError(
														    """Cannot return output in \'np\' format if melgan component is not defined. Make sure to define `self.melgan` or set \'output_type\' to \'mel\'."""    )

										if output_type == "numpy":
														lowerCAmelCase              = self.melgan(input_features=full_pred_mel.astype(np.floataa    )    )
										else:
														lowerCAmelCase              = full_pred_mel

										if not return_dict:
														return (output,)

										return AudioPipelineOutput(audios=_UpperCamelCase    )













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      lowercase__      (     ):


					'''simple docstring'''


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




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							Optional[Any]     ,       __snake_case    :							List[str]  ):


					'''simple docstring'''


					UpperCAmelCase_    :      str            =						str(tmp_path_factory.mktemp('data'  ) / 'file.arrow'  )
					dataset.map(cache_file_name=__snake_case  )
					return filename


# FILE_CONTENT + files


__UpperCAmelCase								=						'\\n    Text data.\n    Second line of data.'




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							Optional[Any]  ):


					'''simple docstring'''


					UpperCAmelCase_    :      Optional[int]            =						tmp_path_factory.mktemp('data'  ) / 'file.txt'
					UpperCAmelCase_    :      Tuple            =						FILE_CONTENT
					with open(__snake_case     ,       'w'  ) as f:
										f.write(__snake_case  )
					return filename




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							List[str]  ):


					'''simple docstring'''


					import bza

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




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							Any  ):


					'''simple docstring'''


					import gzip

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




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							Dict  ):


					'''simple docstring'''


					if datasets.config.LZ4_AVAILABLE:
										import lza.frame

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




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							Tuple     ,       __snake_case    :							List[Any]  ):


					'''simple docstring'''


					if datasets.config.PY7ZR_AVAILABLE:
										import pyazr

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




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							List[str]     ,       __snake_case    :							List[Any]  ):


					'''simple docstring'''


					import tarfile

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




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							str  ):


					'''simple docstring'''


					import lzma

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




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							Optional[int]     ,       __snake_case    :							Optional[Any]  ):


					'''simple docstring'''


					import zipfile

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




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							Optional[Any]  ):


					'''simple docstring'''


					if datasets.config.ZSTANDARD_AVAILABLE:
										import zstandard as zstd

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




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							Any  ):


					'''simple docstring'''


					UpperCAmelCase_    :      Union[str, Any]            =						tmp_path_factory.mktemp('data'  ) / 'file.xml'
					UpperCAmelCase_    :      List[Any]            =						textwrap.dedent(
					    '\\n    <?xml version="1.0" encoding="UTF-8" ?>\n    <tmx version="1.4">\n      <header segtype="sentence" srclang="ca" />\n      <body>\n        <tu>\n          <tuv xml:lang="ca"><seg>Contingut 1</seg></tuv>\n          <tuv xml:lang="en"><seg>Content 1</seg></tuv>\n        </tu>\n        <tu>\n          <tuv xml:lang="ca"><seg>Contingut 2</seg></tuv>\n          <tuv xml:lang="en"><seg>Content 2</seg></tuv>\n        </tu>\n        <tu>\n          <tuv xml:lang="ca"><seg>Contingut 3</seg></tuv>\n          <tuv xml:lang="en"><seg>Content 3</seg></tuv>\n        </tu>\n        <tu>\n          <tuv xml:lang="ca"><seg>Contingut 4</seg></tuv>\n          <tuv xml:lang="en"><seg>Content 4</seg></tuv>\n        </tu>\n        <tu>\n          <tuv xml:lang="ca"><seg>Contingut 5</seg></tuv>\n          <tuv xml:lang="en"><seg>Content 5</seg></tuv>\n        </tu>\n      </body>\n    </tmx>'  )
					with open(__snake_case     ,       'w'  ) as f:
										f.write(__snake_case  )
					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      lowercase__      (     ):


					'''simple docstring'''


					return DATA_DICT_OF_LISTS




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							int  ):


					'''simple docstring'''


					UpperCAmelCase_    :      List[Any]            =						datasets.Dataset.from_dict(__snake_case  )
					UpperCAmelCase_    :      Optional[Any]            =						str(tmp_path_factory.mktemp('data'  ) / 'dataset.arrow'  )
					dataset.map(cache_file_name=__snake_case  )
					return path




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							List[Any]  ):


					'''simple docstring'''


					UpperCAmelCase_    :      Optional[int]            =						str(tmp_path_factory.mktemp('data'  ) / 'dataset.sqlite'  )
					with contextlib.closing(sqlitea.connect(__snake_case  )  ) as con:
										UpperCAmelCase_    :      List[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      lowercase__      (     __snake_case    :							Union[str, Any]  ):


					'''simple docstring'''


					UpperCAmelCase_    :      Optional[Any]            =						str(tmp_path_factory.mktemp('data'  ) / 'dataset.csv'  )
					with open(__snake_case     ,       'w'     ,       newline=''  ) as f:
										UpperCAmelCase_    :      Tuple            =						csv.DictWriter(__snake_case     ,       fieldnames=['col_1', 'col_2', 'col_3']  )
										writer.writeheader()
										for item in DATA:
															writer.writerow(__snake_case  )
					return path




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							Optional[Any]  ):


					'''simple docstring'''


					UpperCAmelCase_    :      Tuple            =						str(tmp_path_factory.mktemp('data'  ) / 'dataset2.csv'  )
					with open(__snake_case     ,       'w'     ,       newline=''  ) as f:
										UpperCAmelCase_    :      Optional[Any]            =						csv.DictWriter(__snake_case     ,       fieldnames=['col_1', 'col_2', 'col_3']  )
										writer.writeheader()
										for item in DATA:
															writer.writerow(__snake_case  )
					return path




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							str     ,       __snake_case    :							Any  ):


					'''simple docstring'''


					import bza

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




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							List[str]     ,       __snake_case    :							Tuple     ,       __snake_case    :							Optional[Any]  ):


					'''simple docstring'''


					UpperCAmelCase_    :      List[Any]            =						tmp_path_factory.mktemp('data'  ) / 'dataset.csv.zip'
					with zipfile.ZipFile(__snake_case     ,       'w'  ) as f:
										f.write(__snake_case     ,       arcname=os.path.basename(__snake_case  )  )
										f.write(__snake_case     ,       arcname=os.path.basename(__snake_case  )  )
					return path




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							str     ,       __snake_case    :							Optional[int]     ,       __snake_case    :							Tuple  ):


					'''simple docstring'''


					UpperCAmelCase_    :      List[Any]            =						tmp_path_factory.mktemp('data'  ) / 'dataset.csv.zip'
					with zipfile.ZipFile(__snake_case     ,       'w'  ) as f:
										f.write(__snake_case     ,       arcname=os.path.basename(csv_path.replace('.csv'     ,       '.CSV'  )  )  )
										f.write(__snake_case     ,       arcname=os.path.basename(csva_path.replace('.csv'     ,       '.CSV'  )  )  )
					return path




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							Tuple     ,       __snake_case    :							int     ,       __snake_case    :							str  ):


					'''simple docstring'''


					UpperCAmelCase_    :      Optional[Any]            =						tmp_path_factory.mktemp('data'  ) / 'dataset_with_dir.csv.zip'
					with zipfile.ZipFile(__snake_case     ,       'w'  ) as f:
										f.write(__snake_case     ,       arcname=os.path.join('main_dir'     ,       os.path.basename(__snake_case  )  )  )
										f.write(__snake_case     ,       arcname=os.path.join('main_dir'     ,       os.path.basename(__snake_case  )  )  )
					return path




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							Union[str, Any]  ):


					'''simple docstring'''


					UpperCAmelCase_    :      int            =						str(tmp_path_factory.mktemp('data'  ) / 'dataset.parquet'  )
					UpperCAmelCase_    :      Dict            =						pa.schema(
					    {
					        'col_1': pa.string(),
					        'col_2': pa.intaa(),
					        'col_3': pa.floataa(),
					    }  )
					with open(__snake_case     ,       'wb'  ) as f:
										UpperCAmelCase_    :      List[Any]            =						pq.ParquetWriter(__snake_case     ,       schema=__snake_case  )
										UpperCAmelCase_    :      Any            =						pa.Table.from_pydict({k: [DATA[i][k] for i in range(len(__snake_case  )  )] for k in DATA[0]}     ,       schema=__snake_case  )
										writer.write_table(__snake_case  )
										writer.close()
					return path




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							Union[str, Any]  ):


					'''simple docstring'''


					UpperCAmelCase_    :      Tuple            =						str(tmp_path_factory.mktemp('data'  ) / 'dataset.json'  )
					UpperCAmelCase_    :      Optional[int]            =						{'data': DATA}
					with open(__snake_case     ,       'w'  ) as f:
										json.dump(__snake_case     ,       __snake_case  )
					return path




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							List[Any]  ):


					'''simple docstring'''


					UpperCAmelCase_    :      Tuple            =						str(tmp_path_factory.mktemp('data'  ) / 'dataset.json'  )
					UpperCAmelCase_    :      Tuple            =						{'data': DATA_DICT_OF_LISTS}
					with open(__snake_case     ,       'w'  ) as f:
										json.dump(__snake_case     ,       __snake_case  )
					return path




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							Optional[Any]  ):


					'''simple docstring'''


					UpperCAmelCase_    :      Dict            =						str(tmp_path_factory.mktemp('data'  ) / 'dataset.jsonl'  )
					with open(__snake_case     ,       'w'  ) as f:
										for item in DATA:
															f.write(json.dumps(__snake_case  ) + '\n'  )
					return path




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							str  ):


					'''simple docstring'''


					UpperCAmelCase_    :      Union[str, Any]            =						str(tmp_path_factory.mktemp('data'  ) / 'dataset2.jsonl'  )
					with open(__snake_case     ,       'w'  ) as f:
										for item in DATA:
															f.write(json.dumps(__snake_case  ) + '\n'  )
					return path




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							int  ):


					'''simple docstring'''


					UpperCAmelCase_    :      int            =						str(tmp_path_factory.mktemp('data'  ) / 'dataset_312.jsonl'  )
					with open(__snake_case     ,       'w'  ) as f:
										for item in DATA_312:
															f.write(json.dumps(__snake_case  ) + '\n'  )
					return path




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							str  ):


					'''simple docstring'''


					UpperCAmelCase_    :      Optional[int]            =						str(tmp_path_factory.mktemp('data'  ) / 'dataset-str.jsonl'  )
					with open(__snake_case     ,       'w'  ) as f:
										for item in DATA_STR:
															f.write(json.dumps(__snake_case  ) + '\n'  )
					return path




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							Dict     ,       __snake_case    :							Dict  ):


					'''simple docstring'''


					import gzip

					UpperCAmelCase_    :      Union[str, Any]            =						str(tmp_path_factory.mktemp('data'  ) / 'dataset.txt.gz'  )
					with open(__snake_case     ,       'rb'  ) as orig_file:
										with gzip.open(__snake_case     ,       'wb'  ) as zipped_file:
															zipped_file.writelines(__snake_case  )
					return path




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							int     ,       __snake_case    :							Any  ):


					'''simple docstring'''


					import gzip

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




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							Optional[Any]     ,       __snake_case    :							Dict     ,       __snake_case    :							Optional[int]  ):


					'''simple docstring'''


					UpperCAmelCase_    :      int            =						tmp_path_factory.mktemp('data'  ) / 'dataset.jsonl.zip'
					with zipfile.ZipFile(__snake_case     ,       'w'  ) as f:
										f.write(__snake_case     ,       arcname=os.path.basename(__snake_case  )  )
										f.write(__snake_case     ,       arcname=os.path.basename(__snake_case  )  )
					return path




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							Optional[Any]     ,       __snake_case    :							str     ,       __snake_case    :							Dict     ,       __snake_case    :							Union[str, Any]  ):


					'''simple docstring'''


					UpperCAmelCase_    :      str            =						tmp_path_factory.mktemp('data'  ) / 'dataset_nested.jsonl.zip'
					with zipfile.ZipFile(__snake_case     ,       'w'  ) as f:
										f.write(__snake_case     ,       arcname=os.path.join('nested'     ,       os.path.basename(__snake_case  )  )  )
					return path




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							Dict     ,       __snake_case    :							Union[str, Any]     ,       __snake_case    :							Tuple  ):


					'''simple docstring'''


					UpperCAmelCase_    :      Optional[int]            =						tmp_path_factory.mktemp('data'  ) / 'dataset_with_dir.jsonl.zip'
					with zipfile.ZipFile(__snake_case     ,       'w'  ) as f:
										f.write(__snake_case     ,       arcname=os.path.join('main_dir'     ,       os.path.basename(__snake_case  )  )  )
										f.write(__snake_case     ,       arcname=os.path.join('main_dir'     ,       os.path.basename(__snake_case  )  )  )
					return path




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							Tuple     ,       __snake_case    :							str     ,       __snake_case    :							Union[str, Any]  ):


					'''simple docstring'''


					UpperCAmelCase_    :      List[Any]            =						tmp_path_factory.mktemp('data'  ) / 'dataset.jsonl.tar'
					with tarfile.TarFile(__snake_case     ,       'w'  ) as f:
										f.add(__snake_case     ,       arcname=os.path.basename(__snake_case  )  )
										f.add(__snake_case     ,       arcname=os.path.basename(__snake_case  )  )
					return path




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							str     ,       __snake_case    :							Any     ,       __snake_case    :							Any     ,       __snake_case    :							List[Any]  ):


					'''simple docstring'''


					UpperCAmelCase_    :      List[Any]            =						tmp_path_factory.mktemp('data'  ) / 'dataset_nested.jsonl.tar'
					with tarfile.TarFile(__snake_case     ,       'w'  ) as f:
										f.add(__snake_case     ,       arcname=os.path.join('nested'     ,       os.path.basename(__snake_case  )  )  )
					return path




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							List[Any]  ):


					'''simple docstring'''


					UpperCAmelCase_    :      Any            =						['0', '1', '2', '3']
					UpperCAmelCase_    :      Dict            =						str(tmp_path_factory.mktemp('data'  ) / 'dataset.txt'  )
					with open(__snake_case     ,       'w'  ) as f:
										for item in data:
															f.write(item + '\n'  )
					return path




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							List[Any]  ):


					'''simple docstring'''


					UpperCAmelCase_    :      Optional[Any]            =						['0', '1', '2', '3']
					UpperCAmelCase_    :      Optional[int]            =						str(tmp_path_factory.mktemp('data'  ) / 'dataset2.txt'  )
					with open(__snake_case     ,       'w'  ) as f:
										for item in data:
															f.write(item + '\n'  )
					return path




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							Tuple  ):


					'''simple docstring'''


					UpperCAmelCase_    :      Dict            =						['0', '1', '2', '3']
					UpperCAmelCase_    :      List[str]            =						tmp_path_factory.mktemp('data'  ) / 'dataset.abc'
					with open(__snake_case     ,       'w'  ) as f:
										for item in data:
															f.write(item + '\n'  )
					return path




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							Any     ,       __snake_case    :							Union[str, Any]     ,       __snake_case    :							List[Any]  ):


					'''simple docstring'''


					UpperCAmelCase_    :      List[Any]            =						tmp_path_factory.mktemp('data'  ) / 'dataset.text.zip'
					with zipfile.ZipFile(__snake_case     ,       'w'  ) as f:
										f.write(__snake_case     ,       arcname=os.path.basename(__snake_case  )  )
										f.write(__snake_case     ,       arcname=os.path.basename(__snake_case  )  )
					return path




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							Dict     ,       __snake_case    :							str     ,       __snake_case    :							Any  ):


					'''simple docstring'''


					UpperCAmelCase_    :      Union[str, Any]            =						tmp_path_factory.mktemp('data'  ) / 'dataset_with_dir.text.zip'
					with zipfile.ZipFile(__snake_case     ,       'w'  ) as f:
										f.write(__snake_case     ,       arcname=os.path.join('main_dir'     ,       os.path.basename(__snake_case  )  )  )
										f.write(__snake_case     ,       arcname=os.path.join('main_dir'     ,       os.path.basename(__snake_case  )  )  )
					return path




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							Union[str, Any]     ,       __snake_case    :							str     ,       __snake_case    :							Optional[int]  ):


					'''simple docstring'''


					UpperCAmelCase_    :      Union[str, Any]            =						tmp_path_factory.mktemp('data'  ) / 'dataset.ext.zip'
					with zipfile.ZipFile(__snake_case     ,       'w'  ) as f:
										f.write(__snake_case     ,       arcname=os.path.basename('unsupported.ext'  )  )
										f.write(__snake_case     ,       arcname=os.path.basename('unsupported_2.ext'  )  )
					return path




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							Dict  ):


					'''simple docstring'''


					UpperCAmelCase_    :      Tuple            =						'\n'.join(['First', 'Second\u2029with Unicode new line', 'Third']  )
					UpperCAmelCase_    :      Dict            =						str(tmp_path_factory.mktemp('data'  ) / 'dataset_with_unicode_new_lines.txt'  )
					with open(__snake_case     ,       'w'     ,       encoding='utf-8'  ) as f:
										f.write(__snake_case  )
					return path




@pytest.fixture(scope='session'  )
def      lowercase__      (     ):


					'''simple docstring'''


					return os.path.join('tests'     ,       'features'     ,       'data'     ,       'test_image_rgb.jpg'  )




@pytest.fixture(scope='session'  )
def      lowercase__      (     ):


					'''simple docstring'''


					return os.path.join('tests'     ,       'features'     ,       'data'     ,       'test_audio_44100.wav'  )




@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							str     ,       __snake_case    :							List[str]  ):


					'''simple docstring'''


					UpperCAmelCase_    :      Optional[Any]            =						tmp_path_factory.mktemp('data'  ) / 'dataset.img.zip'
					with zipfile.ZipFile(__snake_case     ,       'w'  ) as f:
										f.write(__snake_case     ,       arcname=os.path.basename(__snake_case  )  )
										f.write(__snake_case     ,       arcname=os.path.basename(__snake_case  ).replace('.jpg'     ,       '2.jpg'  )  )
					return path






@pytest.fixture(scope='session'  )
def      lowercase__      (     __snake_case    :							Any  ):


					'''simple docstring'''


					UpperCAmelCase_    :      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






