
"""simple docstring"""







import argparse
import json
from pathlib import Path

import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image

from transformers import (
    SwiftFormerConfig,
    SwiftFormerForImageClassification,
    ViTImageProcessor,
)
from transformers.utils import logging


logging.set_verbosity_info()
lowercase_         =       logging.get_logger(__name__)

lowercase_         =       torch.device("cpu")




def       A_      (       )  ->				Union[str, Any]:


     """simple docstring"""







     UpperCAmelCase_    :     List[str]            =	"""http://images.cocodataset.org/val2017/000000039769.jpg"""
     UpperCAmelCase_    :     Optional[Any]            =	Image.open(requests.get(lowercase    ,			stream=lowercase   ).raw   )
     return im




def       A_      (       lowercase   )  ->				List[str]:


     """simple docstring"""







     if swiftformer_name == "swiftformer_xs":
          return torch.tensor([-2.1_703E00, 2.1_107E00, -2.0_811E00, 8.8_685E-01, 2.4_360E-01]   )

     elif swiftformer_name == "swiftformer_s":
          return torch.tensor([3.9_636E-01, 2.3_478E-01, -1.6_963E00, -1.7_381E00, -8.6_337E-01]   )

     elif swiftformer_name == "swiftformer_l1":
          return torch.tensor([-4.2_768E-01, -4.7_429E-01, -1.0_897E00, -1.0_248E00, 3.5_523E-02]   )

     elif swiftformer_name == "swiftformer_l3":
          return torch.tensor([-2.5_330E-01, 2.4_211E-01, -6.0_185E-01, -8.2_789E-01, -6.0_446E-02]   )




def       A_      (       lowercase    ,			lowercase    ,			lowercase   )  ->				int:


     """simple docstring"""







     UpperCAmelCase_    :     Union[str, Any]            =	dct.pop(lowercase   )
     UpperCAmelCase_    :     Any            =	val




def       A_      (       lowercase   )  ->				int:


     """simple docstring"""







     UpperCAmelCase_    :     Any            =	[]
     for k in state_dict.keys():
          UpperCAmelCase_    :     Tuple            =	k
          if ".pwconv" in k:
               UpperCAmelCase_    :     Union[str, Any]            =	k_new.replace(""".pwconv"""    ,			""".point_wise_conv"""   )
          if ".dwconv" in k:
               UpperCAmelCase_    :     List[str]            =	k_new.replace(""".dwconv"""    ,			""".depth_wise_conv"""   )
          if ".Proj." in k:
               UpperCAmelCase_    :     Dict            =	k_new.replace(""".Proj."""    ,			""".proj."""   )
          if "patch_embed" in k_new:
               UpperCAmelCase_    :     List[str]            =	k_new.replace("""patch_embed"""    ,			"""swiftformer.patch_embed.patch_embedding"""   )
          if "network" in k_new:
               UpperCAmelCase_    :     Union[str, Any]            =	k_new.split("""."""   )
               if ls[2].isdigit():
                    UpperCAmelCase_    :     str            =	"""swiftformer.encoder.network.""" + ls[1] + """.blocks.""" + ls[2] + """.""" + """.""".join(ls[3:]   )
               else:
                    UpperCAmelCase_    :     Dict            =	k_new.replace("""network"""    ,			"""swiftformer.encoder.network"""   )
          rename_keys.append((k, k_new)   )
     return rename_keys




@torch.no_grad()
def       A_      (       lowercase    ,			lowercase    ,			lowercase   )  ->				Tuple:


     """simple docstring"""







     UpperCAmelCase_    :     List[str]            =	SwiftFormerConfig()

     # dataset (ImageNet-21k only or also fine-tuned on ImageNet 2012), patch_size and image_size
     UpperCAmelCase_    :     Any            =	1000
     UpperCAmelCase_    :     List[str]            =	"""huggingface/label-files"""
     UpperCAmelCase_    :     str            =	"""imagenet-1k-id2label.json"""
     UpperCAmelCase_    :     Union[str, Any]            =	json.load(open(hf_hub_download(lowercase    ,			lowercase    ,			repo_type="""dataset"""   )    ,			"""r"""   )   )
     UpperCAmelCase_    :     List[Any]            =	{int(lowercase   ): v for k, v in idalabel.items()}
     UpperCAmelCase_    :     int            =	idalabel
     UpperCAmelCase_    :     Dict            =	{v: k for k, v in idalabel.items()}

     # size of the architecture
     if swiftformer_name == "swiftformer_xs":
          UpperCAmelCase_    :     Dict            =	[3, 3, 6, 4]
          UpperCAmelCase_    :     str            =	[48, 56, 112, 220]

     elif swiftformer_name == "swiftformer_s":
          UpperCAmelCase_    :     Tuple            =	[3, 3, 9, 6]
          UpperCAmelCase_    :     Union[str, Any]            =	[48, 64, 168, 224]

     elif swiftformer_name == "swiftformer_l1":
          UpperCAmelCase_    :     List[str]            =	[4, 3, 10, 5]
          UpperCAmelCase_    :     Dict            =	[48, 96, 192, 384]

     elif swiftformer_name == "swiftformer_l3":
          UpperCAmelCase_    :     int            =	[4, 4, 12, 6]
          UpperCAmelCase_    :     List[str]            =	[64, 128, 320, 512]

     # load state_dict of original model, remove and rename some keys
     if original_ckpt:
          if original_ckpt.startswith("""https"""   ):
               UpperCAmelCase_    :     Union[str, Any]            =	torch.hub.load_state_dict_from_url(lowercase    ,			map_location="""cpu"""    ,			check_hash=lowercase   )
          else:
               UpperCAmelCase_    :     Dict            =	torch.load(lowercase    ,			map_location="""cpu"""   )
     UpperCAmelCase_    :     Any            =	checkpoint

     UpperCAmelCase_    :     List[Any]            =	create_rename_keys(lowercase   )
     for rename_key_src, rename_key_dest in rename_keys:
          rename_key(lowercase    ,			lowercase    ,			lowercase   )

     # load HuggingFace model
     UpperCAmelCase_    :     List[str]            =	SwiftFormerForImageClassification(lowercase   ).eval()
     hf_model.load_state_dict(lowercase   )

     # prepare test inputs
     UpperCAmelCase_    :     List[Any]            =	prepare_img()
     UpperCAmelCase_    :     List[str]            =	ViTImageProcessor.from_pretrained("""preprocessor_config"""   )
     UpperCAmelCase_    :     Dict            =	processor(images=lowercase    ,			return_tensors="""pt"""   )

     # compare outputs from both models
     UpperCAmelCase_    :     Any            =	get_expected_output(lowercase   )
     UpperCAmelCase_    :     Optional[Any]            =	hf_model(inputs["""pixel_values"""]   ).logits

     assert hf_logits.shape == torch.Size([1, 1000]   )
     assert torch.allclose(hf_logits[0, 0:5]    ,			lowercase    ,			atol=1E-3   )

     Path(lowercase   ).mkdir(exist_ok=lowercase   )
     print(f'''Saving model {swiftformer_name} to {pytorch_dump_folder_path}'''   )
     hf_model.save_pretrained(lowercase   )


if __name__ == "__main__":
       lowercase_         =       argparse.ArgumentParser()
       # Required parameters
       parser.add_argument(
           "--swiftformer_name",
           default="swiftformer_xs",
           choices=["swiftformer_xs", "swiftformer_s", "swiftformer_l1", "swiftformer_l3"],
           type=str,
           help="Name of the SwiftFormer model you'd like to convert.",
       )
       parser.add_argument(
           "--pytorch_dump_folder_path",
           default="./converted_outputs/",
           type=str,
           help="Path to the output PyTorch model directory.",
       )
       parser.add_argument("--original_ckpt", default=None, type=str, help="Path to the original model checkpoint.")

       lowercase_         =       parser.parse_args()
       convert_swiftformer_checkpoint(args.swiftformer_name, args.pytorch_dump_folder_path, args.original_ckpt)



"""simple docstring"""







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

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

import datasets
import datasets.config




@pytest.fixture(scope="""session"""   )
def       A_      (       )  ->				str:


     """simple docstring"""







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




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase    ,			lowercase   )  ->				int:


     """simple docstring"""







     UpperCAmelCase_    :     Optional[Any]            =	str(tmp_path_factory.mktemp("""data"""   ) / """file.arrow"""   )
     dataset.map(cache_file_name=lowercase   )
     return filename


# FILE_CONTENT + files


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




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase   )  ->				Optional[Any]:


     """simple docstring"""







     UpperCAmelCase_    :     int            =	tmp_path_factory.mktemp("""data"""   ) / """file.txt"""
     UpperCAmelCase_    :     Tuple            =	FILE_CONTENT
     with open(lowercase    ,			"""w"""   ) as f:
          f.write(lowercase   )
     return filename




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase   )  ->				Dict:


     """simple docstring"""







     import bza

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




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase   )  ->				List[str]:


     """simple docstring"""







     import gzip

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




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase   )  ->				Union[str, Any]:


     """simple docstring"""







     if datasets.config.LZ4_AVAILABLE:
          import lza.frame

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




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase    ,			lowercase   )  ->				Optional[Any]:


     """simple docstring"""







     if datasets.config.PY7ZR_AVAILABLE:
          import pyazr

          UpperCAmelCase_    :     List[str]            =	tmp_path_factory.mktemp("""data"""   ) / """file.txt.7z"""
          with pyazr.SevenZipFile(lowercase    ,			"""w"""   ) as archive:
               archive.write(lowercase    ,			arcname=os.path.basename(lowercase   )   )
          return path




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase    ,			lowercase   )  ->				Union[str, Any]:


     """simple docstring"""







     import tarfile

     UpperCAmelCase_    :     Optional[int]            =	tmp_path_factory.mktemp("""data"""   ) / """file.txt.tar"""
     with tarfile.TarFile(lowercase    ,			"""w"""   ) as f:
          f.add(lowercase    ,			arcname=os.path.basename(lowercase   )   )
     return path




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase   )  ->				int:


     """simple docstring"""







     import lzma

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




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase    ,			lowercase   )  ->				Any:


     """simple docstring"""







     import zipfile

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




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase   )  ->				Dict:


     """simple docstring"""







     if datasets.config.ZSTANDARD_AVAILABLE:
          import zstandard as zstd

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




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase   )  ->				Dict:


     """simple docstring"""







     UpperCAmelCase_    :     int            =	tmp_path_factory.mktemp("""data"""   ) / """file.xml"""
     UpperCAmelCase_    :     int            =	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(lowercase    ,			"""w"""   ) as f:
          f.write(lowercase   )
     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       A_      (       )  ->				Union[str, Any]:


     """simple docstring"""







     return DATA_DICT_OF_LISTS




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase   )  ->				int:


     """simple docstring"""







     UpperCAmelCase_    :     str            =	datasets.Dataset.from_dict(lowercase   )
     UpperCAmelCase_    :     List[str]            =	str(tmp_path_factory.mktemp("""data"""   ) / """dataset.arrow"""   )
     dataset.map(cache_file_name=lowercase   )
     return path




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase   )  ->				List[Any]:


     """simple docstring"""







     UpperCAmelCase_    :     Dict            =	str(tmp_path_factory.mktemp("""data"""   ) / """dataset.sqlite"""   )
     with contextlib.closing(sqlitea.connect(lowercase   )   ) as con:
          UpperCAmelCase_    :     Tuple            =	con.cursor()
          cur.execute("""CREATE TABLE dataset(col_1 text, col_2 int, col_3 real)"""   )
          for item in DATA:
               cur.execute("""INSERT INTO dataset(col_1, col_2, col_3) VALUES (?, ?, ?)"""    ,			tuple(item.values()   )   )
          con.commit()
     return path




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase   )  ->				Optional[int]:


     """simple docstring"""







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




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase   )  ->				str:


     """simple docstring"""







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




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase    ,			lowercase   )  ->				Optional[Any]:


     """simple docstring"""







     import bza

     UpperCAmelCase_    :     List[Any]            =	tmp_path_factory.mktemp("""data"""   ) / """dataset.csv.bz2"""
     with open(lowercase    ,			"""rb"""   ) as f:
          UpperCAmelCase_    :     Dict            =	f.read()
     # data = bytes(FILE_CONTENT, "utf-8")
     with bza.open(lowercase    ,			"""wb"""   ) as f:
          f.write(lowercase   )
     return path




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase    ,			lowercase    ,			lowercase   )  ->				List[Any]:


     """simple docstring"""







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




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase    ,			lowercase    ,			lowercase   )  ->				List[Any]:


     """simple docstring"""







     UpperCAmelCase_    :     Tuple            =	tmp_path_factory.mktemp("""data"""   ) / """dataset.csv.zip"""
     with zipfile.ZipFile(lowercase    ,			"""w"""   ) as f:
          f.write(lowercase    ,			arcname=os.path.basename(csv_path.replace(""".csv"""    ,			""".CSV"""   )   )   )
          f.write(lowercase    ,			arcname=os.path.basename(csva_path.replace(""".csv"""    ,			""".CSV"""   )   )   )
     return path




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase    ,			lowercase    ,			lowercase   )  ->				Optional[int]:


     """simple docstring"""







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




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase   )  ->				Any:


     """simple docstring"""







     UpperCAmelCase_    :     Union[str, Any]            =	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(lowercase    ,			"""wb"""   ) as f:
          UpperCAmelCase_    :     List[str]            =	pq.ParquetWriter(lowercase    ,			schema=lowercase   )
          UpperCAmelCase_    :     Any            =	pa.Table.from_pydict({k: [DATA[i][k] for i in range(len(lowercase   )   )] for k in DATA[0]}    ,			schema=lowercase   )
          writer.write_table(lowercase   )
          writer.close()
     return path




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase   )  ->				Tuple:


     """simple docstring"""







     UpperCAmelCase_    :     Union[str, Any]            =	str(tmp_path_factory.mktemp("""data"""   ) / """dataset.json"""   )
     UpperCAmelCase_    :     Union[str, Any]            =	{"""data""": DATA}
     with open(lowercase    ,			"""w"""   ) as f:
          json.dump(lowercase    ,			lowercase   )
     return path




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase   )  ->				Optional[int]:


     """simple docstring"""







     UpperCAmelCase_    :     Union[str, Any]            =	str(tmp_path_factory.mktemp("""data"""   ) / """dataset.json"""   )
     UpperCAmelCase_    :     Optional[int]            =	{"""data""": DATA_DICT_OF_LISTS}
     with open(lowercase    ,			"""w"""   ) as f:
          json.dump(lowercase    ,			lowercase   )
     return path




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase   )  ->				str:


     """simple docstring"""







     UpperCAmelCase_    :     List[str]            =	str(tmp_path_factory.mktemp("""data"""   ) / """dataset.jsonl"""   )
     with open(lowercase    ,			"""w"""   ) as f:
          for item in DATA:
               f.write(json.dumps(lowercase   ) + """\n"""   )
     return path




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase   )  ->				Union[str, Any]:


     """simple docstring"""







     UpperCAmelCase_    :     str            =	str(tmp_path_factory.mktemp("""data"""   ) / """dataset2.jsonl"""   )
     with open(lowercase    ,			"""w"""   ) as f:
          for item in DATA:
               f.write(json.dumps(lowercase   ) + """\n"""   )
     return path




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase   )  ->				Optional[Any]:


     """simple docstring"""







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




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase   )  ->				Optional[int]:


     """simple docstring"""







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




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase    ,			lowercase   )  ->				Dict:


     """simple docstring"""







     import gzip

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




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase    ,			lowercase   )  ->				str:


     """simple docstring"""







     import gzip

     UpperCAmelCase_    :     Optional[Any]            =	str(tmp_path_factory.mktemp("""data"""   ) / """dataset.jsonl.gz"""   )
     with open(lowercase    ,			"""rb"""   ) as orig_file:
          with gzip.open(lowercase    ,			"""wb"""   ) as zipped_file:
               zipped_file.writelines(lowercase   )
     return path




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase    ,			lowercase    ,			lowercase   )  ->				Optional[int]:


     """simple docstring"""







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




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase    ,			lowercase    ,			lowercase    ,			lowercase   )  ->				List[Any]:


     """simple docstring"""







     UpperCAmelCase_    :     List[Any]            =	tmp_path_factory.mktemp("""data"""   ) / """dataset_nested.jsonl.zip"""
     with zipfile.ZipFile(lowercase    ,			"""w"""   ) as f:
          f.write(lowercase    ,			arcname=os.path.join("""nested"""    ,			os.path.basename(lowercase   )   )   )
     return path




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase    ,			lowercase    ,			lowercase   )  ->				Optional[Any]:


     """simple docstring"""







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




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase    ,			lowercase    ,			lowercase   )  ->				int:


     """simple docstring"""







     UpperCAmelCase_    :     int            =	tmp_path_factory.mktemp("""data"""   ) / """dataset.jsonl.tar"""
     with tarfile.TarFile(lowercase    ,			"""w"""   ) as f:
          f.add(lowercase    ,			arcname=os.path.basename(lowercase   )   )
          f.add(lowercase    ,			arcname=os.path.basename(lowercase   )   )
     return path




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase    ,			lowercase    ,			lowercase    ,			lowercase   )  ->				Union[str, Any]:


     """simple docstring"""







     UpperCAmelCase_    :     Optional[int]            =	tmp_path_factory.mktemp("""data"""   ) / """dataset_nested.jsonl.tar"""
     with tarfile.TarFile(lowercase    ,			"""w"""   ) as f:
          f.add(lowercase    ,			arcname=os.path.join("""nested"""    ,			os.path.basename(lowercase   )   )   )
     return path




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase   )  ->				Tuple:


     """simple docstring"""







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




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase   )  ->				str:


     """simple docstring"""







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




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase   )  ->				int:


     """simple docstring"""







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




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase    ,			lowercase    ,			lowercase   )  ->				int:


     """simple docstring"""







     UpperCAmelCase_    :     Any            =	tmp_path_factory.mktemp("""data"""   ) / """dataset.text.zip"""
     with zipfile.ZipFile(lowercase    ,			"""w"""   ) as f:
          f.write(lowercase    ,			arcname=os.path.basename(lowercase   )   )
          f.write(lowercase    ,			arcname=os.path.basename(lowercase   )   )
     return path




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase    ,			lowercase    ,			lowercase   )  ->				List[Any]:


     """simple docstring"""







     UpperCAmelCase_    :     Tuple            =	tmp_path_factory.mktemp("""data"""   ) / """dataset_with_dir.text.zip"""
     with zipfile.ZipFile(lowercase    ,			"""w"""   ) as f:
          f.write(lowercase    ,			arcname=os.path.join("""main_dir"""    ,			os.path.basename(lowercase   )   )   )
          f.write(lowercase    ,			arcname=os.path.join("""main_dir"""    ,			os.path.basename(lowercase   )   )   )
     return path




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase    ,			lowercase    ,			lowercase   )  ->				str:


     """simple docstring"""







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




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase   )  ->				Union[str, Any]:


     """simple docstring"""







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




@pytest.fixture(scope="""session"""   )
def       A_      (       )  ->				Optional[int]:


     """simple docstring"""







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




@pytest.fixture(scope="""session"""   )
def       A_      (       )  ->				Tuple:


     """simple docstring"""







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




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase    ,			lowercase   )  ->				int:


     """simple docstring"""







     UpperCAmelCase_    :     Dict            =	tmp_path_factory.mktemp("""data"""   ) / """dataset.img.zip"""
     with zipfile.ZipFile(lowercase    ,			"""w"""   ) as f:
          f.write(lowercase    ,			arcname=os.path.basename(lowercase   )   )
          f.write(lowercase    ,			arcname=os.path.basename(lowercase   ).replace(""".jpg"""    ,			"""2.jpg"""   )   )
     return path




@pytest.fixture(scope="""session"""   )
def       A_      (       lowercase   )  ->				Dict:


     """simple docstring"""







     UpperCAmelCase_    :     Optional[int]            =	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

