






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   SCREAMING_SNAKE_CASE       (				):
 snake_case__				:   str     =						10
 snake_case__				:   Union[str, Any]     =						datasets.Features(
     {
         "tokens": datasets.Sequence(datasets.Value("string"     )     ),
         "labels": datasets.Sequence(datasets.ClassLabel(names=["negative", "positive"]     )     ),
         "answers": datasets.Sequence(
             {
                 "text": datasets.Value("string"     ),
                 "answer_start": datasets.Value("int32"     ),
             }     ),
         "id": datasets.Value("int64"     ),
     }     )
 snake_case__				:   List[str]     =						datasets.Dataset.from_dict(
     {
         "tokens": [["foo"] * 5] * n,
         "labels": [[1] * 5] * n,
         "answers": [{"answer_start": [97], "text": ["1976"]}] * 10,
         "id": list(range(lowerCamelCase__     )     ),
     }  ,						features=lowerCamelCase__  ,						)
 return dataset







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							Dict  ,						snake_case_      :							Optional[Any]     ):
 snake_case__				:   str     =						str(tmp_path_factory.mktemp("data"     ) / "file.arrow"     )
 dataset.map(cache_file_name=lowerCamelCase__     )
 return filename


# FILE_CONTENT + files


__lowerCamelCase      :    Any   		=   """\
    Text data.
    Second line of data."""







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							List[Any]     ):
 snake_case__				:   Any     =						tmp_path_factory.mktemp("data"     ) / "file.txt"
 snake_case__				:   List[str]     =						FILE_CONTENT
 with open(lowerCamelCase__  ,						"w"     ) as f:
  f.write(lowerCamelCase__     )
 return filename







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							int     ):
 import bza

 snake_case__				:   Dict     =						tmp_path_factory.mktemp("data"     ) / "file.txt.bz2"
 snake_case__				:   Tuple     =						bytes(lowerCamelCase__  ,						"utf-8"     )
 with bza.open(lowerCamelCase__  ,						"wb"     ) as f:
  f.write(lowerCamelCase__     )
 return path







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							int     ):
 import gzip

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







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							Dict     ):


 if datasets.config.LZ4_AVAILABLE:
  import lza.frame

  snake_case__				:   Dict     =						tmp_path_factory.mktemp("data"     ) / "file.txt.lz4"
  snake_case__				:   Optional[Any]     =						bytes(lowerCamelCase__  ,						"utf-8"     )
  with lza.frame.open(lowerCamelCase__  ,						"wb"     ) as f:
   f.write(lowerCamelCase__     )
  return path







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							str  ,						snake_case_      :							Optional[Any]     ):


 if datasets.config.PY7ZR_AVAILABLE:
  import pyazr

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







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							List[str]  ,						snake_case_      :							int     ):
 import tarfile

 snake_case__				:   str     =						tmp_path_factory.mktemp("data"     ) / "file.txt.tar"
 with tarfile.TarFile(lowerCamelCase__  ,						"w"     ) as f:
  f.add(lowerCamelCase__  ,						arcname=os.path.basename(lowerCamelCase__     )     )
 return path







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							Any     ):
 import lzma

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







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							Dict  ,						snake_case_      :							Tuple     ):
 import zipfile

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







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							Dict     ):


 if datasets.config.ZSTANDARD_AVAILABLE:
  import zstandard as zstd

  snake_case__				:   Any     =						tmp_path_factory.mktemp("data"     ) / "file.txt.zst"
  snake_case__				:   Optional[Any]     =						bytes(lowerCamelCase__  ,						"utf-8"     )
  with zstd.open(lowerCamelCase__  ,						"wb"     ) as f:
   f.write(lowerCamelCase__     )
  return path







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							Optional[int]     ):
 snake_case__				:   Tuple     =						tmp_path_factory.mktemp("data"     ) / "file.xml"
 snake_case__				:   Optional[int]     =						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(lowerCamelCase__  ,						"w"     ) as f:
  f.write(lowerCamelCase__     )
 return filename


__lowerCamelCase      :    List[Any]   		=   [
    {"""col_1""": """0""", """col_2""": 0, """col_3""": 0.0},
    {"""col_1""": """1""", """col_2""": 1, """col_3""": 1.0},
    {"""col_1""": """2""", """col_2""": 2, """col_3""": 2.0},
    {"""col_1""": """3""", """col_2""": 3, """col_3""": 3.0},
]
__lowerCamelCase      :    str   		=   [
    {"""col_1""": """4""", """col_2""": 4, """col_3""": 4.0},
    {"""col_1""": """5""", """col_2""": 5, """col_3""": 5.0},
]
__lowerCamelCase      :    Optional[Any]   		=   {
    """col_1""": ["""0""", """1""", """2""", """3"""],
    """col_2""": [0, 1, 2, 3],
    """col_3""": [0.0, 1.0, 2.0, 3.0],
}

__lowerCamelCase      :    Union[str, Any]   		=   [
    {"""col_3""": 0.0, """col_1""": """0""", """col_2""": 0},
    {"""col_3""": 1.0, """col_1""": """1""", """col_2""": 1},
]

__lowerCamelCase      :    Union[str, Any]   		=   [
    {"""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   SCREAMING_SNAKE_CASE       (				):
 return DATA_DICT_OF_LISTS







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							Dict     ):
 snake_case__				:   Optional[int]     =						datasets.Dataset.from_dict(lowerCamelCase__     )
 snake_case__				:   Any     =						str(tmp_path_factory.mktemp("data"     ) / "dataset.arrow"     )
 dataset.map(cache_file_name=lowerCamelCase__     )
 return path







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







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							Dict     ):
 snake_case__				:   int     =						str(tmp_path_factory.mktemp("data"     ) / "dataset2.csv"     )
 with open(lowerCamelCase__  ,						"w"  ,						newline=""     ) as f:
  snake_case__				:   Union[str, Any]     =						csv.DictWriter(lowerCamelCase__  ,						fieldnames=["col_1", "col_2", "col_3"]     )
  writer.writeheader()
  for item in DATA:
   writer.writerow(lowerCamelCase__     )
 return path







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							Optional[int]  ,						snake_case_      :							Any     ):
 import bza

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







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							Dict  ,						snake_case_      :							List[Any]  ,						snake_case_      :							Any     ):
 snake_case__				:   Optional[int]     =						tmp_path_factory.mktemp("data"     ) / "dataset.csv.zip"
 with zipfile.ZipFile(lowerCamelCase__  ,						"w"     ) as f:
  f.write(lowerCamelCase__  ,						arcname=os.path.basename(lowerCamelCase__     )     )
  f.write(lowerCamelCase__  ,						arcname=os.path.basename(lowerCamelCase__     )     )
 return path







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							List[Any]  ,						snake_case_      :							str  ,						snake_case_      :							Union[str, Any]     ):
 snake_case__				:   List[Any]     =						tmp_path_factory.mktemp("data"     ) / "dataset.csv.zip"
 with zipfile.ZipFile(lowerCamelCase__  ,						"w"     ) as f:
  f.write(lowerCamelCase__  ,						arcname=os.path.basename(csv_path.replace(".csv"  ,						".CSV"     )     )     )
  f.write(lowerCamelCase__  ,						arcname=os.path.basename(csva_path.replace(".csv"  ,						".CSV"     )     )     )
 return path







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							List[str]  ,						snake_case_      :							Optional[int]  ,						snake_case_      :							str     ):
 snake_case__				:   Dict     =						tmp_path_factory.mktemp("data"     ) / "dataset_with_dir.csv.zip"
 with zipfile.ZipFile(lowerCamelCase__  ,						"w"     ) as f:
  f.write(lowerCamelCase__  ,						arcname=os.path.join("main_dir"  ,						os.path.basename(lowerCamelCase__     )     )     )
  f.write(lowerCamelCase__  ,						arcname=os.path.join("main_dir"  ,						os.path.basename(lowerCamelCase__     )     )     )
 return path







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							str     ):
 snake_case__				:   Union[str, Any]     =						str(tmp_path_factory.mktemp("data"     ) / "dataset.parquet"     )
 snake_case__				:   str     =						pa.schema(
     {
         "col_1": pa.string(),
         "col_2": pa.intaa(),
         "col_3": pa.floataa(),
     }     )
 with open(lowerCamelCase__  ,						"wb"     ) as f:
  snake_case__				:   Union[str, Any]     =						pq.ParquetWriter(lowerCamelCase__  ,						schema=lowerCamelCase__     )
  snake_case__				:   Optional[Any]     =						pa.Table.from_pydict({k: [DATA[i][k] for i in range(len(lowerCamelCase__     )     )] for k in DATA[0]}  ,						schema=lowerCamelCase__     )
  writer.write_table(lowerCamelCase__     )
  writer.close()
 return path







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							Any     ):
 snake_case__				:   Tuple     =						str(tmp_path_factory.mktemp("data"     ) / "dataset.json"     )
 snake_case__				:   int     =						{"data": DATA}
 with open(lowerCamelCase__  ,						"w"     ) as f:
  json.dump(lowerCamelCase__  ,						lowerCamelCase__     )
 return path







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							Union[str, Any]     ):
 snake_case__				:   List[str]     =						str(tmp_path_factory.mktemp("data"     ) / "dataset.json"     )
 snake_case__				:   int     =						{"data": DATA_DICT_OF_LISTS}
 with open(lowerCamelCase__  ,						"w"     ) as f:
  json.dump(lowerCamelCase__  ,						lowerCamelCase__     )
 return path







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







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							Tuple     ):
 snake_case__				:   Dict     =						str(tmp_path_factory.mktemp("data"     ) / "dataset2.jsonl"     )
 with open(lowerCamelCase__  ,						"w"     ) as f:
  for item in DATA:
   f.write(json.dumps(lowerCamelCase__     ) + "\n"     )
 return path







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							str     ):
 snake_case__				:   Any     =						str(tmp_path_factory.mktemp("data"     ) / "dataset_312.jsonl"     )
 with open(lowerCamelCase__  ,						"w"     ) as f:
  for item in DATA_312:
   f.write(json.dumps(lowerCamelCase__     ) + "\n"     )
 return path







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							Any     ):
 snake_case__				:   Dict     =						str(tmp_path_factory.mktemp("data"     ) / "dataset-str.jsonl"     )
 with open(lowerCamelCase__  ,						"w"     ) as f:
  for item in DATA_STR:
   f.write(json.dumps(lowerCamelCase__     ) + "\n"     )
 return path







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							Dict  ,						snake_case_      :							Union[str, Any]     ):
 import gzip

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







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							List[str]  ,						snake_case_      :							Optional[int]     ):
 import gzip

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







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							Dict  ,						snake_case_      :							Tuple  ,						snake_case_      :							int     ):
 snake_case__				:   List[Any]     =						tmp_path_factory.mktemp("data"     ) / "dataset.jsonl.zip"
 with zipfile.ZipFile(lowerCamelCase__  ,						"w"     ) as f:
  f.write(lowerCamelCase__  ,						arcname=os.path.basename(lowerCamelCase__     )     )
  f.write(lowerCamelCase__  ,						arcname=os.path.basename(lowerCamelCase__     )     )
 return path







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							Optional[int]  ,						snake_case_      :							List[str]  ,						snake_case_      :							Optional[int]  ,						snake_case_      :							Optional[int]     ):
 snake_case__				:   List[Any]     =						tmp_path_factory.mktemp("data"     ) / "dataset_nested.jsonl.zip"
 with zipfile.ZipFile(lowerCamelCase__  ,						"w"     ) as f:
  f.write(lowerCamelCase__  ,						arcname=os.path.join("nested"  ,						os.path.basename(lowerCamelCase__     )     )     )
 return path







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							str  ,						snake_case_      :							Union[str, Any]  ,						snake_case_      :							Dict     ):
 snake_case__				:   Any     =						tmp_path_factory.mktemp("data"     ) / "dataset_with_dir.jsonl.zip"
 with zipfile.ZipFile(lowerCamelCase__  ,						"w"     ) as f:
  f.write(lowerCamelCase__  ,						arcname=os.path.join("main_dir"  ,						os.path.basename(lowerCamelCase__     )     )     )
  f.write(lowerCamelCase__  ,						arcname=os.path.join("main_dir"  ,						os.path.basename(lowerCamelCase__     )     )     )
 return path







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							List[Any]  ,						snake_case_      :							str  ,						snake_case_      :							Any     ):
 snake_case__				:   Dict     =						tmp_path_factory.mktemp("data"     ) / "dataset.jsonl.tar"
 with tarfile.TarFile(lowerCamelCase__  ,						"w"     ) as f:
  f.add(lowerCamelCase__  ,						arcname=os.path.basename(lowerCamelCase__     )     )
  f.add(lowerCamelCase__  ,						arcname=os.path.basename(lowerCamelCase__     )     )
 return path







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							List[Any]  ,						snake_case_      :							Any  ,						snake_case_      :							List[str]  ,						snake_case_      :							List[Any]     ):
 snake_case__				:   Dict     =						tmp_path_factory.mktemp("data"     ) / "dataset_nested.jsonl.tar"
 with tarfile.TarFile(lowerCamelCase__  ,						"w"     ) as f:
  f.add(lowerCamelCase__  ,						arcname=os.path.join("nested"  ,						os.path.basename(lowerCamelCase__     )     )     )
 return path







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							int     ):
 snake_case__				:   List[Any]     =						["0", "1", "2", "3"]
 snake_case__				:   Union[str, Any]     =						str(tmp_path_factory.mktemp("data"     ) / "dataset.txt"     )
 with open(lowerCamelCase__  ,						"w"     ) as f:
  for item in data:
   f.write(item + "\n"     )
 return path







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







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							Any     ):
 snake_case__				:   List[str]     =						["0", "1", "2", "3"]
 snake_case__				:   Optional[Any]     =						tmp_path_factory.mktemp("data"     ) / "dataset.abc"
 with open(lowerCamelCase__  ,						"w"     ) as f:
  for item in data:
   f.write(item + "\n"     )
 return path







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							Optional[Any]  ,						snake_case_      :							Optional[int]  ,						snake_case_      :							Any     ):
 snake_case__				:   Tuple     =						tmp_path_factory.mktemp("data"     ) / "dataset.text.zip"
 with zipfile.ZipFile(lowerCamelCase__  ,						"w"     ) as f:
  f.write(lowerCamelCase__  ,						arcname=os.path.basename(lowerCamelCase__     )     )
  f.write(lowerCamelCase__  ,						arcname=os.path.basename(lowerCamelCase__     )     )
 return path







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							Tuple  ,						snake_case_      :							List[Any]  ,						snake_case_      :							Union[str, Any]     ):
 snake_case__				:   Any     =						tmp_path_factory.mktemp("data"     ) / "dataset_with_dir.text.zip"
 with zipfile.ZipFile(lowerCamelCase__  ,						"w"     ) as f:
  f.write(lowerCamelCase__  ,						arcname=os.path.join("main_dir"  ,						os.path.basename(lowerCamelCase__     )     )     )
  f.write(lowerCamelCase__  ,						arcname=os.path.join("main_dir"  ,						os.path.basename(lowerCamelCase__     )     )     )
 return path







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							Dict  ,						snake_case_      :							Tuple  ,						snake_case_      :							str     ):
 snake_case__				:   Any     =						tmp_path_factory.mktemp("data"     ) / "dataset.ext.zip"
 with zipfile.ZipFile(lowerCamelCase__  ,						"w"     ) as f:
  f.write(lowerCamelCase__  ,						arcname=os.path.basename("unsupported.ext"     )     )
  f.write(lowerCamelCase__  ,						arcname=os.path.basename("unsupported_2.ext"     )     )
 return path







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







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







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







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							List[str]  ,						snake_case_      :							Any     ):
 snake_case__				:   Union[str, Any]     =						tmp_path_factory.mktemp("data"     ) / "dataset.img.zip"
 with zipfile.ZipFile(lowerCamelCase__  ,						"w"     ) as f:
  f.write(lowerCamelCase__  ,						arcname=os.path.basename(lowerCamelCase__     )     )
  f.write(lowerCamelCase__  ,						arcname=os.path.basename(lowerCamelCase__     ).replace(".jpg"  ,						"2.jpg"     )     )
 return path







@pytest.fixture(scope="session"     )
def   SCREAMING_SNAKE_CASE       (				snake_case_      :							Union[str, Any]     ):
 snake_case__				:   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











import argparse
import re
from typing import Dict

import torch
from datasets import Audio, Dataset, load_dataset, load_metric

from transformers import AutoFeatureExtractor, pipeline







def   SCREAMING_SNAKE_CASE       (				snake_case_      :							Dataset  ,						snake_case_      :							Dict[str, str]     ):
	snake_case__				:   Tuple     =						args.log_outputs
	snake_case__				:   Union[str, Any]     =						"_".join(args.dataset.split("/"     ) + [args.config, args.split]     )

	# load metric
	snake_case__				:   List[str]     =						load_metric("wer"     )
	snake_case__				:   List[str]     =						load_metric("cer"     )

	# compute metrics
	snake_case__				:   List[Any]     =						wer.compute(references=result["target"]  ,						predictions=result["prediction"]     )
	snake_case__				:   List[str]     =						cer.compute(references=result["target"]  ,						predictions=result["prediction"]     )

	# print & log results
	snake_case__				:   Dict     =						F'''WER: {wer_result}\nCER: {cer_result}'''
	print(snake_case_     )

	with open(F'''{dataset_id}_eval_results.txt'''  ,						"w"     ) as f:
		f.write(snake_case_     )

	# log all results in text file. Possibly interesting for analysis
	if log_outputs is not None:
		snake_case__				:   Union[str, Any]     =						F'''log_{dataset_id}_predictions.txt'''
		snake_case__				:   int     =						F'''log_{dataset_id}_targets.txt'''

		with open(snake_case_  ,						"w"     ) as p, open(snake_case_  ,						"w"     ) as t:
			# mapping function to write output
			def write_to_file(snake_case_      :							Union[str, Any]  ,						snake_case_      :							Any     ):
				p.write(F'''{i}''' + "\n"     )
				p.write(batch["prediction"] + "\n"     )
				t.write(F'''{i}''' + "\n"     )
				t.write(batch["target"] + "\n"     )

			result.map(snake_case_  ,						with_indices=snake_case_     )







def   SCREAMING_SNAKE_CASE       (				snake_case_      :							str     ):
	snake_case__				:   List[Any]     =						"[,?.!\-\;\:\"“%‘”�—’…–]"  # noqa: W605 IMPORTANT: this should correspond to the chars that were ignored during training

	snake_case__				:   Optional[int]     =						re.sub(snake_case_  ,						""  ,						text.lower()     )

	# In addition, we can normalize the target text, e.g. removing new lines characters etc...
	# note that order is important here!
	snake_case__				:   Optional[Any]     =						["\n\n", "\n", "   ", "  "]

	for t in token_sequences_to_ignore:
		snake_case__				:   Optional[int]     =						" ".join(text.split(snake_case_     )     )

	return text







def   SCREAMING_SNAKE_CASE       (				snake_case_      :							int     ):
	# load dataset
	snake_case__				:   int     =						load_dataset(args.dataset  ,						args.config  ,						split=args.split  ,						use_auth_token=snake_case_     )

	# for testing: only process the first two examples as a test
	# dataset = dataset.select(range(10))

	# load processor
	snake_case__				:   List[str]     =						AutoFeatureExtractor.from_pretrained(args.model_id     )
	snake_case__				:   List[Any]     =						feature_extractor.sampling_rate

	# resample audio
	snake_case__				:   Dict     =						dataset.cast_column("audio"  ,						Audio(sampling_rate=snake_case_     )     )

	# load eval pipeline
	if args.device is None:
		snake_case__				:   int     =						0 if torch.cuda.is_available() else -1
	snake_case__				:   List[str]     =						pipeline("automatic-speech-recognition"  ,						model=args.model_id  ,						device=args.device     )

	# map function to decode audio
	def map_to_pred(snake_case_      :							Any     ):
		snake_case__				:   Union[str, Any]     =						asr(
		    batch["audio"]["array"]  ,						chunk_length_s=args.chunk_length_s  ,						stride_length_s=args.stride_length_s     )

		snake_case__				:   Optional[int]     =						prediction["text"]
		snake_case__				:   Optional[Any]     =						normalize_text(batch["sentence"]     )
		return batch

	# run inference on all examples
	snake_case__				:   Any     =						dataset.map(snake_case_  ,						remove_columns=dataset.column_names     )

	# compute and log_results
	# do not change function below
	log_results(snake_case_  ,						snake_case_     )


if __name__ == "__main__":
	__lowerCamelCase      :    Dict   		=   argparse.ArgumentParser()

	parser.add_argument(
	    """--model_id""", type=str, required=True, help="""Model identifier. Should be loadable with 🤗 Transformers"""
	)
	parser.add_argument(
	    """--dataset""",
	    type=str,
	    required=True,
	    help="""Dataset name to evaluate the `model_id`. Should be loadable with 🤗 Datasets""",
	)
	parser.add_argument(
	    """--config""", type=str, required=True, help="""Config of the dataset. *E.g.* `'en'`  for Common Voice"""
	)
	parser.add_argument("""--split""", type=str, required=True, help="""Split of the dataset. *E.g.* `'test'`""")
	parser.add_argument(
	    """--chunk_length_s""", type=float, default=None, help="""Chunk length in seconds. Defaults to 5 seconds."""
	)
	parser.add_argument(
	    """--stride_length_s""", type=float, default=None, help="""Stride of the audio chunks. Defaults to 1 second."""
	)
	parser.add_argument(
	    """--log_outputs""", action="""store_true""", help="""If defined, write outputs to log file for analysis."""
	)
	parser.add_argument(
	    """--device""",
	    type=int,
	    default=None,
	    help="""The device to run the pipeline on. -1 for CPU (default), 0 for the first GPU and so on.""",
	)
	__lowerCamelCase      :    str   		=   parser.parse_args()

	main(args)



