





'''simple docstring'''






import os
import textwrap

import pyarrow as pa
import pytest

from datasets import ClassLabel, Features, Image
from datasets.packaged_modules.csv.csv import Csv

from ..utils import require_pil






@pytest.fixture
def      __A						(							a_						:  Dict	):
		lowerCAmelCase     :    List[Any]						=   tmp_path / "file.csv"
		lowerCAmelCase     :    Any						=   textwrap.dedent(
		    "\\n        header1,header2\n        1,2\n        10,20\n        "	)
		with open(a_      ,"w"	) as f:
				f.write(a_	)
		return str(a_	)






@pytest.fixture
def      __A						(							a_						:  List[str]	):
		lowerCAmelCase     :    Optional[Any]						=   tmp_path / "malformed_file.csv"
		lowerCAmelCase     :    Any						=   textwrap.dedent(
		    "\\n        header1,header2\n        1,2\n        10,20,\n        "	)
		with open(a_      ,"w"	) as f:
				f.write(a_	)
		return str(a_	)






@pytest.fixture
def      __A						(							a_						:  Union[str, Any]      ,a_						:  Union[str, Any]	):
		lowerCAmelCase     :    List[Any]						=   tmp_path / "csv_with_image.csv"
		lowerCAmelCase     :    Union[str, Any]						=   textwrap.dedent(
		    f'''\
        image
        {image_file}
        '''	)
		with open(a_      ,"w"	) as f:
				f.write(a_	)
		return str(a_	)






@pytest.fixture
def      __A						(							a_						:  List[Any]	):
		lowerCAmelCase     :    List[str]						=   tmp_path / "csv_with_label.csv"
		lowerCAmelCase     :    Union[str, Any]						=   textwrap.dedent(
		    "\\n        label\n        good\n        bad\n        good\n        "	)
		with open(a_      ,"w"	) as f:
				f.write(a_	)
		return str(a_	)






@pytest.fixture
def      __A						(							a_						:  Tuple	):
		lowerCAmelCase     :    Any						=   tmp_path / "csv_with_int_list.csv"
		lowerCAmelCase     :    Dict						=   textwrap.dedent(
		    "\\n        int_list\n        1 2 3\n        4 5 6\n        7 8 9\n        "	)
		with open(a_      ,"w"	) as f:
				f.write(a_	)
		return str(a_	)






def      __A						(							a_						:  Tuple      ,a_						:  Tuple      ,a_						:  Any	):
		lowerCAmelCase     :    Union[str, Any]						=   Csv()
		lowerCAmelCase     :    List[str]						=   csv._generate_tables([[csv_file, malformed_csv_file]]	)
		with pytest.raises(a_      ,match="Error tokenizing data"	):
				for _ in generator:
						pass
		assert any(
		    record.levelname == "ERROR"
		    and "Failed to read file" in record.message
		    and os.path.basename(a_	) in record.message
		    for record in caplog.records	)






@require_pil
def      __A						(							a_						:  Optional[Any]	):
		with open(a_      ,encoding="utf-8"	) as f:
				lowerCAmelCase     :    Any						=   f.read().splitlines()[1]
		lowerCAmelCase     :    Optional[int]						=   Csv(encoding="utf-8"      ,features=Features({"image": Image()}	)	)
		lowerCAmelCase     :    int						=   csv._generate_tables([[csv_file_with_image]]	)
		lowerCAmelCase     :    List[str]						=   pa.concat_tables([table for _, table in generator]	)
		assert pa_table.schema.field("image"	).type == Image()()
		lowerCAmelCase     :    Optional[Any]						=   pa_table.to_pydict()["image"]
		assert generated_content == [{"path": image_file, "bytes": None}]






def      __A						(							a_						:  Optional[int]	):
		with open(a_      ,encoding="utf-8"	) as f:
				lowerCAmelCase     :    Dict						=   f.read().splitlines()[1:]
		lowerCAmelCase     :    int						=   Csv(encoding="utf-8"      ,features=Features({"label": ClassLabel(names=["good", "bad"]	)}	)	)
		lowerCAmelCase     :    Dict						=   csv._generate_tables([[csv_file_with_label]]	)
		lowerCAmelCase     :    Union[str, Any]						=   pa.concat_tables([table for _, table in generator]	)
		assert pa_table.schema.field("label"	).type == ClassLabel(names=["good", "bad"]	)()
		lowerCAmelCase     :    Any						=   pa_table.to_pydict()["label"]
		assert generated_content == [ClassLabel(names=["good", "bad"]	).straint(a_	) for label in labels]






def      __A						(							a_						:  int	):
		lowerCAmelCase     :    List[Any]						=   Csv(encoding="utf-8"      ,sep=","      ,converters={"int_list": lambda a_	: [int(a_	) for i in x.split()]}	)
		lowerCAmelCase     :    Optional[Any]						=   csv._generate_tables([[csv_file_with_int_list]]	)
		lowerCAmelCase     :    Any						=   pa.concat_tables([table for _, table in generator]	)
		assert pa.types.is_list(pa_table.schema.field("int_list"	).type	)
		lowerCAmelCase     :    Union[str, Any]						=   pa_table.to_pydict()["int_list"]
		assert generated_content == [[1, 2, 3], [4, 5, 6], [7, 8, 9]]










'''simple docstring'''






import warnings

from ...utils import logging
from .image_processing_chinese_clip import ChineseCLIPImageProcessor


lowerCAmelCase       		=      logging.get_logger(__name__)
class 		lowerCamelCase  (      _A       ):



	def __init__(   self		,      *a_		,      **a_	):
			warnings.warn(
			    "The class ChineseCLIPFeatureExtractor is deprecated and will be removed in version 5 of Transformers."
			    " Please use ChineseCLIPImageProcessor instead."		,      a_		,      )
			super().__init__(*a_		,      **a_	)



