


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 						_UpperCAmelCase    (      SCREAMING_SNAKE_CASE__      : Tuple    ):
     __UpperCamelCase   							=tmp_path / """file.csv"""
     __UpperCamelCase   							=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 						_UpperCAmelCase    (      SCREAMING_SNAKE_CASE__      : Optional[Any]    ):
     __UpperCamelCase   							=tmp_path / """malformed_file.csv"""
     __UpperCamelCase   							=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 						_UpperCAmelCase    (      SCREAMING_SNAKE_CASE__      : Any      ,					SCREAMING_SNAKE_CASE__      : List[Any]    ):
     __UpperCamelCase   							=tmp_path / """csv_with_image.csv"""
     __UpperCamelCase   							=textwrap.dedent(
         F'\\n        image\n        {image_file}\n        '    )
     with open(_a      ,					'w'    ) as f:
          f.write(_a    )
     return str(_a    )

@pytest.fixture
def 						_UpperCAmelCase    (      SCREAMING_SNAKE_CASE__      : Optional[int]    ):
     __UpperCamelCase   							=tmp_path / """csv_with_label.csv"""
     __UpperCamelCase   							=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 						_UpperCAmelCase    (      SCREAMING_SNAKE_CASE__      : Any    ):
     __UpperCamelCase   							=tmp_path / """csv_with_int_list.csv"""
     __UpperCamelCase   							=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 						_UpperCAmelCase    (      SCREAMING_SNAKE_CASE__      : List[str]      ,					SCREAMING_SNAKE_CASE__      : Optional[int]      ,					SCREAMING_SNAKE_CASE__      : Dict    ):
     __UpperCamelCase   							=Csv()
     __UpperCamelCase   							=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 						_UpperCAmelCase    (      SCREAMING_SNAKE_CASE__      : List[Any]    ):




     with open(_a      ,					encoding='utf-8'    ) as f:
          __UpperCamelCase   							=f.read().splitlines()[1]
     __UpperCamelCase   							=Csv(encoding='utf-8'      ,					features=Features({'image': Image()}    )    )
     __UpperCamelCase   							=csv._generate_tables([[csv_file_with_image]]    )
     __UpperCamelCase   							=pa.concat_tables([table for _, table in generator]    )
     assert pa_table.schema.field('image'    ).type == Image()()
     __UpperCamelCase   							=pa_table.to_pydict()["""image"""]
     assert generated_content == [{"path": image_file, "bytes": None}]

def 						_UpperCAmelCase    (      SCREAMING_SNAKE_CASE__      : int    ):




     with open(_a      ,					encoding='utf-8'    ) as f:
          __UpperCamelCase   							=f.read().splitlines()[1:]
     __UpperCamelCase   							=Csv(encoding='utf-8'      ,					features=Features({'label': ClassLabel(names=['good', 'bad']    )}    )    )
     __UpperCamelCase   							=csv._generate_tables([[csv_file_with_label]]    )
     __UpperCamelCase   							=pa.concat_tables([table for _, table in generator]    )
     assert pa_table.schema.field('label'    ).type == ClassLabel(names=['good', 'bad']    )()
     __UpperCamelCase   							=pa_table.to_pydict()["""label"""]
     assert generated_content == [ClassLabel(names=['good', 'bad']    ).straint(_a    ) for label in labels]





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



from ....utils import logging


_A			=						logging.get_logger(__name__)






class    UpperCAmelCase__	( A_		):



    """simple docstring"""






    def __init__(      self ,       A_ ,       A_=None ,       A_=2048   )  ->	Any:
         __UpperCamelCase   							=config.__dict__
         __UpperCamelCase   							=modal_hidden_size
         if num_labels:
              __UpperCamelCase   							=num_labels





