


"""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        lowercase							(		lowerCAmelCase__ :     Optional[Any]			) ->      Optional[int]:
		__a           =			tmp_path / '''file.csv'''
		__a           =			textwrap.dedent(
		    '''\
        header1,header2
        1,2
        10,20
        '''			)
		with open(lowerCAmelCase__    ,					'''w'''			) as f:
				f.write(lowerCAmelCase__			)
		return str(lowerCAmelCase__			)

@pytest.fixture
def        lowercase							(		lowerCAmelCase__ :     str			) ->      Any:
		__a           =			tmp_path / '''malformed_file.csv'''
		__a           =			textwrap.dedent(
		    '''\
        header1,header2
        1,2
        10,20,
        '''			)
		with open(lowerCAmelCase__    ,					'''w'''			) as f:
				f.write(lowerCAmelCase__			)
		return str(lowerCAmelCase__			)

@pytest.fixture
def        lowercase							(		lowerCAmelCase__ :     Optional[int]    ,					lowerCAmelCase__ :     Any			) ->      List[str]:
		__a           =			tmp_path / '''csv_with_image.csv'''
		__a           =			textwrap.dedent(
		    f'''\
        image
        {image_file}
        '''			)
		with open(lowerCAmelCase__    ,					'''w'''			) as f:
				f.write(lowerCAmelCase__			)
		return str(lowerCAmelCase__			)

@pytest.fixture
def        lowercase							(		lowerCAmelCase__ :     Dict			) ->      Union[str, Any]:
		__a           =			tmp_path / '''csv_with_label.csv'''
		__a           =			textwrap.dedent(
		    '''\
        label
        good
        bad
        good
        '''			)
		with open(lowerCAmelCase__    ,					'''w'''			) as f:
				f.write(lowerCAmelCase__			)
		return str(lowerCAmelCase__			)

@pytest.fixture
def        lowercase							(		lowerCAmelCase__ :     Optional[int]			) ->      List[str]:
		__a           =			tmp_path / '''csv_with_int_list.csv'''
		__a           =			textwrap.dedent(
		    '''\
        int_list
        1 2 3
        4 5 6
        7 8 9
        '''			)
		with open(lowerCAmelCase__    ,					'''w'''			) as f:
				f.write(lowerCAmelCase__			)
		return str(lowerCAmelCase__			)

def        lowercase							(		lowerCAmelCase__ :     Optional[int]    ,					lowerCAmelCase__ :     int    ,					lowerCAmelCase__ :     Any			) ->      Tuple:
		__a           =			Csv()
		__a           =			csv._generate_tables([[csv_file, malformed_csv_file]]			)
		with pytest.raises(lowerCAmelCase__    ,					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(lowerCAmelCase__			) in record.message
		    for record in caplog.records			)

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

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




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










"""simple docstring"""




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


lowercase_			     =  {"configuration_unispeech": ["UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP", "UniSpeechConfig"]}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase_			     =  [
				    "UNISPEECH_PRETRAINED_MODEL_ARCHIVE_LIST",
				    "UniSpeechForCTC",
				    "UniSpeechForPreTraining",
				    "UniSpeechForSequenceClassification",
				    "UniSpeechModel",
				    "UniSpeechPreTrainedModel",
				]

if TYPE_CHECKING:
				from .configuration_unispeech import UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP, UniSpeechConfig

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_unispeech import (
								    UNISPEECH_PRETRAINED_MODEL_ARCHIVE_LIST,
								    UniSpeechForCTC,
								    UniSpeechForPreTraining,
								    UniSpeechForSequenceClassification,
								    UniSpeechModel,
								    UniSpeechPreTrainedModel,
								)

else:
				import sys

				lowercase_			     =  _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)






