






"""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   lowerCAmelCase_( SCREAMING_SNAKE_CASE					)					->	List[Any]:
				"""simple docstring"""

				UpperCamelCase__         =    tmp_path / 'file.csv'
				UpperCamelCase__         =    textwrap.dedent(
				    '\\n        header1,header2\n        1,2\n        10,20\n        '					)
				with open(SCREAMING_SNAKE_CASE ,	'w'					) as f:
								f.write(SCREAMING_SNAKE_CASE					)
				return str(SCREAMING_SNAKE_CASE					)







@pytest.fixture
def   lowerCAmelCase_( SCREAMING_SNAKE_CASE					)					->	List[Any]:
				"""simple docstring"""

				UpperCamelCase__         =    tmp_path / 'malformed_file.csv'
				UpperCamelCase__         =    textwrap.dedent(
				    '\\n        header1,header2\n        1,2\n        10,20,\n        '					)
				with open(SCREAMING_SNAKE_CASE ,	'w'					) as f:
								f.write(SCREAMING_SNAKE_CASE					)
				return str(SCREAMING_SNAKE_CASE					)







@pytest.fixture
def   lowerCAmelCase_( SCREAMING_SNAKE_CASE ,	SCREAMING_SNAKE_CASE					)					->	int:
				"""simple docstring"""

				UpperCamelCase__         =    tmp_path / 'csv_with_image.csv'
				UpperCamelCase__         =    textwrap.dedent(
				    F'\\n        image\n        {image_file}\n        '					)
				with open(SCREAMING_SNAKE_CASE ,	'w'					) as f:
								f.write(SCREAMING_SNAKE_CASE					)
				return str(SCREAMING_SNAKE_CASE					)







@pytest.fixture
def   lowerCAmelCase_( SCREAMING_SNAKE_CASE					)					->	List[Any]:
				"""simple docstring"""

				UpperCamelCase__         =    tmp_path / 'csv_with_label.csv'
				UpperCamelCase__         =    textwrap.dedent(
				    '\\n        label\n        good\n        bad\n        good\n        '					)
				with open(SCREAMING_SNAKE_CASE ,	'w'					) as f:
								f.write(SCREAMING_SNAKE_CASE					)
				return str(SCREAMING_SNAKE_CASE					)







@pytest.fixture
def   lowerCAmelCase_( SCREAMING_SNAKE_CASE					)					->	str:
				"""simple docstring"""

				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(SCREAMING_SNAKE_CASE ,	'w'					) as f:
								f.write(SCREAMING_SNAKE_CASE					)
				return str(SCREAMING_SNAKE_CASE					)







def   lowerCAmelCase_( SCREAMING_SNAKE_CASE ,	SCREAMING_SNAKE_CASE ,	SCREAMING_SNAKE_CASE					)					->	Dict:
				"""simple docstring"""

				UpperCamelCase__         =    Csv()
				UpperCamelCase__         =    csv._generate_tables([[csv_file, malformed_csv_file]]					)
				with pytest.raises(SCREAMING_SNAKE_CASE ,	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(SCREAMING_SNAKE_CASE					) in record.message
				    for record in caplog.records					)







@require_pil
def   lowerCAmelCase_( SCREAMING_SNAKE_CASE					)					->	List[Any]:
				"""simple docstring"""

				with open(SCREAMING_SNAKE_CASE ,	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   lowerCAmelCase_( SCREAMING_SNAKE_CASE					)					->	Dict:
				"""simple docstring"""

				with open(SCREAMING_SNAKE_CASE ,	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(SCREAMING_SNAKE_CASE					) for label in labels]







def   lowerCAmelCase_( SCREAMING_SNAKE_CASE					)					->	Dict:
				"""simple docstring"""

				UpperCamelCase__         =    Csv(encoding='utf-8' ,	sep=',' ,	converters={'int_list': lambda SCREAMING_SNAKE_CASE					: [int(SCREAMING_SNAKE_CASE					) 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]]












"""simple docstring"""





import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union

import transformers
from transformers.testing_utils import require_tf, require_torch, slow


A__					: Union[str, Any]=	logging.getLogger()
@unittest.skip("""Temporarily disable the doc tests."""  )
@require_torch
@require_tf
@slow
class    __lowerCamelCase    (  unittest.TestCase  ):

   def 						SCREAMING_SNAKE_CASE__ (					self ,				snake_case_ ,				snake_case_ = None ,				snake_case_ = None ,				snake_case_ = None ,				snake_case_ = True ,				)		->       Tuple:
       UpperCamelCase__         =    [file for file in os.listdir(snake_case_      ) if os.path.isfile(os.path.join(snake_case_ ,				snake_case_      )      )]

       if identifier is not None:
           UpperCamelCase__         =    [file for file in files if identifier in file]

       if n_identifier is not None:
           if isinstance(snake_case_ ,				snake_case_      ):
               for n_ in n_identifier:
                   UpperCamelCase__         =    [file for file in files if n_ not in file]
           else:
               UpperCamelCase__         =    [file for file in files if n_identifier not in file]

       UpperCamelCase__         =    ignore_files or []
       ignore_files.append('__init__.py'      )
       UpperCamelCase__         =    [file for file in files if file not in ignore_files]

       for file in files:
           # Open all files
           print('Testing' ,				snake_case_      )

           if only_modules:
               UpperCamelCase__         =    file.split('.'      )[0]
               try:
                   UpperCamelCase__         =    getattr(snake_case_ ,				snake_case_      )
                   UpperCamelCase__         =    doctest.DocTestSuite(snake_case_      )
                   UpperCamelCase__         =    unittest.TextTestRunner().run(snake_case_      )
                   self.assertIs(len(result.failures      ) ,				0      )
               except AttributeError:
                   logger.info(F'{module_identifier} is not a module.'      )
           else:
               UpperCamelCase__         =    doctest.testfile(str('..' / directory / file      ) ,				optionflags=doctest.ELLIPSIS      )
               self.assertIs(result.failed ,				0      )

   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       Union[str, Any]:
       UpperCamelCase__         =    Path('src/transformers'      )
       UpperCamelCase__         =    'modeling'
       UpperCamelCase__         =    [
           'modeling_ctrl.py',
           'modeling_tf_ctrl.py',
       ]
       self.analyze_directory(snake_case_ ,				identifier=snake_case_ ,				ignore_files=snake_case_      )

   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       Optional[int]:
       UpperCamelCase__         =    Path('src/transformers'      )
       UpperCamelCase__         =    'tokenization'
       self.analyze_directory(snake_case_ ,				identifier=snake_case_      )

   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       Optional[Any]:
       UpperCamelCase__         =    Path('src/transformers'      )
       UpperCamelCase__         =    'configuration'
       self.analyze_directory(snake_case_ ,				identifier=snake_case_      )

   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       str:
       UpperCamelCase__         =    Path('src/transformers'      )
       UpperCamelCase__         =    ['configuration', 'modeling', 'tokenization']
       self.analyze_directory(snake_case_ ,				n_identifier=snake_case_      )







   def 						SCREAMING_SNAKE_CASE__ (					self      )		->       Union[str, Any]:
       UpperCamelCase__         =    Path('docs/source'      )
       UpperCamelCase__         =    ['favicon.ico']
       self.analyze_directory(snake_case_ ,				ignore_files=snake_case_ ,				only_modules=snake_case_      )




