




import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union

import pandas as pd
import pyarrow as pa

import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from datasets.utils.py_utils import Literal


a_		:						Optional[int]             =    datasets.utils.logging.get_logger(__name__)

a_		:						Union[str, Any]             =    ['names', 'prefix']
a_		:						Union[str, Any]             =    ['warn_bad_lines', 'error_bad_lines', 'mangle_dupe_cols']
a_		:						List[Any]             =    ['encoding_errors', 'on_bad_lines']
a_		:						Tuple             =    ['date_format']

@dataclass
class 		_snake_case  (  datasets.BuilderConfig					):
			_lowercase		:    str			     =							","
			_lowercase		:    Optional[str]			     =							None
			_lowercase		:    Optional[Union[int, List[int], str]]			     =							"infer"
			_lowercase		:    Optional[List[str]]			     =							None
			_lowercase		:    Optional[List[str]]			     =							None
			_lowercase		:    Optional[Union[int, str, List[int], List[str]]]			     =							None
			_lowercase		:    Optional[Union[List[int], List[str]]]			     =							None
			_lowercase		:    Optional[str]			     =							None
			_lowercase		:    bool			     =							True
			_lowercase		:    Optional[Literal["c", "python", "pyarrow"]]			     =							None
			_lowercase		:    Dict[Union[int, str], Callable[[Any], Any]]			     =							None
			_lowercase		:    Optional[list]			     =							None
			_lowercase		:    Optional[list]			     =							None
			_lowercase		:    bool			     =							False
			_lowercase		:    Optional[Union[int, List[int]]]			     =							None
			_lowercase		:    Optional[int]			     =							None
			_lowercase		:    Optional[Union[str, List[str]]]			     =							None
			_lowercase		:    bool			     =							True
			_lowercase		:    bool			     =							True
			_lowercase		:    bool			     =							False
			_lowercase		:    bool			     =							True
			_lowercase		:    Optional[str]			     =							None
			_lowercase		:    str			     =							"."
			_lowercase		:    Optional[str]			     =							None
			_lowercase		:    str			     =							'"'
			_lowercase		:    int			     =							0
			_lowercase		:    Optional[str]			     =							None
			_lowercase		:    Optional[str]			     =							None
			_lowercase		:    Optional[str]			     =							None
			_lowercase		:    Optional[str]			     =							None
			_lowercase		:    bool			     =							True
			_lowercase		:    bool			     =							True
			_lowercase		:    int			     =							0
			_lowercase		:    bool			     =							True
			_lowercase		:    bool			     =							False
			_lowercase		:    Optional[str]			     =							None
			_lowercase		:    int			     =							1_00_00
			_lowercase		:    Optional[datasets.Features]			     =							None
			_lowercase		:    Optional[str]			     =							"strict"
			_lowercase		:    Literal["error", "warn", "skip"]			     =							"error"
			_lowercase		:    Optional[str]			     =							None






			def    SCREAMING_SNAKE_CASE__    (       self)      ->       Dict:
						if self.delimiter is not None:
									SCREAMING_SNAKE_CASE						= self.delimiter
						if self.column_names is not None:
									SCREAMING_SNAKE_CASE						= self.column_names







			@property
			def    SCREAMING_SNAKE_CASE__    (       self)      ->       int:
						SCREAMING_SNAKE_CASE						= {
						    'sep': self.sep,
						    'header': self.header,
						    'names': self.names,
						    'index_col': self.index_col,
						    'usecols': self.usecols,
						    'prefix': self.prefix,
						    'mangle_dupe_cols': self.mangle_dupe_cols,
						    'engine': self.engine,
						    'converters': self.converters,
						    'true_values': self.true_values,
						    'false_values': self.false_values,
						    'skipinitialspace': self.skipinitialspace,
						    'skiprows': self.skiprows,
						    'nrows': self.nrows,
						    'na_values': self.na_values,
						    'keep_default_na': self.keep_default_na,
						    'na_filter': self.na_filter,
						    'verbose': self.verbose,
						    'skip_blank_lines': self.skip_blank_lines,
						    'thousands': self.thousands,
						    'decimal': self.decimal,
						    'lineterminator': self.lineterminator,
						    'quotechar': self.quotechar,
						    'quoting': self.quoting,
						    'escapechar': self.escapechar,
						    'comment': self.comment,
						    'encoding': self.encoding,
						    'dialect': self.dialect,
						    'error_bad_lines': self.error_bad_lines,
						    'warn_bad_lines': self.warn_bad_lines,
						    'skipfooter': self.skipfooter,
						    'doublequote': self.doublequote,
						    'memory_map': self.memory_map,
						    'float_precision': self.float_precision,
						    'chunksize': self.chunksize,
						    'encoding_errors': self.encoding_errors,
						    'on_bad_lines': self.on_bad_lines,
						    'date_format': self.date_format,
						}

						# some kwargs must not be passed if they don't have a default value
						# some others are deprecated and we can also not pass them if they are the default value
						for pd_read_csv_parameter in _PANDAS_READ_CSV_NO_DEFAULT_PARAMETERS + _PANDAS_READ_CSV_DEPRECATED_PARAMETERS:
									if pd_read_csv_kwargs[pd_read_csv_parameter] == getattr(CsvConfig()		,					a):
												del pd_read_csv_kwargs[pd_read_csv_parameter]

        # Remove 2.0 new arguments
						if not (datasets.config.PANDAS_VERSION.major >= 2):
									for pd_read_csv_parameter in _PANDAS_READ_CSV_NEW_2_0_0_PARAMETERS:
												del pd_read_csv_kwargs[pd_read_csv_parameter]

        # Remove 1.3 new arguments
						if not (datasets.config.PANDAS_VERSION.major >= 1 and datasets.config.PANDAS_VERSION.minor >= 3):
									for pd_read_csv_parameter in _PANDAS_READ_CSV_NEW_1_3_0_PARAMETERS:
												del pd_read_csv_kwargs[pd_read_csv_parameter]

						return pd_read_csv_kwargs



class 		_snake_case  (  datasets.ArrowBasedBuilder					):
			_lowercase		:    Dict			     =							CsvConfig






			def    SCREAMING_SNAKE_CASE__    (       self)      ->       Union[str, Any]:
						return datasets.DatasetInfo(features=self.config.features)






			def    SCREAMING_SNAKE_CASE__    (       self		,					a)      ->       str:
						if not self.config.data_files:
									raise ValueError(f'''At least one data file must be specified, but got data_files={self.config.data_files}''')
						SCREAMING_SNAKE_CASE						= dl_manager.download_and_extract(self.config.data_files)
						if isinstance(a		,					(str, list, tuple)):
									SCREAMING_SNAKE_CASE						= data_files
									if isinstance(a		,					a):
												SCREAMING_SNAKE_CASE						= [files]
									SCREAMING_SNAKE_CASE						= [dl_manager.iter_files(a) for file in files]
									return [datasets.SplitGenerator(name=datasets.Split.TRAIN		,					gen_kwargs={'files': files})]
						SCREAMING_SNAKE_CASE						= []
						for split_name, files in data_files.items():
									if isinstance(a		,					a):
												SCREAMING_SNAKE_CASE						= [files]
									SCREAMING_SNAKE_CASE						= [dl_manager.iter_files(a) for file in files]
									splits.append(datasets.SplitGenerator(name=a		,					gen_kwargs={'files': files}))
						return splits






			def    SCREAMING_SNAKE_CASE__    (       self		,					a)      ->       pa.Table:
						if self.config.features is not None:
									SCREAMING_SNAKE_CASE						= self.config.features.arrow_schema
									if all(not require_storage_cast(a) for feature in self.config.features.values()):
												# cheaper cast
												SCREAMING_SNAKE_CASE						= pa.Table.from_arrays([pa_table[field.name] for field in schema]		,					schema=a)
									else:
												# more expensive cast; allows str <-> int/float or str to Audio for example
												SCREAMING_SNAKE_CASE						= table_cast(a		,					a)
						return pa_table







			def    SCREAMING_SNAKE_CASE__    (       self		,					a)      ->       Dict:
						SCREAMING_SNAKE_CASE						= self.config.features.arrow_schema if self.config.features else None
						# dtype allows reading an int column as str
						SCREAMING_SNAKE_CASE						= (
						    {
						        name: dtype.to_pandas_dtype() if not require_storage_cast(a) else object
						        for name, dtype, feature in zip(schema.names		,					schema.types		,					self.config.features.values())
						    }
						    if schema is not None
						    else None
						)
						for file_idx, file in enumerate(itertools.chain.from_iterable(a)):
									SCREAMING_SNAKE_CASE						= pd.read_csv(a		,					iterator=a		,					dtype=a		,					**self.config.pd_read_csv_kwargs)
									try:
												for batch_idx, df in enumerate(a):
															SCREAMING_SNAKE_CASE						= pa.Table.from_pandas(a)
															# Uncomment for debugging (will print the Arrow table size and elements)
															# logger.warning(f"pa_table: {pa_table} num rows: {pa_table.num_rows}")
															# logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
															yield (file_idx, batch_idx), self._cast_table(a)
									except ValueError as e:
												logger.error(f'''Failed to read file \'{file}\' with error {type(a)}: {e}''')
												raise












# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run

import doctest
import sys
import warnings
from os.path import abspath, dirname, join

import _pytest

from transformers.testing_utils import HfDoctestModule, HfDocTestParser


# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checkouts and running tests.
a_		:						List[str]             =    abspath(join(dirname(__file__), 'src'))
sys.path.insert(1, git_repo_path)

# silence FutureWarning warnings in tests since often we can't act on them until
# they become normal warnings - i.e. the tests still need to test the current functionality
warnings.simplefilter(action='ignore', category=FutureWarning)






def 				lowerCamelCase__				(_UpperCAmelCase):
			config.addinivalue_line(
			    'markers'							,       'is_pt_tf_cross_test: mark test to run only when PT and TF interactions are tested')
			config.addinivalue_line(
			    'markers'							,       'is_pt_flax_cross_test: mark test to run only when PT and FLAX interactions are tested')
			config.addinivalue_line('markers'							,       'is_pipeline_test: mark test to run only when pipelines are tested')
			config.addinivalue_line('markers'							,       'is_staging_test: mark test to run only in the staging environment')
			config.addinivalue_line('markers'							,       'accelerate_tests: mark test that require accelerate')
			config.addinivalue_line('markers'							,       'tool_tests: mark the tool tests that are run on their specific schedule')






def 				lowerCamelCase__				(_UpperCAmelCase):
			from transformers.testing_utils import pytest_addoption_shared

			pytest_addoption_shared(_UpperCAmelCase)






def 				lowerCamelCase__				(_UpperCAmelCase):
			from transformers.testing_utils import pytest_terminal_summary_main

			SCREAMING_SNAKE_CASE						= terminalreporter.config.getoption('--make-reports')
			if make_reports:
						pytest_terminal_summary_main(_UpperCAmelCase							,       id=_UpperCAmelCase)






def 				lowerCamelCase__				(_UpperCAmelCase							,       _UpperCAmelCase):
			# If no tests are collected, pytest exists with code 5, which makes the CI fail.
			if exitstatus == 5:
						SCREAMING_SNAKE_CASE						= 0


# Doctest custom flag to ignore output.
a_		:						List[Any]             =    doctest.register_optionflag('IGNORE_RESULT')

a_		:						Any             =    doctest.OutputChecker

class 		_snake_case  (  A__					):






			def    SCREAMING_SNAKE_CASE__    (       self		,					a		,					a		,					a)      ->       List[Any]:
						if IGNORE_RESULT & optionflags:
									return True
						return OutputChecker.check_output(self		,					a		,					a		,					a)



a_		:						int             =    CustomOutputChecker
a_		:						List[str]             =    HfDoctestModule







a_		:						Optional[int]             =    HfDocTestParser




