

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


_lowerCAmelCase			:						Optional[Any]  					=     datasets.utils.logging.get_logger(__name__)

_lowerCAmelCase			:						Any  					=     ['names', 'prefix']
_lowerCAmelCase			:						Tuple  					=     ['warn_bad_lines', 'error_bad_lines', 'mangle_dupe_cols']
_lowerCAmelCase			:						Dict  					=     ['encoding_errors', 'on_bad_lines']
_lowerCAmelCase			:						str  					=     ['date_format']


@dataclass
class      lowerCAmelCase					(     datasets.BuilderConfig					):


       '''simple docstring'''







       snake_case     				=						','
       snake_case     				=						None
       snake_case     				=						'infer'
       snake_case     				=						None
       snake_case     				=						None
       snake_case     				=						None
       snake_case     				=						None
       snake_case     				=						None
       snake_case     				=						True
       snake_case     				=						None
       snake_case     				=						None
       snake_case     				=						None
       snake_case     				=						None
       snake_case     				=						False
       snake_case     				=						None
       snake_case     				=						None
       snake_case     				=						None
       snake_case     				=						True
       snake_case     				=						True
       snake_case     				=						False
       snake_case     				=						True
       snake_case     				=						None
       snake_case     				=						'.'
       snake_case     				=						None
       snake_case     				=						'"'
       snake_case     				=						0
       snake_case     				=						None
       snake_case     				=						None
       snake_case     				=						None
       snake_case     				=						None
       snake_case     				=						True
       snake_case     				=						True
       snake_case     				=						0
       snake_case     				=						True
       snake_case     				=						False
       snake_case     				=						None
       snake_case     				=						10_000
       snake_case     				=						None
       snake_case     				=						'strict'
       snake_case     				=						'error'
       snake_case     				=						None

       def 	lowerCamelCase__    (						self       :	Tuple  ) ->			List[str]:







        '''simple docstring'''

        if self.delimiter is not None:
         lowerCamelCase       =     self.delimiter
        if self.column_names is not None:
         lowerCamelCase       =     self.column_names





       @property
       def 	lowerCamelCase__    (						self       :	Union[str, Any]  ) ->			Tuple:







        '''simple docstring'''

        lowerCamelCase       =     {
            '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()    ,						__lowerCamelCase  ):
          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      lowerCAmelCase					(     datasets.ArrowBasedBuilder					):


       '''simple docstring'''







       snake_case     				=						CsvConfig

       def 	lowerCamelCase__    (						self       :	int  ) ->			int:







        '''simple docstring'''

        return datasets.DatasetInfo(features=self.config.features  )

       def 	lowerCamelCase__    (						self       :	Any    ,						__snake_case       :	str  ) ->			Optional[Any]:







        '''simple docstring'''

        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}'''  )
        lowerCamelCase       =     dl_manager.download_and_extract(self.config.data_files  )
        if isinstance(__lowerCamelCase    ,						(str, list, tuple)  ):
         lowerCamelCase       =     data_files
         if isinstance(__lowerCamelCase    ,						__lowerCamelCase  ):
          lowerCamelCase       =     [files]
         lowerCamelCase       =     [dl_manager.iter_files(__lowerCamelCase  ) for file in files]
         return [datasets.SplitGenerator(name=datasets.Split.TRAIN    ,						gen_kwargs={'files': files}  )]
        lowerCamelCase       =     []
        for split_name, files in data_files.items():
         if isinstance(__lowerCamelCase    ,						__lowerCamelCase  ):
          lowerCamelCase       =     [files]
         lowerCamelCase       =     [dl_manager.iter_files(__lowerCamelCase  ) for file in files]
         splits.append(datasets.SplitGenerator(name=__lowerCamelCase    ,						gen_kwargs={'files': files}  )  )
        return splits

       def 	lowerCamelCase__    (						self       :	List[Any]    ,						__snake_case       :	pa.Table  ) ->			Dict:







        '''simple docstring'''

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





       def 	lowerCamelCase__    (						self       :	Optional[int]    ,						__snake_case       :	Optional[Any]  ) ->			List[Any]:







        '''simple docstring'''

        lowerCamelCase       =     self.config.features.arrow_schema if self.config.features else None
        # dtype allows reading an int column as str
        lowerCamelCase       =     (
            {
                name: dtype.to_pandas_dtype() if not require_storage_cast(__lowerCamelCase  ) 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(__lowerCamelCase  )  ):
         lowerCamelCase       =     pd.read_csv(__lowerCamelCase    ,						iterator=__lowerCamelCase    ,						dtype=__lowerCamelCase    ,						**self.config.pd_read_csv_kwargs  )
         try:
          for batch_idx, df in enumerate(__lowerCamelCase  ):
           lowerCamelCase       =     pa.Table.from_pandas(__lowerCamelCase  )
           # 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(__lowerCamelCase  )
         except ValueError as e:
          logger.error(F'''Failed to read file \'{file}\' with error {type(__lowerCamelCase  )}: {e}'''  )
          raise







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__A			:					List[Any]						=			{
    'configuration_git': ['GIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GitConfig', 'GitVisionConfig'],
    'processing_git': ['GitProcessor'],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __A			:					int						=			[
        'GIT_PRETRAINED_MODEL_ARCHIVE_LIST',
        'GitForCausalLM',
        'GitModel',
        'GitPreTrainedModel',
        'GitVisionModel',
    ]

if TYPE_CHECKING:
    from .configuration_git import GIT_PRETRAINED_CONFIG_ARCHIVE_MAP, GitConfig, GitVisionConfig
    from .processing_git import GitProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_git import (
            GIT_PRETRAINED_MODEL_ARCHIVE_LIST,
            GitForCausalLM,
            GitModel,
            GitPreTrainedModel,
            GitVisionModel,
        )

else:
    import sys

    __A			:					List[Any]						=			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)