




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

lowerCamelCase       :	List[str]									=     ["names", "prefix"]
lowerCamelCase       :	Optional[int]									=     ["warn_bad_lines", "error_bad_lines", "mangle_dupe_cols"]
lowerCamelCase       :	int									=     ["encoding_errors", "on_bad_lines"]
lowerCamelCase       :	Union[str, Any]									=     ["date_format"]







@dataclass
class 						A(		datasets.BuilderConfig     ):



 '''simple docstring'''


 UpperCamelCase		     =		''','''
 UpperCamelCase		     =		None
 UpperCamelCase		     =		'''infer'''
 UpperCamelCase		     =		None
 UpperCamelCase		     =		None
 UpperCamelCase		     =		None
 UpperCamelCase		     =		None
 UpperCamelCase		     =		None
 UpperCamelCase		     =		True
 UpperCamelCase		     =		None
 UpperCamelCase		     =		None
 UpperCamelCase		     =		None
 UpperCamelCase		     =		None
 UpperCamelCase		     =		False
 UpperCamelCase		     =		None
 UpperCamelCase		     =		None
 UpperCamelCase		     =		None
 UpperCamelCase		     =		True
 UpperCamelCase		     =		True
 UpperCamelCase		     =		False
 UpperCamelCase		     =		True
 UpperCamelCase		     =		None
 UpperCamelCase		     =		'''.'''
 UpperCamelCase		     =		None
 UpperCamelCase		     =		'''"'''
 UpperCamelCase		     =		0
 UpperCamelCase		     =		None
 UpperCamelCase		     =		None
 UpperCamelCase		     =		None
 UpperCamelCase		     =		None
 UpperCamelCase		     =		True
 UpperCamelCase		     =		True
 UpperCamelCase		     =		0
 UpperCamelCase		     =		True
 UpperCamelCase		     =		False
 UpperCamelCase		     =		None
 UpperCamelCase		     =		1_0000
 UpperCamelCase		     =		None
 UpperCamelCase		     =		'''strict'''
 UpperCamelCase		     =		'''error'''
 UpperCamelCase		     =		None

 def        a__				(       self      :						Union[str, Any]						)     ->			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        a__				(       self      :						List[str]						)     ->			List[Any]:

       """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()		,							_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 						A(		datasets.ArrowBasedBuilder     ):



 '''simple docstring'''


 UpperCamelCase		     =		CsvConfig

 def        a__				(       self      :						Any						)     ->			Dict:

       """simple docstring"""






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

 def        a__				(       self      :						Dict		,							A_      :						Union[str, Any]						)     ->			Dict:

       """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(_A		,							(str, list, tuple)						):
             lowerCamelCase_	  =					data_files
             if isinstance(_A		,							_A						):
                   lowerCamelCase_	  =					[files]
             lowerCamelCase_	  =					[dl_manager.iter_files(_A						) 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(_A		,							_A						):
                   lowerCamelCase_	  =					[files]
             lowerCamelCase_	  =					[dl_manager.iter_files(_A						) for file in files]
             splits.append(datasets.SplitGenerator(name=_A		,							gen_kwargs={'files': files}						)						)
       return splits

 def        a__				(       self      :						Any		,							A_      :						Optional[int]						)     ->			Union[str, Any]:

       """simple docstring"""






       if self.config.features is not None:
             lowerCamelCase_	  =					self.config.features.arrow_schema
             if all(not require_storage_cast(_A						) for feature in self.config.features.values()						):
                   # cheaper cast
                   lowerCamelCase_	  =					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
                   lowerCamelCase_	  =					table_cast(_A		,							_A						)
       return pa_table





 def        a__				(       self      :						str		,							A_      :						str						)     ->			Tuple:

       """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(_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						)						):
             lowerCamelCase_	  =					pd.read_csv(_A		,							iterator=_A		,							dtype=_A		,							**self.config.pd_read_csv_kwargs						)
             try:
                   for batch_idx, df in enumerate(_A						):
                         lowerCamelCase_	  =					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









from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase       :	str									=     logging.get_logger(__name__)

lowerCamelCase       :	List[str]									=     {
    "abeja/gpt-neox-japanese-2.7b": "https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/config.json",
}







class 						A(		UpperCamelCase     ):



 '''simple docstring'''


 UpperCamelCase		     =		'''gpt_neox_japanese'''

 def __init__(       self      :						int		,							A_      :						Dict=32000		,							A_      :						List[Any]=2560		,							A_      :						Dict=32		,							A_      :						Union[str, Any]=32		,							A_      :						List[Any]=4		,							A_      :						List[str]="gelu"		,							A_      :						Dict=1.00		,							A_      :						int=10000		,							A_      :						Dict=2048		,							A_      :						Dict=0.02		,							A_      :						Any=1E-5		,							A_      :						Union[str, Any]=True		,							A_      :						int=31996		,							A_      :						List[str]=31999		,							A_      :						List[Any]=0.1		,							A_      :						List[Any]=0.0		,							**A_      :						Tuple		,							)     ->			Dict:

       """simple docstring"""






       super().__init__(bos_token_id=A_		,							eos_token_id=A_		,							**A_						)
       lowerCamelCase_	  =					vocab_size
       lowerCamelCase_	  =					max_position_embeddings
       lowerCamelCase_	  =					hidden_size
       lowerCamelCase_	  =					num_hidden_layers
       lowerCamelCase_	  =					num_attention_heads
       lowerCamelCase_	  =					intermediate_multiple_size
       lowerCamelCase_	  =					hidden_act
       lowerCamelCase_	  =					rotary_pct
       lowerCamelCase_	  =					rotary_emb_base
       lowerCamelCase_	  =					initializer_range
       lowerCamelCase_	  =					layer_norm_eps
       lowerCamelCase_	  =					use_cache
       lowerCamelCase_	  =					attention_dropout
       lowerCamelCase_	  =					hidden_dropout



