


"""simple docstring"""





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


snake_case__						:   Union[str, Any]			 = datasets.utils.logging.get_logger(__name__)

snake_case__						:   Optional[int]			 = ['''names''', '''prefix''']
snake_case__						:   Any			 = ['''warn_bad_lines''', '''error_bad_lines''', '''mangle_dupe_cols''']
snake_case__						:   Any			 = ['''encoding_errors''', '''on_bad_lines''']
snake_case__						:   Tuple			 = ['''date_format''']



@dataclass
class 						snake_case_(				datasets.BuilderConfig	):
     __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     =    10_000
     __UpperCamelCase     =    None
     __UpperCamelCase     =    "strict"
     __UpperCamelCase     =    "error"
     __UpperCamelCase     =    None






     def    lowerCamelCase__   (		self     :    Union[str, Any] ):
           if self.delimiter is not None:
                 lowerCAmelCase    :		Dict				=      self.delimiter
           if self.column_names is not None:
                 lowerCAmelCase    :		Dict				=      self.column_names






     @property
     def    lowerCamelCase__   (		self     :    Any ):
           lowerCAmelCase    :		Any				=      {
               '''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()    , UpperCamelCase_ ):
                       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	):
     __UpperCamelCase     =    CsvConfig






     def    lowerCamelCase__   (		self     :    List[str] ):
           return datasets.DatasetInfo(features=self.config.features )






     def    lowerCamelCase__   (		self     :    Union[str, Any]    , UpperCamelCase_     :    List[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}''' )
           lowerCAmelCase    :		Union[str, Any]				=      dl_manager.download_and_extract(self.config.data_files )
           if isinstance(UpperCamelCase_    , (str, list, tuple) ):
                 lowerCAmelCase    :		Dict				=      data_files
                 if isinstance(UpperCamelCase_    , UpperCamelCase_ ):
                       lowerCAmelCase    :		Tuple				=      [files]
                 lowerCAmelCase    :		List[Any]				=      [dl_manager.iter_files(UpperCamelCase_ ) for file in files]
                 return [datasets.SplitGenerator(name=datasets.Split.TRAIN    , gen_kwargs={'''files''': files} )]
           lowerCAmelCase    :		Tuple				=      []
           for split_name, files in data_files.items():
                 if isinstance(UpperCamelCase_    , UpperCamelCase_ ):
                       lowerCAmelCase    :		Optional[int]				=      [files]
                 lowerCAmelCase    :		Dict				=      [dl_manager.iter_files(UpperCamelCase_ ) for file in files]
                 splits.append(datasets.SplitGenerator(name=UpperCamelCase_    , gen_kwargs={'''files''': files} ) )
           return splits






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






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






"""simple docstring"""





import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
 from .tokenization_fnet import FNetTokenizer
else:
 snake_case__						:   str			 = None

snake_case__						:   Optional[Any]			 = logging.get_logger(__name__)
snake_case__						:   Optional[int]			 = {'''vocab_file''': '''spiece.model''', '''tokenizer_file''': '''tokenizer.json'''}

snake_case__						:   Dict			 = {
    '''vocab_file''': {
        '''google/fnet-base''': '''https://huggingface.co/google/fnet-base/resolve/main/spiece.model''',
        '''google/fnet-large''': '''https://huggingface.co/google/fnet-large/resolve/main/spiece.model''',
    },
    '''tokenizer_file''': {
        '''google/fnet-base''': '''https://huggingface.co/google/fnet-base/resolve/main/tokenizer.json''',
        '''google/fnet-large''': '''https://huggingface.co/google/fnet-large/resolve/main/tokenizer.json''',
    },
}

snake_case__						:   Any			 = {
    '''google/fnet-base''': 512,
    '''google/fnet-large''': 512,
}

snake_case__						:   Dict			 = '''▁'''



class 						snake_case_(				a__	):
     __UpperCamelCase     =    VOCAB_FILES_NAMES
     __UpperCamelCase     =    PRETRAINED_VOCAB_FILES_MAP
     __UpperCamelCase     =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     __UpperCamelCase     =    ['''input_ids''', '''token_type_ids''']
     __UpperCamelCase     =    FNetTokenizer






     def __init__(		self     :    Union[str, Any]    , UpperCamelCase_     :    Union[str, Any]=None    , UpperCamelCase_     :    Union[str, Any]=None    , UpperCamelCase_     :    Any=False    , UpperCamelCase_     :    Any=True    , UpperCamelCase_     :    Dict=True    , UpperCamelCase_     :    Tuple="<unk>"    , UpperCamelCase_     :    List[str]="[SEP]"    , UpperCamelCase_     :    List[Any]="<pad>"    , UpperCamelCase_     :    Union[str, Any]="[CLS]"    , UpperCamelCase_     :    int="[MASK]"    , **UpperCamelCase_     :    Optional[Any]    , ):
           # Mask token behave like a normal word, i.e. include the space before it and
           # is included in the raw text, there should be a match in a non-normalized sentence.
           lowerCAmelCase    :		int				=      (
               AddedToken(UpperCamelCase_    , lstrip=UpperCamelCase_    , rstrip=UpperCamelCase_    , normalized=UpperCamelCase_ )
               if isinstance(UpperCamelCase_    , UpperCamelCase_ )
               else mask_token
           )

           super().__init__(
               UpperCamelCase_    , tokenizer_file=UpperCamelCase_    , do_lower_case=UpperCamelCase_    , remove_space=UpperCamelCase_    , keep_accents=UpperCamelCase_    , unk_token=UpperCamelCase_    , sep_token=UpperCamelCase_    , pad_token=UpperCamelCase_    , cls_token=UpperCamelCase_    , mask_token=UpperCamelCase_    , **UpperCamelCase_    , )

           lowerCAmelCase    :		Optional[int]				=      do_lower_case
           lowerCAmelCase    :		str				=      remove_space
           lowerCAmelCase    :		Any				=      keep_accents
           lowerCAmelCase    :		int				=      vocab_file
           lowerCAmelCase    :		List[str]				=      False if not self.vocab_file else True






     def    lowerCamelCase__   (		self     :    List[Any]    , UpperCamelCase_     :    List[int]    , UpperCamelCase_     :    Optional[List[int]] = None ):
           lowerCAmelCase    :		Optional[int]				=      [self.sep_token_id]
           lowerCAmelCase    :		Optional[Any]				=      [self.cls_token_id]
           if token_ids_a is None:
                 return cls + token_ids_a + sep
           return cls + token_ids_a + sep + token_ids_a + sep






     def    lowerCamelCase__   (		self     :    List[str]    , UpperCamelCase_     :    List[int]    , UpperCamelCase_     :    Optional[List[int]] = None ):
           lowerCAmelCase    :		List[str]				=      [self.sep_token_id]
           lowerCAmelCase    :		Optional[Any]				=      [self.cls_token_id]

           if token_ids_a is None:
                 return len(cls + token_ids_a + sep ) * [0]
           return len(cls + token_ids_a + sep ) * [0] + len(token_ids_a + sep ) * [1]






     def    lowerCamelCase__   (		self     :    List[Any]    , UpperCamelCase_     :    str    , UpperCamelCase_     :    Optional[str] = None ):
           if not os.path.isdir(UpperCamelCase_ ):
                 logger.error(F'''Vocabulary path ({save_directory}) should be a directory''' )
                 return
           lowerCAmelCase    :		str				=      os.path.join(
               UpperCamelCase_    , (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file'''] )

           if os.path.abspath(self.vocab_file ) != os.path.abspath(UpperCamelCase_ ):
                 copyfile(self.vocab_file    , UpperCamelCase_ )

           return (out_vocab_file,)


