




import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union

import numpy as np
import pyarrow as pa

from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..table import array_cast
from ..utils.py_utils import no_op_if_value_is_null, string_to_dict


if TYPE_CHECKING:
 from .features import FeatureType


_lowerCamelCase			,					_lowerCamelCase			,					_lowerCamelCase      			=						False, False, False



@dataclass
class       a					:

     '''simple docstring'''





     lowerCAmelCase    :	Optional[int]       		=  None
     lowerCAmelCase    :	bool       		=  True
     lowerCAmelCase    :	bool       		=  True
     lowerCAmelCase    :	Optional[str]       		=  None
     # Automatically constructed
     lowerCAmelCase    :	ClassVar[str]       		=  "dict"
     lowerCAmelCase    :	ClassVar[Any]       		=  pa.struct({'bytes': pa.binary(), 'path': pa.string()}      )
     lowerCAmelCase    :	str       		=  field(default='Audio'     ,       init=_A     ,       repr=_A      )
     def __call__(     self       :      Any    ):
         return self.pa_type
     def   lowerCamelCase_       (     self       :      Tuple ,   __snake_case       :      Union[str, bytes, dict]    ):
         try:
             import soundfile as sf  # soundfile is a dependency of librosa, needed to decode audio files.
         except ImportError as err:
             raise ImportError('''To support encoding audio data, please install \'soundfile\'.'''    ) from err
         if isinstance(__snake_case ,   __snake_case    ):
             return {"bytes": None, "path": value}
         elif isinstance(__snake_case ,   __snake_case    ):
             return {"bytes": value, "path": None}
         elif "array" in value:
             # convert the audio array to wav bytes
             UpperCAmelCase_										=					BytesIO()
             sf.write(__snake_case ,   value['''array'''] ,   value['''sampling_rate'''] ,   format='''wav'''    )
             return {"bytes": buffer.getvalue(), "path": None}
         elif value.get('''path'''    ) is not None and os.path.isfile(value['''path''']    ):
             # we set "bytes": None to not duplicate the data if they're already available locally
             if value["path"].endswith('''pcm'''    ):
                 # "PCM" only has raw audio bytes
                 if value.get('''sampling_rate'''    ) is None:
                     # At least, If you want to convert "PCM-byte" to "WAV-byte", you have to know sampling rate
                     raise KeyError('''To use PCM files, please specify a \'sampling_rate\' in Audio object'''    )
                 if value.get('''bytes'''    ):
                     # If we already had PCM-byte, we don`t have to make "read file, make bytes" (just use it!)
                     UpperCAmelCase_										=					np.frombuffer(value['''bytes'''] ,   dtype=np.intaa    ).astype(np.floataa    ) / 3_27_67
                 else:
                     UpperCAmelCase_										=					np.memmap(value['''path'''] ,   dtype='''h''' ,   mode='''r'''    ).astype(np.floataa    ) / 3_27_67

                 UpperCAmelCase_										=					BytesIO(bytes()    )
                 sf.write(__snake_case ,   __snake_case ,   value['''sampling_rate'''] ,   format='''wav'''    )
                 return {"bytes": buffer.getvalue(), "path": None}
             else:
                 return {"bytes": None, "path": value.get('''path'''    )}
         elif value.get('''bytes'''    ) is not None or value.get('''path'''    ) is not None:
             # store the audio bytes, and path is used to infer the audio format using the file extension
             return {"bytes": value.get('''bytes'''    ), "path": value.get('''path'''    )}
         else:
             raise ValueError(
                 F'An audio sample should have one of \'path\' or \'bytes\' but they are missing or None in {value}.'    )
     def   lowerCamelCase_       (     self       :      List[Any] ,   __snake_case       :      dict ,   __snake_case       :      Optional[Dict[str, Union[str, bool, None]]] = None    ):
         if not self.decode:
             raise RuntimeError('''Decoding is disabled for this feature. Please use Audio(decode=True) instead.'''    )

         UpperCAmelCase_			,							UpperCAmelCase_										=					(value['''path'''], BytesIO(value['''bytes''']    )) if value['''bytes'''] is not None else (value['''path'''], None)
         if path is None and file is None:
             raise ValueError(F'An audio sample should have one of \'path\' or \'bytes\' but both are None in {value}.'    )

         try:
             import librosa
             import soundfile as sf
         except ImportError as err:
             raise ImportError('''To support decoding audio files, please install \'librosa\' and \'soundfile\'.'''    ) from err

         UpperCAmelCase_										=					xsplitext(__snake_case    )[1][1:].lower() if path is not None else None
         if not config.IS_OPUS_SUPPORTED and audio_format == "opus":
             raise RuntimeError(
                 '''Decoding \'opus\' files requires system library \'libsndfile\'>=1.0.31, '''
                 '''You can try to update `soundfile` python library: `pip install "soundfile>=0.12.1"`. '''    )
         elif not config.IS_MP3_SUPPORTED and audio_format == "mp3":
             raise RuntimeError(
                 '''Decoding \'mp3\' files requires system library \'libsndfile\'>=1.1.0, '''
                 '''You can try to update `soundfile` python library: `pip install "soundfile>=0.12.1"`. '''    )

         if file is None:
             UpperCAmelCase_										=					token_per_repo_id or {}
             UpperCAmelCase_										=					path.split('''::'''    )[-1]
             try:
                 UpperCAmelCase_										=					string_to_dict(__snake_case ,   config.HUB_DATASETS_URL    )['''repo_id''']
                 UpperCAmelCase_										=					token_per_repo_id[repo_id]
             except (ValueError, KeyError):
                 UpperCAmelCase_										=					None

             with xopen(__snake_case ,   '''rb''' ,   use_auth_token=__snake_case    ) as f:
                 UpperCAmelCase_			,							UpperCAmelCase_										=					sf.read(__snake_case    )

         else:
             UpperCAmelCase_			,							UpperCAmelCase_										=					sf.read(__snake_case    )

         UpperCAmelCase_										=					array.T
         if self.mono:
             UpperCAmelCase_										=					librosa.to_mono(__snake_case    )
         if self.sampling_rate and self.sampling_rate != sampling_rate:
             UpperCAmelCase_										=					librosa.resample(__snake_case ,   orig_sr=__snake_case ,   target_sr=self.sampling_rate    )
             UpperCAmelCase_										=					self.sampling_rate

         return {"path": path, "array": array, "sampling_rate": sampling_rate}
     def   lowerCamelCase_       (     self       :      Union[str, Any]    ):
         from .features import Value

         if self.decode:
             raise ValueError('''Cannot flatten a decoded Audio feature.'''    )
         return {
             "bytes": Value('''binary'''    ),
             "path": Value('''string'''    ),
         }
     def   lowerCamelCase_       (     self       :      Optional[int] ,   __snake_case       :      Union[pa.StringArray, pa.StructArray]    ):
         if pa.types.is_string(storage.type    ):
             UpperCAmelCase_										=					pa.array([None] * len(__snake_case    ) ,   type=pa.binary()    )
             UpperCAmelCase_										=					pa.StructArray.from_arrays([bytes_array, storage] ,   ['''bytes''', '''path'''] ,   mask=storage.is_null()    )
         elif pa.types.is_binary(storage.type    ):
             UpperCAmelCase_										=					pa.array([None] * len(__snake_case    ) ,   type=pa.string()    )
             UpperCAmelCase_										=					pa.StructArray.from_arrays([storage, path_array] ,   ['''bytes''', '''path'''] ,   mask=storage.is_null()    )
         elif pa.types.is_struct(storage.type    ) and storage.type.get_all_field_indices('''array'''    ):
             UpperCAmelCase_										=					pa.array([Audio().encode_example(__snake_case    ) if x is not None else None for x in storage.to_pylist()]    )
         elif pa.types.is_struct(storage.type    ):
             if storage.type.get_field_index('''bytes'''    ) >= 0:
                 UpperCAmelCase_										=					storage.field('''bytes'''    )
             else:
                 UpperCAmelCase_										=					pa.array([None] * len(__snake_case    ) ,   type=pa.binary()    )
             if storage.type.get_field_index('''path'''    ) >= 0:
                 UpperCAmelCase_										=					storage.field('''path'''    )
             else:
                 UpperCAmelCase_										=					pa.array([None] * len(__snake_case    ) ,   type=pa.string()    )
             UpperCAmelCase_										=					pa.StructArray.from_arrays([bytes_array, path_array] ,   ['''bytes''', '''path'''] ,   mask=storage.is_null()    )
         return array_cast(__snake_case ,   self.pa_type    )




     def   lowerCamelCase_       (     self       :      str ,   __snake_case       :      pa.StructArray    ):

         @no_op_if_value_is_null
         def path_to_bytes(__snake_case       :      Optional[int]    ):
             with xopen(__snake_case ,   '''rb'''    ) as f:
                 UpperCAmelCase_										=					f.read()
             return bytes_

         UpperCAmelCase_										=					pa.array(
             [
                 (path_to_bytes(x['''path''']    ) if x['''bytes'''] is None else x['''bytes''']) if x is not None else None
                 for x in storage.to_pylist()
             ] ,   type=pa.binary() ,   )
         UpperCAmelCase_										=					pa.array(
             [os.path.basename(__snake_case    ) if path is not None else None for path in storage.field('''path'''    ).to_pylist()] ,   type=pa.string() ,   )
         UpperCAmelCase_										=					pa.StructArray.from_arrays([bytes_array, path_array] ,   ['''bytes''', '''path'''] ,   mask=bytes_array.is_null()    )
         return array_cast(__snake_case ,   self.pa_type    )











import argparse
import logging
import pickle
from collections import Counter


logging.basicConfig(
    format='%(asctime)s - %(levelname)s - %(name)s - %(message)s', datefmt='%m/%d/%Y %H:%M:%S', level=logging.INFO
)
_lowerCamelCase      			=						logging.getLogger(__name__)

if __name__ == "__main__":
 _lowerCamelCase      			=						argparse.ArgumentParser(
     description='Token Counts for smoothing the masking probabilities in MLM (cf XLM/word2vec)'
 )
 parser.add_argument(
     '--data_file', type=str, default='data/dump.bert-base-uncased.pickle', help='The binarized dataset.'
 )
 parser.add_argument(
     '--token_counts_dump', type=str, default='data/token_counts.bert-base-uncased.pickle', help='The dump file.'
 )
 parser.add_argument('--vocab_size', default=3_05_22, type=int)
 _lowerCamelCase      			=						parser.parse_args()

 logger.info(F"Loading data from {args.data_file}")
 with open(args.data_file, 'rb') as fp:
  _lowerCamelCase      			=						pickle.load(fp)

 logger.info('Counting occurrences for MLM.')
 _lowerCamelCase      			=						Counter()
 for tk_ids in data:
  counter.update(tk_ids)
 _lowerCamelCase      			=						[0] * args.vocab_size
 for k, v in counter.items():
  _lowerCamelCase      			=						v

 logger.info(F"Dump to {args.token_counts_dump}")
 with open(args.token_counts_dump, 'wb') as handle:
  pickle.dump(counts, handle, protocol=pickle.HIGHEST_PROTOCOL)





