





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


_UpperCAmelCase     ,_UpperCAmelCase     ,_UpperCAmelCase       : int			     =       False, False, False

@dataclass
class      lowerCAmelCase							:
 UpperCAmelCase__									=	None
 UpperCAmelCase__									=	True
 UpperCAmelCase__									=	True
 UpperCAmelCase__									=	None
 # Automatically constructed
 UpperCAmelCase__									=	"dict"
 UpperCAmelCase__									=	pa.struct({"""bytes""": pa.binary(), """path""": pa.string()}    )
 UpperCAmelCase__									=	field(default="""Audio""",						init=__UpperCamelCase,						repr=__UpperCamelCase    )
 def __call__(   self						:   Optional[Any]			)    ->			Dict:
     return self.pa_type
 def   A_			(   self						:   List[str]    ,  UpperCAmelCase						:   Union[str, bytes, dict]			)    ->			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(UpperCAmelCase    ,  UpperCAmelCase			):
         return {"bytes": None, "path": value}
     elif isinstance(UpperCAmelCase    ,  UpperCAmelCase			):
         return {"bytes": value, "path": None}
     elif "array" in value:
         # convert the audio array to wav bytes
         lowerCamelCase__					:   List[str]      				=	BytesIO()
         sf.write(UpperCAmelCase    ,  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!)
                 lowerCamelCase__					:   Optional[int]      				=	np.frombuffer(value['bytes']    ,  dtype=np.intaa			).astype(np.floataa			) / 32767
             else:
                 lowerCamelCase__					:   Union[str, Any]      				=	np.memmap(value['path']    ,  dtype='h'    ,  mode='r'			).astype(np.floataa			) / 32767

             lowerCamelCase__					:   str      				=	BytesIO(bytes()			)
             sf.write(UpperCAmelCase    ,  UpperCAmelCase    ,  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   A_			(   self						:   int    ,  UpperCAmelCase						:   dict    ,  UpperCAmelCase						:   Optional[Dict[str, Union[str, bool, None]]] = None			)    ->			dict:
     if not self.decode:
         raise RuntimeError('Decoding is disabled for this feature. Please use Audio(decode=True) instead.'			)

     lowerCamelCase__				,							lowerCamelCase__					:   Any      				=	(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

     lowerCamelCase__					:   Tuple      				=	xsplitext(UpperCAmelCase			)[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:
         lowerCamelCase__					:   Optional[Any]      				=	token_per_repo_id or {}
         lowerCamelCase__					:   Dict      				=	path.split('::'			)[-1]
         try:
             lowerCamelCase__					:   int      				=	string_to_dict(UpperCAmelCase    ,  config.HUB_DATASETS_URL			)['repo_id']
             lowerCamelCase__					:   Dict      				=	token_per_repo_id[repo_id]
         except (ValueError, KeyError):
             lowerCamelCase__					:   Tuple      				=	None

         with xopen(UpperCAmelCase    ,  'rb'    ,  use_auth_token=UpperCAmelCase			) as f:
             lowerCamelCase__				,							lowerCamelCase__					:   Optional[Any]      				=	sf.read(UpperCAmelCase			)

     else:
         lowerCamelCase__				,							lowerCamelCase__					:   List[str]      				=	sf.read(UpperCAmelCase			)

     lowerCamelCase__					:   Any      				=	array.T
     if self.mono:
         lowerCamelCase__					:   Tuple      				=	librosa.to_mono(UpperCAmelCase			)
     if self.sampling_rate and self.sampling_rate != sampling_rate:
         lowerCamelCase__					:   int      				=	librosa.resample(UpperCAmelCase    ,  orig_sr=UpperCAmelCase    ,  target_sr=self.sampling_rate			)
         lowerCamelCase__					:   List[Any]      				=	self.sampling_rate

     return {"path": path, "array": array, "sampling_rate": sampling_rate}
 def   A_			(   self						:   Any			)    ->			Union["FeatureType", Dict[str, "FeatureType"]]:
     from .features import Value

     if self.decode:
         raise ValueError('Cannot flatten a decoded Audio feature.'			)
     return {
         "bytes": Value('binary'			),
         "path": Value('string'			),
     }
 def   A_			(   self						:   Union[str, Any]    ,  UpperCAmelCase						:   Union[pa.StringArray, pa.StructArray]			)    ->			pa.StructArray:
     if pa.types.is_string(storage.type			):
         lowerCamelCase__					:   Tuple      				=	pa.array([None] * len(UpperCAmelCase			)    ,  type=pa.binary()			)
         lowerCamelCase__					:   Any      				=	pa.StructArray.from_arrays([bytes_array, storage]    ,  ['bytes', 'path']    ,  mask=storage.is_null()			)
     elif pa.types.is_binary(storage.type			):
         lowerCamelCase__					:   Union[str, Any]      				=	pa.array([None] * len(UpperCAmelCase			)    ,  type=pa.string()			)
         lowerCamelCase__					:   Tuple      				=	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'			):
         lowerCamelCase__					:   Any      				=	pa.array([Audio().encode_example(UpperCAmelCase			) 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:
             lowerCamelCase__					:   int      				=	storage.field('bytes'			)
         else:
             lowerCamelCase__					:   Dict      				=	pa.array([None] * len(UpperCAmelCase			)    ,  type=pa.binary()			)
         if storage.type.get_field_index('path'			) >= 0:
             lowerCamelCase__					:   Union[str, Any]      				=	storage.field('path'			)
         else:
             lowerCamelCase__					:   Optional[int]      				=	pa.array([None] * len(UpperCAmelCase			)    ,  type=pa.string()			)
         lowerCamelCase__					:   Tuple      				=	pa.StructArray.from_arrays([bytes_array, path_array]    ,  ['bytes', 'path']    ,  mask=storage.is_null()			)
     return array_cast(UpperCAmelCase    ,  self.pa_type			)







 def   A_			(   self						:   Dict    ,  UpperCAmelCase						:   pa.StructArray			)    ->			pa.StructArray:

     @no_op_if_value_is_null
     def path_to_bytes(UpperCAmelCase						:   int			):
         with xopen(UpperCAmelCase    ,  'rb'			) as f:
             lowerCamelCase__					:   Any      				=	f.read()
         return bytes_

     lowerCamelCase__					:   Any      				=	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()    ,  )
     lowerCamelCase__					:   List[str]      				=	pa.array(
         [os.path.basename(UpperCAmelCase			) if path is not None else None for path in storage.field('path'			).to_pylist()]    ,  type=pa.string()    ,  )
     lowerCamelCase__					:   List[str]      				=	pa.StructArray.from_arrays([bytes_array, path_array]    ,  ['bytes', 'path']    ,  mask=bytes_array.is_null()			)
     return array_cast(UpperCAmelCase    ,  self.pa_type			)












_UpperCAmelCase       : str			     =       """Tobias Carryer"""

from time import time

class      lowerCAmelCase							:
 def __init__(   self						:   Optional[Any]    ,  UpperCAmelCase						:   int    ,  UpperCAmelCase						:   Dict    ,  UpperCAmelCase						:   Any    ,  UpperCAmelCase						:   str=int(time()			)			)    ->			Optional[int]:  # noqa: B008
     lowerCamelCase__					:   List[Any]      				=	multiplier
     lowerCamelCase__					:   Tuple      				=	increment
     lowerCamelCase__					:   int      				=	modulo
     lowerCamelCase__					:   Any      				=	seed







 def   A_			(   self						:   Optional[int]			)    ->			List[Any]:
     lowerCamelCase__					:   List[str]      				=	(self.multiplier * self.seed + self.increment) % self.modulo
     return self.seed


if __name__ == "__main__":
    # Show the LCG in action.
    _UpperCAmelCase       : List[Any]			     =       LinearCongruentialGenerator(1_66_45_25, 10_13_90_42_23, 2 << 31)
    while True:
        print(lcg.next_number())





