





"""simple docstring"""

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__  							=False, False, False





@dataclass
class    lowerCamelCase__						:
      a :     Optional[int]											=		None
      a :     bool											=		True
      a :     bool											=		True
      a :     Optional[str]											=		None
      # Automatically constructed
      a :     ClassVar[str]											=		"dict"
      a :     ClassVar[Any]											=		pa.struct({"""bytes""": pa.binary(), """path""": pa.string()}    )
      a :     str											=		field(default="""Audio"""			,   init=a__			,   repr=a__    )
      def __call__(		self	:	Any							):






       '''simple docstring'''


       return self.pa_type
      def SCREAMING_SNAKE_CASE_	(		self	:	Optional[Any]      ,       A_	:	int							):






       '''simple docstring'''


       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(lowerCamelCase_      ,       lowerCamelCase_							):
        return {"bytes": None, "path": value}
       elif isinstance(lowerCamelCase_      ,       lowerCamelCase_							):
        return {"bytes": value, "path": None}
       elif "array" in value:
        # convert the audio array to wav bytes
        __lowercase									=	BytesIO()
        sf.write(lowerCamelCase_      ,       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!)
          __lowercase									=	np.frombuffer(value["""bytes"""]      ,       dtype=np.intaa							).astype(np.floataa							) / 3_2_7_6_7
         else:
          __lowercase									=	np.memmap(value["""path"""]      ,       dtype="""h"""      ,       mode="""r"""							).astype(np.floataa							) / 3_2_7_6_7

         __lowercase									=	BytesIO(bytes()							)
         sf.write(lowerCamelCase_      ,       lowerCamelCase_      ,       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 SCREAMING_SNAKE_CASE_	(		self	:	int      ,       A_	:	Optional[int]      ,       A_	:	Union[str, Any] = None							):






       '''simple docstring'''


       if not self.decode:
        raise RuntimeError("""Decoding is disabled for this feature. Please use Audio(decode=True) instead."""							)

       __lowercase							,		__lowercase									=	(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

       __lowercase									=	xsplitext(lowerCamelCase_							)[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:
        __lowercase									=	token_per_repo_id or {}
        __lowercase									=	path.split("""::"""							)[-1]
        try:
         __lowercase									=	string_to_dict(lowerCamelCase_      ,       config.HUB_DATASETS_URL							)["""repo_id"""]
         __lowercase									=	token_per_repo_id[repo_id]
        except (ValueError, KeyError):
         __lowercase									=	None

        with xopen(lowerCamelCase_      ,       """rb"""      ,       use_auth_token=lowerCamelCase_							) as f:
         __lowercase							,		__lowercase									=	sf.read(lowerCamelCase_							)

       else:
        __lowercase							,		__lowercase									=	sf.read(lowerCamelCase_							)

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

       return {"path": path, "array": array, "sampling_rate": sampling_rate}
      def SCREAMING_SNAKE_CASE_	(		self	:	Dict							):






       '''simple docstring'''


       from .features import Value

       if self.decode:
        raise ValueError("""Cannot flatten a decoded Audio feature."""							)
       return {
           "bytes": Value("""binary"""							),
           "path": Value("""string"""							),
       }
      def SCREAMING_SNAKE_CASE_	(		self	:	int      ,       A_	:	str							):






       '''simple docstring'''


       if pa.types.is_string(storage.type							):
        __lowercase									=	pa.array([None] * len(lowerCamelCase_							)      ,       type=pa.binary()							)
        __lowercase									=	pa.StructArray.from_arrays([bytes_array, storage]      ,       ["""bytes""", """path"""]      ,       mask=storage.is_null()							)
       elif pa.types.is_binary(storage.type							):
        __lowercase									=	pa.array([None] * len(lowerCamelCase_							)      ,       type=pa.string()							)
        __lowercase									=	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"""							):
        __lowercase									=	pa.array([Audio().encode_example(lowerCamelCase_							) 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:
         __lowercase									=	storage.field("""bytes"""							)
        else:
         __lowercase									=	pa.array([None] * len(lowerCamelCase_							)      ,       type=pa.binary()							)
        if storage.type.get_field_index("""path"""							) >= 0:
         __lowercase									=	storage.field("""path"""							)
        else:
         __lowercase									=	pa.array([None] * len(lowerCamelCase_							)      ,       type=pa.string()							)
        __lowercase									=	pa.StructArray.from_arrays([bytes_array, path_array]      ,       ["""bytes""", """path"""]      ,       mask=storage.is_null()							)
       return array_cast(lowerCamelCase_      ,       self.pa_type							)






      def SCREAMING_SNAKE_CASE_	(		self	:	List[str]      ,       A_	:	List[Any]							):






       '''simple docstring'''


       @no_op_if_value_is_null
       def path_to_bytes(A_	:	Any							):
        with xopen(lowerCamelCase_      ,       """rb"""							) as f:
         __lowercase									=	f.read()
        return bytes_

       __lowercase									=	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()      ,       )
       __lowercase									=	pa.array(
           [os.path.basename(lowerCamelCase_							) if path is not None else None for path in storage.field("""path"""							).to_pylist()]      ,       type=pa.string()      ,       )
       __lowercase									=	pa.StructArray.from_arrays([bytes_array, path_array]      ,       ["""bytes""", """path"""]      ,       mask=bytes_array.is_null()							)
       return array_cast(lowerCamelCase_      ,       self.pa_type							)




"""simple docstring"""

import random


def lowerCAmelCase_      (				UpperCamelCase__	: int				,   UpperCamelCase__	: float				,   UpperCamelCase__	: bool = False ):






 """simple docstring"""







 __lowercase									=	{i: [] for i in range(UpperCamelCase__ )}

 # if probability is greater or equal than 1, then generate a complete graph
 if probability >= 1:
  return complete_graph(UpperCamelCase__ )
 # if probability is lower or equal than 0, then return a graph without edges
 if probability <= 0:
  return graph

 # for each couple of nodes, add an edge from u to v
 # if the number randomly generated is greater than probability probability
 for i in range(UpperCamelCase__ ):
  for j in range(i + 1				,   UpperCamelCase__ ):
   if random.random() < probability:
    graph[i].append(UpperCamelCase__ )
    if not directed:
     # if the graph is undirected, add an edge in from j to i, either
     graph[j].append(UpperCamelCase__ )
 return graph


def lowerCAmelCase_      (				UpperCamelCase__	: int ):






 """simple docstring"""







 return {
     i: [j for j in range(UpperCamelCase__ ) if i != j] for i in range(UpperCamelCase__ )
 }


if __name__ == "__main__":
       import doctest

       doctest.testmod()
