



"""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


A	,	A	,	A		=						False, False, False

@dataclass
class       _a  :
			__magic_name__     					=     None
			__magic_name__     					=     True
			__magic_name__     					=     True
			__magic_name__     					=     None
			# Automatically constructed
			__magic_name__     					=     "dict"
			__magic_name__     					=     pa.struct({"""bytes""": pa.binary(), """path""": pa.string()})
			__magic_name__     					=     field(default="""Audio"""     ,	init=SCREAMING_SNAKE_CASE__     ,	repr=SCREAMING_SNAKE_CASE__)



			def __call__(			self							:				Any		)							->					str:
									return self.pa_type



			def 				__lowercase					(			self							:				List[str]   ,	_lowercase							:				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(_lowercase   ,	_lowercase		):
															return {"bytes": None, "path": value}
									elif isinstance(_lowercase   ,	_lowercase		):
															return {"bytes": value, "path": None}
									elif "array" in value:
															# convert the audio array to wav bytes
															snake_case   :			Optional[Any]						    = BytesIO()
															sf.write(_lowercase   ,	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!)
																											snake_case   :			Any						    = np.frombuffer(value["bytes"]   ,	dtype=np.intaa		).astype(np.floataa		) / 32767
																					else:
																											snake_case   :			Union[str, Any]						    = np.memmap(value["path"]   ,	dtype="h"   ,	mode="r"		).astype(np.floataa		) / 32767

																					snake_case   :			Any						    = BytesIO(bytes()		)
																					sf.write(_lowercase   ,	_lowercase   ,	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 				__lowercase					(			self							:				Tuple   ,	_lowercase							:				dict   ,	_lowercase							:				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."		)

									snake_case    ,			snake_case   :			str						    = (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

									snake_case   :			List[str]						    = xsplitext(_lowercase		)[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:
															snake_case   :			str						    = token_per_repo_id or {}
															snake_case   :			str						    = path.split("::"		)[-1]
															try:
																					snake_case   :			Union[str, Any]						    = string_to_dict(_lowercase   ,	config.HUB_DATASETS_URL		)["repo_id"]
																					snake_case   :			str						    = token_per_repo_id[repo_id]
															except (ValueError, KeyError):
																					snake_case   :			str						    = None

															with xopen(_lowercase   ,	"rb"   ,	use_auth_token=_lowercase		) as f:
																					snake_case    ,			snake_case   :			Optional[int]						    = sf.read(_lowercase		)

									else:
															snake_case    ,			snake_case   :			str						    = sf.read(_lowercase		)

									snake_case   :			List[Any]						    = array.T
									if self.mono:
															snake_case   :			List[str]						    = librosa.to_mono(_lowercase		)
									if self.sampling_rate and self.sampling_rate != sampling_rate:
															snake_case   :			Union[str, Any]						    = librosa.resample(_lowercase   ,	orig_sr=_lowercase   ,	target_sr=self.sampling_rate		)
															snake_case   :			Optional[int]						    = self.sampling_rate

									return {"path": path, "array": array, "sampling_rate": sampling_rate}



			def 				__lowercase					(			self							:				Dict		)							->					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 				__lowercase					(			self							:				List[str]   ,	_lowercase							:				Union[pa.StringArray, pa.StructArray]		)							->					pa.StructArray:
									if pa.types.is_string(storage.type		):
															snake_case   :			Any						    = pa.array([None] * len(_lowercase		)   ,	type=pa.binary()		)
															snake_case   :			List[Any]						    = pa.StructArray.from_arrays([bytes_array, storage]   ,	["bytes", "path"]   ,	mask=storage.is_null()		)
									elif pa.types.is_binary(storage.type		):
															snake_case   :			int						    = pa.array([None] * len(_lowercase		)   ,	type=pa.string()		)
															snake_case   :			Optional[Any]						    = 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"		):
															snake_case   :			Optional[Any]						    = pa.array([Audio().encode_example(_lowercase		) 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:
																					snake_case   :			Dict						    = storage.field("bytes"		)
															else:
																					snake_case   :			str						    = pa.array([None] * len(_lowercase		)   ,	type=pa.binary()		)
															if storage.type.get_field_index("path"		) >= 0:
																					snake_case   :			Tuple						    = storage.field("path"		)
															else:
																					snake_case   :			Optional[Any]						    = pa.array([None] * len(_lowercase		)   ,	type=pa.string()		)
															snake_case   :			Union[str, Any]						    = pa.StructArray.from_arrays([bytes_array, path_array]   ,	["bytes", "path"]   ,	mask=storage.is_null()		)
									return array_cast(_lowercase   ,	self.pa_type		)



			def 				__lowercase					(			self							:				str   ,	_lowercase							:				pa.StructArray		)							->					pa.StructArray:

									@no_op_if_value_is_null
									def path_to_bytes(_lowercase							:				Optional[Any]		):
															with xopen(_lowercase   ,	"rb"		) as f:
																					snake_case   :			Any						    = f.read()
															return bytes_

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








"""simple docstring"""







import math
import sys

def  __SCREAMING_SNAKE_CASE		(			lowerCamelCase_:							int ):
						"""simple docstring"""






						if number != int(lowerCamelCase_ ):
												raise ValueError("the value of input must be a natural number" )
						if number < 0:
												raise ValueError("the value of input must not be a negative number" )
						if number == 0:
												return 1
						snake_case   :			List[str]						    = [-1] * (number + 1)
						snake_case   :			str						    = 0
						for i in range(1     ,		number + 1 ):
												snake_case   :			Tuple						    = sys.maxsize
												snake_case   :			Optional[Any]						    = int(math.sqrt(lowerCamelCase_ ) )
												for j in range(1     ,		root + 1 ):
																		snake_case   :			List[str]						    = 1 + answers[i - (j**2)]
																		snake_case   :			List[str]						    = min(lowerCamelCase_     ,		lowerCamelCase_ )
												snake_case   :			Dict						    = answer
						return answers[number]


if __name__ == "__main__":
			import doctest

			doctest.testmod()



