

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


lowercase   ,       lowercase   ,       lowercase  :							int	   =							False, False, False
@dataclass
class 		SCREAMING_SNAKE_CASE__       :







						"""simple docstring"""




						lowercase	:					Optional[int]           =				None
						lowercase	:					Any           =				True
						lowercase	:					Dict           =				True
						lowercase	:					Tuple           =				None
						# Automatically constructed
						lowercase	:					List[str]           =				'dict'
						lowercase	:					List[str]           =				pa.struct({'bytes': pa.binary(), 'path': pa.string()} )
						lowercase	:					Optional[Any]           =				field(default='Audio'    ,						init=SCREAMING_SNAKE_CASE__    ,						repr=SCREAMING_SNAKE_CASE__ )

						def __call__(					self     )				->						str:




									'''simple docstring'''


									return self.pa_type

						def __lowerCamelCase       (					self			,			__UpperCamelCase     )				->						dict:




									'''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(_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
												__UpperCamelCase     :     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!)
																		__UpperCamelCase     :     Any										=   np.frombuffer(value["bytes"]			,			dtype=np.intaa     ).astype(np.floataa     ) / 3_27_67
															else:
																		__UpperCamelCase     :     Union[str, Any]										=   np.memmap(value["path"]			,			dtype="h"			,			mode="r"     ).astype(np.floataa     ) / 3_27_67

															__UpperCamelCase     :     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 __lowerCamelCase       (					self			,			__UpperCamelCase			,			__UpperCamelCase = None     )				->						dict:




									'''simple docstring'''


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

									__UpperCamelCase     :     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

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

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

									else:
												__UpperCamelCase     :     str										=   sf.read(_lowercase     )

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

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

						def __lowerCamelCase       (					self     )				->						Union["FeatureType", Dict[str, "FeatureType"]]:




									'''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 __lowerCamelCase       (					self			,			__UpperCamelCase     )				->						pa.StructArray:




									'''simple docstring'''


									if pa.types.is_string(storage.type     ):
												__UpperCamelCase     :     Any										=   pa.array([None] * len(_lowercase     )			,			type=pa.binary()     )
												__UpperCamelCase     :     List[Any]										=   pa.StructArray.from_arrays([bytes_array, storage]			,			["bytes", "path"]			,			mask=storage.is_null()     )
									elif pa.types.is_binary(storage.type     ):
												__UpperCamelCase     :     int										=   pa.array([None] * len(_lowercase     )			,			type=pa.string()     )
												__UpperCamelCase     :     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"     ):
												__UpperCamelCase     :     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:
															__UpperCamelCase     :     Dict										=   storage.field("bytes"     )
												else:
															__UpperCamelCase     :     str										=   pa.array([None] * len(_lowercase     )			,			type=pa.binary()     )
												if storage.type.get_field_index("path"     ) >= 0:
															__UpperCamelCase     :     Tuple										=   storage.field("path"     )
												else:
															__UpperCamelCase     :     Optional[Any]										=   pa.array([None] * len(_lowercase     )			,			type=pa.string()     )
												__UpperCamelCase     :     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 __lowerCamelCase       (					self			,			__UpperCamelCase     )				->						pa.StructArray:




									'''simple docstring'''


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

									__UpperCamelCase     :     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()			,			)
									__UpperCamelCase     :     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()			,			)
									__UpperCamelCase     :     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"""







from ..utils import DummyObject, requires_backends

class       _a  ( metaclass=SCREAMING_SNAKE_CASE__):
			__magic_name__     					=     ["""keras_nlp"""]



			def __init__(			self							:				int   ,	*_lowercase							:				Optional[int]   ,	**_lowercase							:				Dict		)							->					List[Any]:
									requires_backends(self   ,	["keras_nlp"]		)



