


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__  :Optional[int]             =							False, False, False

@dataclass
class 		__a				:
		_a     :  Optional[int]           =     None
		_a     :  str           =     True
		_a     :  int           =     True
		_a     :  Tuple           =     None
		# Automatically constructed
		_a     :  Optional[int]           =     'dict'
		_a     :  Tuple           =     pa.struct({'bytes': pa.binary(), 'path': pa.string()}      )
		_a     :  Union[str, Any]           =     field(default='Audio'   ,				init=lowerCamelCase__   ,				repr=lowerCamelCase__      )
		def __call__(      self						)			->	Optional[int]:




									"""simple docstring"""





									return self.pa_type
		def      UpperCAmelCase__    (      self      ,   _SCREAMING_SNAKE_CASE						)			->	List[str]:




									"""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(_SCREAMING_SNAKE_CASE      ,   _SCREAMING_SNAKE_CASE						):
																return {"bytes": None, "path": value}
									elif isinstance(_SCREAMING_SNAKE_CASE      ,   _SCREAMING_SNAKE_CASE						):
																return {"bytes": value, "path": None}
									elif "array" in value:
																# convert the audio array to wav bytes
																_UpperCAmelCase					=      BytesIO()
																sf.write(_SCREAMING_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						) / 32767
																							else:
																														_UpperCAmelCase					=      np.memmap(value['path']      ,   dtype='h'      ,   mode='r'						).astype(np.floataa						) / 32767

																							_UpperCAmelCase					=      BytesIO(bytes()						)
																							sf.write(_SCREAMING_SNAKE_CASE      ,   _SCREAMING_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      UpperCAmelCase__    (      self      ,   _SCREAMING_SNAKE_CASE      ,   _SCREAMING_SNAKE_CASE = None						)			->	int:




									"""simple docstring"""





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

									_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(_SCREAMING_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(_SCREAMING_SNAKE_CASE      ,   config.HUB_DATASETS_URL						)["repo_id"]
																							_UpperCAmelCase					=      token_per_repo_id[repo_id]
																except (ValueError, KeyError):
																							_UpperCAmelCase					=      None

																with xopen(_SCREAMING_SNAKE_CASE      ,   'rb'      ,   use_auth_token=_SCREAMING_SNAKE_CASE						) as f:
																							_UpperCAmelCase					=      sf.read(_SCREAMING_SNAKE_CASE						)

									else:
																_UpperCAmelCase					=      sf.read(_SCREAMING_SNAKE_CASE						)

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

									return {"path": path, "array": array, "sampling_rate": sampling_rate}
		def      UpperCAmelCase__    (      self						)			->	List[Any]:




									"""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      UpperCAmelCase__    (      self      ,   _SCREAMING_SNAKE_CASE						)			->	List[str]:




									"""simple docstring"""





									if pa.types.is_string(storage.type						):
																_UpperCAmelCase					=      pa.array([None] * len(_SCREAMING_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(_SCREAMING_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(_SCREAMING_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(_SCREAMING_SNAKE_CASE						)      ,   type=pa.binary()						)
																if storage.type.get_field_index('path'						) >= 0:
																							_UpperCAmelCase					=      storage.field('path'						)
																else:
																							_UpperCAmelCase					=      pa.array([None] * len(_SCREAMING_SNAKE_CASE						)      ,   type=pa.string()						)
																_UpperCAmelCase					=      pa.StructArray.from_arrays([bytes_array, path_array]      ,   ['bytes', 'path']      ,   mask=storage.is_null()						)
									return array_cast(_SCREAMING_SNAKE_CASE      ,   self.pa_type						)






		def      UpperCAmelCase__    (      self      ,   _SCREAMING_SNAKE_CASE						)			->	List[Any]:




									"""simple docstring"""





									@no_op_if_value_is_null
									def path_to_bytes(_SCREAMING_SNAKE_CASE						):
																with xopen(_SCREAMING_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(_SCREAMING_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(_SCREAMING_SNAKE_CASE      ,   self.pa_type						)




import math
import random

def 	lowerCAmelCase__			(      a__:		float      ,  a__:		bool = False	)  ->		float:


							'''simple docstring'''





							if deriv:
														return value * (1 - value)
							return 1 / (1 + math.exp(-value	))


# Initial Value
lowerCAmelCase__  :Optional[Any]             =							0.02

def 	lowerCAmelCase__			(      a__:		int      ,  a__:		int	)  ->		float:


							'''simple docstring'''





							_UpperCAmelCase					=      float(2 * (random.randint(1      ,  1_0_0	)) - 1	)

							for _ in range(a__	):
														# Forward propagation
														_UpperCAmelCase					=      sigmoid_function(INITIAL_VALUE * weight	)
														# How much did we miss?
														_UpperCAmelCase					=      (expected / 1_0_0) - layer_a
														# Error delta
														_UpperCAmelCase					=      layer_1_error * sigmoid_function(a__      ,  a__	)
														# Update weight
														weight += INITIAL_VALUE * layer_1_delta

							return layer_a * 1_0_0


if __name__ == "__main__":
		import doctest

		doctest.testmod()

		lowerCAmelCase__  :List[Any]             =							int(input('''Expected value: '''))
		lowerCAmelCase__  :Any             =							int(input('''Number of propagations: '''))
		print(forward_propagation(expected, number_propagations))
