

'''simple docstring'''

import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union

import numpy as np



def 							UpperCamelCase__			(			a__			,      a__      ):


						'''simple docstring'''






						_lowerCAmelCase										=F'''{sampling_rate}'''
						_lowerCAmelCase										="1"
						_lowerCAmelCase										="f32le"
						_lowerCAmelCase										=[
						    "ffmpeg",
						    "-i",
						    "pipe:0",
						    "-ac",
						    ac,
						    "-ar",
						    ar,
						    "-f",
						    format_for_conversion,
						    "-hide_banner",
						    "-loglevel",
						    "quiet",
						    "pipe:1",
						]

						try:
												with subprocess.Popen(a__			,      stdin=subprocess.PIPE			,      stdout=subprocess.PIPE      ) as ffmpeg_process:
																		_lowerCAmelCase										=ffmpeg_process.communicate(a__      )
						except FileNotFoundError as error:
												raise ValueError('ffmpeg was not found but is required to load audio files from filename'      ) from error
						_lowerCAmelCase										=output_stream[0]
						_lowerCAmelCase										=np.frombuffer(a__			,      np.floataa      )
						if audio.shape[0] == 0:
												raise ValueError('Malformed soundfile'      )
						return audio



def 							UpperCamelCase__			(			a__			,      a__			,      a__ = "f32le"			,      ):


						'''simple docstring'''






						_lowerCAmelCase										=F'''{sampling_rate}'''
						_lowerCAmelCase										="1"
						if format_for_conversion == "s16le":
												_lowerCAmelCase										=2
						elif format_for_conversion == "f32le":
												_lowerCAmelCase										=4
						else:
												raise ValueError(F'''Unhandled format `{format_for_conversion}`. Please use `s16le` or `f32le`'''      )

						_lowerCAmelCase										=platform.system()
						if system == "Linux":
												_lowerCAmelCase										="alsa"
												_lowerCAmelCase										="default"
						elif system == "Darwin":
												_lowerCAmelCase										="avfoundation"
												_lowerCAmelCase										=":0"
						elif system == "Windows":
												_lowerCAmelCase										="dshow"
												_lowerCAmelCase										="default"

						_lowerCAmelCase										=[
						    "ffmpeg",
						    "-f",
						    format_,
						    "-i",
						    input_,
						    "-ac",
						    ac,
						    "-ar",
						    ar,
						    "-f",
						    format_for_conversion,
						    "-fflags",
						    "nobuffer",
						    "-hide_banner",
						    "-loglevel",
						    "quiet",
						    "pipe:1",
						]
						_lowerCAmelCase										=int(round(sampling_rate * chunk_length_s      )      ) * size_of_sample
						_lowerCAmelCase										=_ffmpeg_stream(a__			,      a__      )
						for item in iterator:
												yield item



def 							UpperCamelCase__			(			a__			,      a__			,      a__ = None			,      a__ = None			,      a__ = "f32le"			,      ):


						'''simple docstring'''






						if stream_chunk_s is not None:
												_lowerCAmelCase										=stream_chunk_s
						else:
												_lowerCAmelCase										=chunk_length_s

						_lowerCAmelCase										=ffmpeg_microphone(a__			,      a__			,      format_for_conversion=a__      )
						if format_for_conversion == "s16le":
												_lowerCAmelCase										=np.intaa
												_lowerCAmelCase										=2
						elif format_for_conversion == "f32le":
												_lowerCAmelCase										=np.floataa
												_lowerCAmelCase										=4
						else:
												raise ValueError(F'''Unhandled format `{format_for_conversion}`. Please use `s16le` or `f32le`'''      )

						if stride_length_s is None:
												_lowerCAmelCase										=chunk_length_s / 6
						_lowerCAmelCase										=int(round(sampling_rate * chunk_length_s      )      ) * size_of_sample
						if isinstance(a__			,      (int, float)      ):
												_lowerCAmelCase										=[stride_length_s, stride_length_s]

						_lowerCAmelCase										=int(round(sampling_rate * stride_length_s[0]      )      ) * size_of_sample
						_lowerCAmelCase										=int(round(sampling_rate * stride_length_s[1]      )      ) * size_of_sample
						_lowerCAmelCase										=datetime.datetime.now()
						_lowerCAmelCase										=datetime.timedelta(seconds=a__      )
						for item in chunk_bytes_iter(a__			,      a__			,      stride=(stride_left, stride_right)			,      stream=a__      ):
												# Put everything back in numpy scale
												_lowerCAmelCase										=np.frombuffer(item['raw']			,      dtype=a__      )
												_lowerCAmelCase										=(
												    item["stride"][0] // size_of_sample,
												    item["stride"][1] // size_of_sample,
												)
												_lowerCAmelCase										=sampling_rate
												audio_time += delta
												if datetime.datetime.now() > audio_time + 1_0 * delta:
																		# We're late !! SKIP
																		continue
												yield item



def 							UpperCamelCase__			(			a__			,      a__			,      a__			,      a__ = False      ):


						'''simple docstring'''






						_lowerCAmelCase										=b""
						_lowerCAmelCase										=stride
						if stride_left + stride_right >= chunk_len:
												raise ValueError(
												    F'''Stride needs to be strictly smaller than chunk_len: ({stride_left}, {stride_right}) vs {chunk_len}'''      )
						_lowerCAmelCase										=0
						for raw in iterator:
												acc += raw
												if stream and len(a__      ) < chunk_len:
																		_lowerCAmelCase										=(_stride_left, 0)
																		yield {"raw": acc[:chunk_len], "stride": stride, "partial": True}
												else:
																		while len(a__      ) >= chunk_len:
																								# We are flushing the accumulator
																								_lowerCAmelCase										=(_stride_left, stride_right)
																								_lowerCAmelCase										={"raw": acc[:chunk_len], "stride": stride}
																								if stream:
																														_lowerCAmelCase										=False
																								yield item
																								_lowerCAmelCase										=stride_left
																								_lowerCAmelCase										=acc[chunk_len - stride_left - stride_right :]
    # Last chunk
						if len(a__      ) > stride_left:
												_lowerCAmelCase										={"raw": acc, "stride": (_stride_left, 0)}
												if stream:
																		_lowerCAmelCase										=False
												yield item



def 							UpperCamelCase__			(			a__			,      a__      ):


						'''simple docstring'''






						_lowerCAmelCase										=2**2_4  # 16Mo
						try:
												with subprocess.Popen(a__			,      stdout=subprocess.PIPE			,      bufsize=a__      ) as ffmpeg_process:
																		while True:
																								_lowerCAmelCase										=ffmpeg_process.stdout.read(a__      )
																								if raw == b"":
																														break
																								yield raw
						except FileNotFoundError as error:
												raise ValueError('ffmpeg was not found but is required to stream audio files from filename'      ) from error






'''simple docstring'''

lowercase_     		= '''
# Installazione di Transformers
! pip install transformers datasets
# Per installare dalla fonte invece dell\'ultima versione rilasciata, commenta il comando sopra e
# rimuovi la modalità commento al comando seguente.
# ! pip install git+https://github.com/huggingface/transformers.git
'''

lowercase_     		= [{'''type''': '''code''', '''content''': INSTALL_CONTENT}]
lowercase_     		= {
    '''{processor_class}''': '''FakeProcessorClass''',
    '''{model_class}''': '''FakeModelClass''',
    '''{object_class}''': '''FakeObjectClass''',
}





