





'''simple docstring'''







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

import numpy as np

def    __UpperCamelCase	(	a    : bytes					,   a    : int     ) ->np.array:
 snake_case				=			f"""{sampling_rate}"""
 snake_case				=			'''1'''
 snake_case				=			'''f32le'''
 snake_case				=			[
     '''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:
   snake_case				=			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
 snake_case				=			output_stream[0]
 snake_case				=			np.frombuffer(a					,   np.floataa     )
 if audio.shape[0] == 0:
  raise ValueError('''Malformed soundfile'''     )
 return audio

def    __UpperCamelCase	(	a    : int					,   a    : float					,   a    : str = "f32le"					,   ) ->int:
 snake_case				=			f"""{sampling_rate}"""
 snake_case				=			'''1'''
 if format_for_conversion == "s16le":
  snake_case				=			2
 elif format_for_conversion == "f32le":
  snake_case				=			4
 else:
  raise ValueError(f"""Unhandled format `{format_for_conversion}`. Please use `s16le` or `f32le`"""     )

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

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

def    __UpperCamelCase	(	a    : int					,   a    : float					,   a    : Optional[int] = None					,   a    : Optional[Union[Tuple[float, float], float]] = None					,   a    : str = "f32le"					,   ) ->Union[str, Any]:
 if stream_chunk_s is not None:
  snake_case				=			stream_chunk_s
 else:
  snake_case				=			chunk_length_s

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

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

 snake_case				=			int(round(sampling_rate * stride_length_s[0]     )     ) * size_of_sample
 snake_case				=			int(round(sampling_rate * stride_length_s[1]     )     ) * size_of_sample
 snake_case				=			datetime.datetime.now()
 snake_case				=			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
  snake_case				=			np.frombuffer(item['''raw''']					,   dtype=a     )
  snake_case				=			(
      item['''stride'''][0] // size_of_sample,
      item['''stride'''][1] // size_of_sample,
  )
  snake_case				=			sampling_rate
  audio_time += delta
  if datetime.datetime.now() > audio_time + 10 * delta:
   # We're late !! SKIP
   continue
  yield item

def    __UpperCamelCase	(	a    : List[Any]					,   a    : int					,   a    : Tuple[int, int]					,   a    : bool = False     ) ->Optional[Any]:
 snake_case				=			b''''''
 snake_case				,		snake_case				=			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}"""     )
 snake_case				=			0
 for raw in iterator:
  acc += raw
  if stream and len(a     ) < chunk_len:
   snake_case				=			(_stride_left, 0)
   yield {"raw": acc[:chunk_len], "stride": stride, "partial": True}
  else:
   while len(a     ) >= chunk_len:
    # We are flushing the accumulator
    snake_case				=			(_stride_left, stride_right)
    snake_case				=			{'''raw''': acc[:chunk_len], '''stride''': stride}
    if stream:
     snake_case				=			False
    yield item
    snake_case				=			stride_left
    snake_case				=			acc[chunk_len - stride_left - stride_right :]
    # Last chunk
 if len(a     ) > stride_left:
  snake_case				=			{'''raw''': acc, '''stride''': (_stride_left, 0)}
  if stream:
   snake_case				=			False
  yield item






def    __UpperCamelCase	(	a    : Optional[int]					,   a    : int     ) ->Optional[int]:
 snake_case				=			2**24  # 16Mo
 try:
  with subprocess.Popen(a					,   stdout=subprocess.PIPE					,   bufsize=a     ) as ffmpeg_process:
   while True:
    snake_case				=			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'''







from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable


try:
   if not (is_transformers_available() and is_torch_available()):
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   from ...utils.dummy_torch_and_transformers_objects import *  # noqa F403
else:
   from .notes_encoder import SpectrogramNotesEncoder
   from .continous_encoder import SpectrogramContEncoder
   from .pipeline_spectrogram_diffusion import (
       SpectrogramContEncoder,
       SpectrogramDiffusionPipeline,
       TaFilmDecoder,
   )

try:
   if not (is_transformers_available() and is_torch_available() and is_note_seq_available()):
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   from ...utils.dummy_transformers_and_torch_and_note_seq_objects import *  # noqa F403
else:
   from .midi_utils import MidiProcessor

