






import os

import numpy
import onnx

def   snake_case (UpperCAmelCase__     ,   UpperCAmelCase__  )	->    Any:
  UpperCamelCase_: Union[str, Any]   				=    a.name
  UpperCamelCase_: Any   				=    b.name

  UpperCamelCase_: str   				=    ''
  UpperCamelCase_: Tuple   				=    ''

  UpperCamelCase_: Dict   				=    a == b

  UpperCamelCase_: List[str]   				=    name_a
  UpperCamelCase_: int   				=    name_b

  return res

def   snake_case (UpperCAmelCase__     ,   UpperCAmelCase__     ,   UpperCAmelCase__  )	->    Dict:
  for i, input_name in enumerate(node_proto.input  ):
    if input_name == name:
      node_proto.input.insert(UpperCAmelCase__     ,   UpperCAmelCase__  )
      node_proto.input.pop(i + 1  )

  if node_proto.op_type == "If":
    _graph_replace_input_with(node_proto.attribute[0].g     ,   UpperCAmelCase__     ,   UpperCAmelCase__  )
    _graph_replace_input_with(node_proto.attribute[1].g     ,   UpperCAmelCase__     ,   UpperCAmelCase__  )
  if node_proto.op_type == "Loop":
    _graph_replace_input_with(node_proto.attribute[0].g     ,   UpperCAmelCase__     ,   UpperCAmelCase__  )

def   snake_case (UpperCAmelCase__     ,   UpperCAmelCase__     ,   UpperCAmelCase__  )	->    Dict:
  for n in graph_proto.node:
    _node_replace_input_with(UpperCAmelCase__     ,   UpperCAmelCase__     ,   UpperCAmelCase__  )

def   snake_case (UpperCAmelCase__     ,   UpperCAmelCase__     ,   UpperCAmelCase__  )	->    List[str]:
  UpperCamelCase_: List[Any]   				=    list(model.graph.initializer  )
  UpperCamelCase_: Optional[int]   				=    list(model_without_ext.graph.initializer  )
  for i, ref_i in ind_to_replace:
    assert inits_with_data[i].name == inits[i].name
    assert inits_with_data[ref_i].name == inits[ref_i].name
    assert i > ref_i

    UpperCamelCase_: Any   				=    inits[i].name
    UpperCamelCase_: int   				=    inits[ref_i].name

    model_without_ext.graph.initializer.remove(inits[i]  )

    # for n in model.graph.node:
    _graph_replace_input_with(model_without_ext.graph     ,   UpperCAmelCase__     ,   UpperCAmelCase__  )

def   snake_case (UpperCAmelCase__  )	->    Tuple:
  UpperCamelCase_: Optional[Any]   				=    os.path.dirname(UpperCAmelCase__  )
  UpperCamelCase_: Optional[Any]   				=    os.path.basename(UpperCAmelCase__  )

  UpperCamelCase_: Any   				=    onnx.load(os.path.join(UpperCAmelCase__     ,   UpperCAmelCase__  )  )

  UpperCamelCase_: Tuple   				=    list(model.graph.initializer  )

  UpperCamelCase_: Optional[Any]   				=    set()
  UpperCamelCase_: str   				=    {}
  UpperCamelCase_: Any   				=    []

  UpperCamelCase_: List[str]   				=    0

  for i in range(len(UpperCAmelCase__  )  ):
    if i in dup_set:
      continue

    for j in range(i + 1     ,   len(UpperCAmelCase__  )  ):
      if j in dup_set:
        continue
      if _is_equal_tensor_proto(inits[i]     ,   inits[j]  ):
        dup_set.add(UpperCAmelCase__  )
        dup_set.add(UpperCAmelCase__  )

        UpperCamelCase_: int   				=    inits[j].data_type
        UpperCamelCase_: Optional[int]   				=    numpy.prod(inits[j].dims  )
        if dtype == 1:
          mem_size *= 4
        elif dtype == 6:
          mem_size *= 4
        elif dtype == 7 or dtype == 1_1:
          mem_size *= 8
        else:
          print('unexpected data type: '     ,   UpperCAmelCase__  )
        total_reduced_size += mem_size

        UpperCamelCase_: Tuple   				=    inits[i].name
        UpperCamelCase_: int   				=    inits[j].name

        if name_i in dup_map:
          dup_map[name_i].append(UpperCAmelCase__  )
        else:
          UpperCamelCase_: Dict   				=    [name_j]
        ind_to_replace.append((j, i)  )

  print('total reduced size: '     ,   total_reduced_size / 1_0_2_4 / 1_0_2_4 / 1_0_2_4     ,   'GB'  )

  UpperCamelCase_: Union[str, Any]   				=    sorted(UpperCAmelCase__  )
  _remove_dup_initializers_from_model(UpperCAmelCase__     ,   UpperCAmelCase__     ,   UpperCAmelCase__  )

  UpperCamelCase_: Tuple   				=    'optimized_' + model_file_name
  UpperCamelCase_: Optional[Any]   				=    os.path.join(UpperCAmelCase__     ,   UpperCAmelCase__  )
  onnx.save(UpperCAmelCase__     ,   UpperCAmelCase__  )

  return new_model







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

import numpy as np

def   snake_case (UpperCAmelCase__     ,   UpperCAmelCase__  )	->    np.array:
  UpperCamelCase_: Dict   				=    F'''{sampling_rate}'''
  UpperCamelCase_: Any   				=    '1'
  UpperCamelCase_: Any   				=    'f32le'
  UpperCamelCase_: Union[str, Any]   				=    [
      'ffmpeg',
      '-i',
      'pipe:0',
      '-ac',
      ac,
      '-ar',
      ar,
      '-f',
      format_for_conversion,
      '-hide_banner',
      '-loglevel',
      'quiet',
      'pipe:1',
  ]

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

def   snake_case (UpperCAmelCase__     ,   UpperCAmelCase__     ,   UpperCAmelCase__ = "f32le"     ,   )	->    Tuple:
  UpperCamelCase_: Any   				=    F'''{sampling_rate}'''
  UpperCamelCase_: Union[str, Any]   				=    '1'
  if format_for_conversion == "s16le":
    UpperCamelCase_: Optional[Any]   				=    2
  elif format_for_conversion == "f32le":
    UpperCamelCase_: Any   				=    4
  else:
    raise ValueError(F'''Unhandled format `{format_for_conversion}`. Please use `s16le` or `f32le`'''  )

  UpperCamelCase_: int   				=    platform.system()
  if system == "Linux":
    UpperCamelCase_: Tuple   				=    'alsa'
    UpperCamelCase_: List[str]   				=    'default'
  elif system == "Darwin":
    UpperCamelCase_: int   				=    'avfoundation'
    UpperCamelCase_: Union[str, Any]   				=    ':0'
  elif system == "Windows":
    UpperCamelCase_: Tuple   				=    'dshow'
    UpperCamelCase_: Dict   				=    'default'

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

def   snake_case (UpperCAmelCase__     ,   UpperCAmelCase__     ,   UpperCAmelCase__ = None     ,   UpperCAmelCase__ = None     ,   UpperCAmelCase__ = "f32le"     ,   )	->    Any:
  if stream_chunk_s is not None:
    UpperCamelCase_: List[Any]   				=    stream_chunk_s
  else:
    UpperCamelCase_: Dict   				=    chunk_length_s

  UpperCamelCase_: List[str]   				=    ffmpeg_microphone(UpperCAmelCase__     ,   UpperCAmelCase__     ,   format_for_conversion=UpperCAmelCase__  )
  if format_for_conversion == "s16le":
    UpperCamelCase_: Union[str, Any]   				=    np.intaa
    UpperCamelCase_: List[Any]   				=    2
  elif format_for_conversion == "f32le":
    UpperCamelCase_: str   				=    np.floataa
    UpperCamelCase_: Tuple   				=    4
  else:
    raise ValueError(F'''Unhandled format `{format_for_conversion}`. Please use `s16le` or `f32le`'''  )

  if stride_length_s is None:
    UpperCamelCase_: int   				=    chunk_length_s / 6
  UpperCamelCase_: Tuple   				=    int(round(sampling_rate * chunk_length_s  )  ) * size_of_sample
  if isinstance(UpperCAmelCase__     ,   (int, float)  ):
    UpperCamelCase_: Union[str, Any]   				=    [stride_length_s, stride_length_s]

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

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

def   snake_case (UpperCAmelCase__     ,   UpperCAmelCase__  )	->    int:
  UpperCamelCase_: Any   				=    2**2_4  # 16Mo
  try:
    with subprocess.Popen(UpperCAmelCase__     ,   stdout=subprocess.PIPE     ,   bufsize=UpperCAmelCase__  ) as ffmpeg_process:
      while True:
        UpperCamelCase_: Any   				=    ffmpeg_process.stdout.read(UpperCAmelCase__  )
        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