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

import numpy as np



def      __SCREAMING_SNAKE_CASE  ( __UpperCamelCase   :	bytes			,					__UpperCamelCase   :	int     )							-> np.array:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__      							=				f"""{sampling_rate}"""
  SCREAMING_SNAKE_CASE__      							=				"""1"""
  SCREAMING_SNAKE_CASE__      							=				"""f32le"""
  SCREAMING_SNAKE_CASE__      							=				[
      """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:
      SCREAMING_SNAKE_CASE__      							=				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
  SCREAMING_SNAKE_CASE__      							=				output_stream[0]
  SCREAMING_SNAKE_CASE__      							=				np.frombuffer(__UpperCamelCase			,					np.floataa     )
  if audio.shape[0] == 0:
    raise ValueError("""Malformed soundfile"""     )
  return audio



def      __SCREAMING_SNAKE_CASE  ( __UpperCamelCase   :	int			,					__UpperCamelCase   :	float			,					__UpperCamelCase   :	str = "f32le"			,					)							-> Optional[int]:







  """simple docstring"""





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

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

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



def      __SCREAMING_SNAKE_CASE  ( __UpperCamelCase   :	int			,					__UpperCamelCase   :	float			,					__UpperCamelCase   :	Optional[int] = None			,					__UpperCamelCase   :	Optional[Union[Tuple[float, float], float]] = None			,					__UpperCamelCase   :	str = "f32le"			,					)							-> Optional[Any]:







  """simple docstring"""





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

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

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

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



def      __SCREAMING_SNAKE_CASE  ( __UpperCamelCase   :	Dict			,					__UpperCamelCase   :	int			,					__UpperCamelCase   :	Tuple[int, int]			,					__UpperCamelCase   :	bool = False     )							-> Optional[int]:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__      							=				B""""""
  SCREAMING_SNAKE_CASE__							,					SCREAMING_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}"""     )
  SCREAMING_SNAKE_CASE__      							=				0
  for raw in iterator:
    acc += raw
    if stream and len(__UpperCamelCase     ) < chunk_len:
      SCREAMING_SNAKE_CASE__      							=				(_stride_left, 0)
      yield {"raw": acc[:chunk_len], "stride": stride, "partial": True}
    else:
      while len(__UpperCamelCase     ) >= chunk_len:
        # We are flushing the accumulator
        SCREAMING_SNAKE_CASE__      							=				(_stride_left, stride_right)
        SCREAMING_SNAKE_CASE__      							=				{"""raw""": acc[:chunk_len], """stride""": stride}
        if stream:
          SCREAMING_SNAKE_CASE__      							=				False
        yield item
        SCREAMING_SNAKE_CASE__      							=				stride_left
        SCREAMING_SNAKE_CASE__      							=				acc[chunk_len - stride_left - stride_right :]
    # Last chunk
  if len(__UpperCamelCase     ) > stride_left:
    SCREAMING_SNAKE_CASE__      							=				{"""raw""": acc, """stride""": (_stride_left, 0)}
    if stream:
      SCREAMING_SNAKE_CASE__      							=				False
    yield item






def      __SCREAMING_SNAKE_CASE  ( __UpperCamelCase   :	Union[str, Any]			,					__UpperCamelCase   :	int     )							-> Optional[Any]:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__      							=				2**24  # 16Mo
  try:
    with subprocess.Popen(__UpperCamelCase			,					stdout=subprocess.PIPE			,					bufsize=__UpperCamelCase     ) as ffmpeg_process:
      while True:
        SCREAMING_SNAKE_CASE__      							=				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

import contextlib
import importlib
import io
import unittest

import transformers

# Try to import everything from transformers to ensure every object can be loaded.
from transformers import *  # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, require_tf, require_torch
from transformers.utils import ContextManagers, find_labels, is_flax_available, is_tf_available, is_torch_available


if is_torch_available():
   from transformers import BertForPreTraining, BertForQuestionAnswering, BertForSequenceClassification

if is_tf_available():
   from transformers import TFBertForPreTraining, TFBertForQuestionAnswering, TFBertForSequenceClassification

if is_flax_available():
   from transformers import FlaxBertForPreTraining, FlaxBertForQuestionAnswering, FlaxBertForSequenceClassification


__lowerCamelCase      :			Tuple							       =		DUMMY_UNKNOWN_IDENTIFIER
# An actual model hosted on huggingface.co

__lowerCamelCase      :			Optional[Any]							       =		'''main'''
# Default branch name
__lowerCamelCase      :			Optional[int]							       =		'''f2c752cfc5c0ab6f4bdec59acea69eefbee381c2'''
# One particular commit (not the top of `main`)
__lowerCamelCase      :			Any							       =		'''aaaaaaa'''
# This commit does not exist, so we should 404.

__lowerCamelCase      :			List[str]							       =		'''d9e9f15bc825e4b2c9249e9578f884bbcb5e3684'''
# Sha-1 of config.json on the top of `main`, for checking purposes
__lowerCamelCase      :			List[Any]							       =		'''4b243c475af8d0a7754e87d7d096c92e5199ec2fe168a2ee7998e3b8e9bcb1d3'''



@contextlib.contextmanager
def      __SCREAMING_SNAKE_CASE  ( )							-> str:







  """simple docstring"""





  print("""Welcome!"""     )
  yield
  print("""Bye!"""     )



@contextlib.contextmanager
def      __SCREAMING_SNAKE_CASE  ( )							-> Any:







  """simple docstring"""





  print("""Bonjour!"""     )
  yield
  print("""Au revoir!"""     )







class __snake_case    (						unittest.TestCase		):




   def      __a						(   self      :    List[Any]				):



     """simple docstring"""






     assert transformers.__spec__ is not None
     assert importlib.util.find_spec("""transformers"""				) is not None







class __snake_case    (						unittest.TestCase		):




   @unittest.mock.patch("""sys.stdout"""	,     new_callable=io.StringIO				)
   def      __a						(   self      :    List[str]	,     _lowercase      :    str				):



     """simple docstring"""






     with ContextManagers([]				):
       print("""Transformers are awesome!"""				)
     # The print statement adds a new line at the end of the output
     self.assertEqual(mock_stdout.getvalue()	,     """Transformers are awesome!\n"""				)




   @unittest.mock.patch("""sys.stdout"""	,     new_callable=io.StringIO				)
   def      __a						(   self      :    Optional[Any]	,     _lowercase      :    str				):



     """simple docstring"""






     with ContextManagers([context_en()]				):
       print("""Transformers are awesome!"""				)
     # The output should be wrapped with an English welcome and goodbye
     self.assertEqual(mock_stdout.getvalue()	,     """Welcome!\nTransformers are awesome!\nBye!\n"""				)




   @unittest.mock.patch("""sys.stdout"""	,     new_callable=io.StringIO				)
   def      __a						(   self      :    Tuple	,     _lowercase      :    Dict				):



     """simple docstring"""






     with ContextManagers([context_fr(), context_en()]				):
       print("""Transformers are awesome!"""				)
     # The output should be wrapped with an English and French welcome and goodbye
     self.assertEqual(mock_stdout.getvalue()	,     """Bonjour!\nWelcome!\nTransformers are awesome!\nBye!\nAu revoir!\n"""				)




   @require_torch
   def      __a						(   self      :    Union[str, Any]				):



     """simple docstring"""






     self.assertEqual(find_labels(_lowercase				)	,     ["""labels"""]				)
     self.assertEqual(find_labels(_lowercase				)	,     ["""labels""", """next_sentence_label"""]				)
     self.assertEqual(find_labels(_lowercase				)	,     ["""start_positions""", """end_positions"""]				)







     class __snake_case    (						lowerCamelCase_		):
        pass





     self.assertEqual(find_labels(_lowercase				)	,     ["""labels"""]				)




   @require_tf
   def      __a						(   self      :    Any				):



     """simple docstring"""






     self.assertEqual(find_labels(_lowercase				)	,     ["""labels"""]				)
     self.assertEqual(find_labels(_lowercase				)	,     ["""labels""", """next_sentence_label"""]				)
     self.assertEqual(find_labels(_lowercase				)	,     ["""start_positions""", """end_positions"""]				)







     class __snake_case    (						lowerCamelCase_		):
        pass





     self.assertEqual(find_labels(_lowercase				)	,     ["""labels"""]				)




   @require_flax
   def      __a						(   self      :    Union[str, Any]				):



     """simple docstring"""






     self.assertEqual(find_labels(_lowercase				)	,     []				)
     self.assertEqual(find_labels(_lowercase				)	,     []				)
     self.assertEqual(find_labels(_lowercase				)	,     []				)







     class __snake_case    (						lowerCamelCase_		):
        pass





     self.assertEqual(find_labels(_lowercase				)	,     []				)
