


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

import numpy as np







def        _lowerCamelCase(	lowercase__   , lowercase__	)						->	Optional[int]:

		'''simple docstring'''







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

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







def        _lowerCamelCase(	lowercase__   , lowercase__   , lowercase__ = "f32le"   , )						->	List[Any]:

		'''simple docstring'''







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

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

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







def        _lowerCamelCase(	lowercase__   , lowercase__   , lowercase__ = None   , lowercase__ = None   , lowercase__ = "f32le"   , )						->	int:

		'''simple docstring'''







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

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

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

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







def        _lowerCamelCase(	lowercase__   , lowercase__   , lowercase__   , lowercase__ = False	)						->	Any:

		'''simple docstring'''







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







def        _lowerCamelCase(	lowercase__   , lowercase__	)						->	Optional[Any]:

		'''simple docstring'''







		__lowercase=			2**2_4  # 16Mo
		try:
				with subprocess.Popen(lowercase__   , stdout=subprocess.PIPE   , bufsize=lowercase__	) as ffmpeg_process:
						while True:
								__lowercase=			ffmpeg_process.stdout.read(lowercase__	)
								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 ...configuration_utils import PretrainedConfig
from ...utils import logging


_snake_case     :		Optional[int]       						= logging.get_logger(__name__)

_snake_case     :		Optional[int]       						= {
    'google/vivit-b-16x2-kinetics400': (
        'https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/config.json'
    ),
    # See all Vivit models at https://huggingface.co/models?filter=vivit
}






class 					_UpperCAmelCase   (	lowercase_ ):
					UpperCamelCase      =							'''vivit'''


					def __init__(					self			:Optional[Any]     ,       __UpperCamelCase			:Dict=2_24     ,       __UpperCamelCase			:int=32     ,       __UpperCamelCase			:Union[str, Any]=[2, 16, 16]     ,       __UpperCamelCase			:Optional[Any]=3     ,       __UpperCamelCase			:Optional[Any]=7_68     ,       __UpperCamelCase			:Any=12     ,       __UpperCamelCase			:List[str]=12     ,       __UpperCamelCase			:List[str]=30_72     ,       __UpperCamelCase			:Any="gelu_fast"     ,       __UpperCamelCase			:List[Any]=0.0     ,       __UpperCamelCase			:str=0.0     ,       __UpperCamelCase			:Dict=0.02     ,       __UpperCamelCase			:Optional[Any]=1e-06     ,       __UpperCamelCase			:Dict=True     ,       **__UpperCamelCase			:Tuple     ,       ):
												A		=  hidden_size
												A		=  num_hidden_layers
												A		=  num_attention_heads
												A		=  intermediate_size
												A		=  hidden_act
												A		=  hidden_dropout_prob
												A		=  attention_probs_dropout_prob
												A		=  initializer_range
												A		=  layer_norm_eps

												A		=  image_size
												A		=  num_frames
												A		=  tubelet_size
												A		=  num_channels
												A		=  qkv_bias

												super().__init__(**__UpperCamelCase		)


