



"""simple docstring"""




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

import numpy as np






def      lowerCAmelCase__		(   lowerCamelCase_		:		Optional[Any]	,lowerCamelCase_		:		Tuple):





				'''simple docstring'''

				lowerCAmelCase__					:    int												=					f"""{sampling_rate}"""
				lowerCAmelCase__					:    str												=					'''1'''
				lowerCAmelCase__					:    Optional[Any]												=					'''f32le'''
				lowerCAmelCase__					:    Optional[Any]												=					[
				    '''ffmpeg''',
				    '''-i''',
				    '''pipe:0''',
				    '''-ac''',
				    ac,
				    '''-ar''',
				    ar,
				    '''-f''',
				    format_for_conversion,
				    '''-hide_banner''',
				    '''-loglevel''',
				    '''quiet''',
				    '''pipe:1''',
				]

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






def      lowerCAmelCase__		(   lowerCamelCase_		:		List[str]	,lowerCamelCase_		:		int	,lowerCamelCase_		:		List[str] = "f32le"	,):





				'''simple docstring'''

				lowerCAmelCase__					:    Union[str, Any]												=					f"""{sampling_rate}"""
				lowerCAmelCase__					:    int												=					'''1'''
				if format_for_conversion == "s16le":
								lowerCAmelCase__					:    Dict												=					2
				elif format_for_conversion == "f32le":
								lowerCAmelCase__					:    Optional[Any]												=					4
				else:
								raise ValueError(f"""Unhandled format `{format_for_conversion}`. Please use `s16le` or `f32le`""")

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

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






def      lowerCAmelCase__		(   lowerCamelCase_		:		Optional[int]	,lowerCamelCase_		:		Any	,lowerCamelCase_		:		Optional[int] = None	,lowerCamelCase_		:		Tuple = None	,lowerCamelCase_		:		List[Any] = "f32le"	,):





				'''simple docstring'''

				if stream_chunk_s is not None:
								lowerCAmelCase__					:    List[str]												=					stream_chunk_s
				else:
								lowerCAmelCase__					:    int												=					chunk_length_s

				lowerCAmelCase__					:    Union[str, Any]												=					ffmpeg_microphone(lowerCamelCase_	,lowerCamelCase_	,format_for_conversion=lowerCamelCase_)
				if format_for_conversion == "s16le":
								lowerCAmelCase__					:    Dict												=					np.intaa
								lowerCAmelCase__					:    Tuple												=					2
				elif format_for_conversion == "f32le":
								lowerCAmelCase__					:    Union[str, Any]												=					np.floataa
								lowerCAmelCase__					:    Union[str, Any]												=					4
				else:
								raise ValueError(f"""Unhandled format `{format_for_conversion}`. Please use `s16le` or `f32le`""")

				if stride_length_s is None:
								lowerCAmelCase__					:    Any												=					chunk_length_s / 6
				lowerCAmelCase__					:    Tuple												=					int(round(sampling_rate * chunk_length_s)) * size_of_sample
				if isinstance(lowerCamelCase_	,(int, float)):
								lowerCAmelCase__					:    int												=					[stride_length_s, stride_length_s]

				lowerCAmelCase__					:    Union[str, Any]												=					int(round(sampling_rate * stride_length_s[0])) * size_of_sample
				lowerCAmelCase__					:    Optional[int]												=					int(round(sampling_rate * stride_length_s[1])) * size_of_sample
				lowerCAmelCase__					:    Dict												=					datetime.datetime.now()
				lowerCAmelCase__					:    Optional[int]												=					datetime.timedelta(seconds=lowerCamelCase_)
				for item in chunk_bytes_iter(lowerCamelCase_	,lowerCamelCase_	,stride=(stride_left, stride_right)	,stream=lowerCamelCase_):
								# Put everything back in numpy scale
								lowerCAmelCase__					:    List[Any]												=					np.frombuffer(item['''raw''']	,dtype=lowerCamelCase_)
								lowerCAmelCase__					:    int												=					(
								    item['''stride'''][0] // size_of_sample,
								    item['''stride'''][1] // size_of_sample,
								)
								lowerCAmelCase__					:    int												=					sampling_rate
								audio_time += delta
								if datetime.datetime.now() > audio_time + 10 * delta:
												# We're late !! SKIP
												continue
								yield item






def      lowerCAmelCase__		(   lowerCamelCase_		:		Tuple	,lowerCamelCase_		:		Dict	,lowerCamelCase_		:		Optional[int]	,lowerCamelCase_		:		Dict = False):





				'''simple docstring'''

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






def      lowerCAmelCase__		(   lowerCamelCase_		:		str	,lowerCamelCase_		:		Tuple):





				'''simple docstring'''

				lowerCAmelCase__					:    Tuple												=					2**24  # 16Mo
				try:
								with subprocess.Popen(lowerCamelCase_	,stdout=subprocess.PIPE	,bufsize=lowerCamelCase_) as ffmpeg_process:
												while True:
																lowerCAmelCase__					:    List[str]												=					ffmpeg_process.stdout.read(lowerCamelCase_)
																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 flax.linen as nn
import jax
import jax.numpy as jnp



class 	lowerCamelCase__      (							nn.Module):




		'''simple docstring'''



		snake_case_     =42
		snake_case_     =jnp.floataa



		def 		lowerCAmelCase__				(self			)					->      List[str]:

						"""simple docstring"""






						lowerCAmelCase__					:    Dict												=					nn.Conv(
						    self.out_channels		,kernel_size=(3, 3)		,strides=(1, 1)		,padding=((1, 1), (1, 1))		,dtype=self.dtype		,)



		def __call__(self		,__lowerCamelCase			)					->      Union[str, Any]:

						"""simple docstring"""






						lowerCAmelCase__						,		lowerCAmelCase__						,		lowerCAmelCase__						,		lowerCAmelCase__					:    Dict												=					hidden_states.shape
						lowerCAmelCase__					:    Dict												=					jax.image.resize(
						    __lowerCamelCase		,shape=(batch, height * 2, width * 2, channels)		,method='''nearest'''		,)
						lowerCAmelCase__					:    Dict												=					self.conv(__lowerCamelCase			)
						return hidden_states



class 	lowerCamelCase__      (							nn.Module):




		'''simple docstring'''



		snake_case_     =42
		snake_case_     =jnp.floataa



		def 		lowerCAmelCase__				(self			)					->      int:

						"""simple docstring"""






						lowerCAmelCase__					:    List[Any]												=					nn.Conv(
						    self.out_channels		,kernel_size=(3, 3)		,strides=(2, 2)		,padding=((1, 1), (1, 1))		,dtype=self.dtype		,)



		def __call__(self		,__lowerCamelCase			)					->      Any:

						"""simple docstring"""






						lowerCAmelCase__					:    Optional[int]												=					self.conv(__lowerCamelCase			)
						return hidden_states



class 	lowerCamelCase__      (							nn.Module):




		'''simple docstring'''



		snake_case_     =42
		snake_case_     =None
		snake_case_     =0.0
		snake_case_     =None
		snake_case_     =jnp.floataa



		def 		lowerCAmelCase__				(self			)					->      int:

						"""simple docstring"""






						lowerCAmelCase__					:    List[str]												=					self.in_channels if self.out_channels is None else self.out_channels

						lowerCAmelCase__					:    Union[str, Any]												=					nn.GroupNorm(num_groups=32		,epsilon=1e-5			)
						lowerCAmelCase__					:    Union[str, Any]												=					nn.Conv(
						    __lowerCamelCase		,kernel_size=(3, 3)		,strides=(1, 1)		,padding=((1, 1), (1, 1))		,dtype=self.dtype		,)

						lowerCAmelCase__					:    int												=					nn.Dense(__lowerCamelCase		,dtype=self.dtype			)

						lowerCAmelCase__					:    List[Any]												=					nn.GroupNorm(num_groups=32		,epsilon=1e-5			)
						lowerCAmelCase__					:    Union[str, Any]												=					nn.Dropout(self.dropout_prob			)
						lowerCAmelCase__					:    Optional[int]												=					nn.Conv(
						    __lowerCamelCase		,kernel_size=(3, 3)		,strides=(1, 1)		,padding=((1, 1), (1, 1))		,dtype=self.dtype		,)

						lowerCAmelCase__					:    str												=					self.in_channels != out_channels if self.use_nin_shortcut is None else self.use_nin_shortcut

						lowerCAmelCase__					:    Union[str, Any]												=					None
						if use_nin_shortcut:
										lowerCAmelCase__					:    Optional[Any]												=					nn.Conv(
										    __lowerCamelCase		,kernel_size=(1, 1)		,strides=(1, 1)		,padding='''VALID'''		,dtype=self.dtype		,)



		def __call__(self		,__lowerCamelCase		,__lowerCamelCase		,__lowerCamelCase=True			)					->      Union[str, Any]:

						"""simple docstring"""






						lowerCAmelCase__					:    Tuple												=					hidden_states
						lowerCAmelCase__					:    Dict												=					self.norma(__lowerCamelCase			)
						lowerCAmelCase__					:    Union[str, Any]												=					nn.swish(__lowerCamelCase			)
						lowerCAmelCase__					:    List[Any]												=					self.conva(__lowerCamelCase			)

						lowerCAmelCase__					:    List[Any]												=					self.time_emb_proj(nn.swish(__lowerCamelCase			)			)
						lowerCAmelCase__					:    Dict												=					jnp.expand_dims(jnp.expand_dims(__lowerCamelCase		,1			)		,1			)
						lowerCAmelCase__					:    Optional[int]												=					hidden_states + temb

						lowerCAmelCase__					:    Optional[int]												=					self.norma(__lowerCamelCase			)
						lowerCAmelCase__					:    Optional[int]												=					nn.swish(__lowerCamelCase			)
						lowerCAmelCase__					:    int												=					self.dropout(__lowerCamelCase		,__lowerCamelCase			)
						lowerCAmelCase__					:    List[Any]												=					self.conva(__lowerCamelCase			)

						if self.conv_shortcut is not None:
										lowerCAmelCase__					:    Optional[int]												=					self.conv_shortcut(__lowerCamelCase			)

						return hidden_states + residual

