






'''simple docstring'''
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union

import numpy as np




def 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase						,		_UpperCamelCase							):


   """simple docstring"""




   lowercase_	:    Optional[int]           =     F"""{sampling_rate}"""
   lowercase_	:    Tuple           =     "1"
   lowercase_	:    Optional[Any]           =     "f32le"
   lowercase_	:    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:
         lowercase_	:    Tuple           =     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
   lowercase_	:    Optional[int]           =     output_stream[0]
   lowercase_	:    List[str]           =     np.frombuffer(_UpperCamelCase						,		np.floataa							)
   if audio.shape[0] == 0:
      raise ValueError("Malformed soundfile"							)
   return audio




def 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase						,		_UpperCamelCase						,		_UpperCamelCase = "f32le"						,		):


   """simple docstring"""




   lowercase_	:    List[str]           =     F"""{sampling_rate}"""
   lowercase_	:    Any           =     "1"
   if format_for_conversion == "s16le":
      lowercase_	:    Dict           =     2
   elif format_for_conversion == "f32le":
      lowercase_	:    Any           =     4
   else:
      raise ValueError(F"""Unhandled format `{format_for_conversion}`. Please use `s16le` or `f32le`"""							)

   lowercase_	:    str           =     platform.system()
   if system == "Linux":
      lowercase_	:    str           =     "alsa"
      lowercase_	:    Optional[Any]           =     "default"
   elif system == "Darwin":
      lowercase_	:    str           =     "avfoundation"
      lowercase_	:    Dict           =     ":0"
   elif system == "Windows":
      lowercase_	:    Tuple           =     "dshow"
      lowercase_	:    Any           =     "default"

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




def 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase						,		_UpperCamelCase						,		_UpperCamelCase = None						,		_UpperCamelCase = None						,		_UpperCamelCase = "f32le"						,		):


   """simple docstring"""




   if stream_chunk_s is not None:
      lowercase_	:    List[str]           =     stream_chunk_s
   else:
      lowercase_	:    List[Any]           =     chunk_length_s

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

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

   lowercase_	:    Tuple           =     int(round(sampling_rate * stride_length_s[0]							)							) * size_of_sample
   lowercase_	:    Optional[Any]           =     int(round(sampling_rate * stride_length_s[1]							)							) * size_of_sample
   lowercase_	:    str           =     datetime.datetime.now()
   lowercase_	:    Any           =     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
      lowercase_	:    Dict           =     np.frombuffer(item["raw"]						,		dtype=_UpperCamelCase							)
      lowercase_	:    Tuple           =     (
          item["stride"][0] // size_of_sample,
          item["stride"][1] // size_of_sample,
      )
      lowercase_	:    Dict           =     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						,		_UpperCamelCase						,		_UpperCamelCase						,		_UpperCamelCase = False							):


   """simple docstring"""




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





def 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase						,		_UpperCamelCase							):


   """simple docstring"""




   lowercase_	:    Tuple           =     2**24  # 16Mo
   try:
      with subprocess.Popen(_UpperCamelCase						,		stdout=subprocess.PIPE						,		bufsize=_UpperCamelCase							) as ffmpeg_process:
         while True:
            lowercase_	:    str           =     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












'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCamelCase__ =			logging.get_logger(__name__)

UpperCamelCase__ =			{
    'abeja/gpt-neox-japanese-2.7b': 'https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/config.json',
}


class        _UpperCAmelCase						(		snake_case			):
    __lowerCamelCase:   List[Any]		       =    'gpt_neox_japanese'




    def __init__(			self  :       List[str]  ,     a  :       List[Any]=3_2_0_0_0  ,     a  :       Union[str, Any]=2_5_6_0  ,     a  :       Optional[Any]=3_2  ,     a  :       Any=3_2  ,     a  :       str=4  ,     a  :       Optional[int]="gelu"  ,     a  :       Optional[Any]=1.00  ,     a  :       Dict=1_0_0_0_0  ,     a  :       List[Any]=2_0_4_8  ,     a  :       Dict=0.02  ,     a  :       int=1e-5  ,     a  :       Optional[int]=True  ,     a  :       Union[str, Any]=3_1_9_9_6  ,     a  :       List[Any]=3_1_9_9_9  ,     a  :       List[str]=0.1  ,     a  :       Dict=0.0  ,     **a  :       Union[str, Any]  ,     ):






       '''simple docstring'''






       super().__init__(bos_token_id=a  ,     eos_token_id=a  ,     **a			)
       lowercase_	:    int           =     vocab_size
       lowercase_	:    int           =     max_position_embeddings
       lowercase_	:    List[str]           =     hidden_size
       lowercase_	:    Any           =     num_hidden_layers
       lowercase_	:    Any           =     num_attention_heads
       lowercase_	:    List[Any]           =     intermediate_multiple_size
       lowercase_	:    List[str]           =     hidden_act
       lowercase_	:    Optional[int]           =     rotary_pct
       lowercase_	:    Tuple           =     rotary_emb_base
       lowercase_	:    Optional[Any]           =     initializer_range
       lowercase_	:    List[str]           =     layer_norm_eps
       lowercase_	:    List[str]           =     use_cache
       lowercase_	:    Any           =     attention_dropout
       lowercase_	:    List[Any]           =     hidden_dropout




