'''simple docstring'''




import argparse

import torch

from transformers import (
    WavaVecaConfig,
    WavaVecaFeatureExtractor,
    WavaVecaForAudioFrameClassification,
    WavaVecaForSequenceClassification,
    WavaVecaForXVector,
    logging,
)


logging.set_verbosity_info()
_A								=   logging.get_logger(__name__)

def _UpperCamelCase   (       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_							):
     lowercase_					:       Optional[int]     				=					WavaVecaForSequenceClassification.from_pretrained(SCREAMING_SNAKE_CASE_  ,       config=SCREAMING_SNAKE_CASE_							)
     lowercase_					:       Dict     				=					downstream_dict['projector.weight']
     lowercase_					:       Union[str, Any]     				=					downstream_dict['projector.bias']
     lowercase_					:       List[Any]     				=					downstream_dict['model.post_net.linear.weight']
     lowercase_					:       Tuple     				=					downstream_dict['model.post_net.linear.bias']
     return model

def _UpperCamelCase   (       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_							):
     lowercase_					:       Optional[Any]     				=					WavaVecaForAudioFrameClassification.from_pretrained(SCREAMING_SNAKE_CASE_  ,       config=SCREAMING_SNAKE_CASE_							)
     lowercase_					:       List[Any]     				=					downstream_dict['model.linear.weight']
     lowercase_					:       str     				=					downstream_dict['model.linear.bias']
     return model

def _UpperCamelCase   (       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_							):
     lowercase_					:       List[str]     				=					WavaVecaForXVector.from_pretrained(SCREAMING_SNAKE_CASE_  ,       config=SCREAMING_SNAKE_CASE_							)
     lowercase_					:       Optional[int]     				=					downstream_dict['connector.weight']
     lowercase_					:       Optional[Any]     				=					downstream_dict['connector.bias']
     for i, kernel_size in enumerate(hf_config.tdnn_kernel							):
          lowercase_					:       List[str]     				=					downstream_dict[
              f'''model.framelevel_feature_extractor.module.{i}.kernel.weight'''
          ]
          lowercase_					:       Dict     				=					downstream_dict[f'''model.framelevel_feature_extractor.module.{i}.kernel.bias''']

     lowercase_					:       Union[str, Any]     				=					downstream_dict['model.utterancelevel_feature_extractor.linear1.weight']
     lowercase_					:       List[str]     				=					downstream_dict['model.utterancelevel_feature_extractor.linear1.bias']
     lowercase_					:       str     				=					downstream_dict['model.utterancelevel_feature_extractor.linear2.weight']
     lowercase_					:       Optional[int]     				=					downstream_dict['model.utterancelevel_feature_extractor.linear2.bias']
     lowercase_					:       List[str]     				=					downstream_dict['objective.W']
     return model

@torch.no_grad()
def _UpperCamelCase   (       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_							):
     lowercase_					:       Any     				=					torch.load(SCREAMING_SNAKE_CASE_  ,       map_location='cpu'							)

     lowercase_					:       str     				=					checkpoint['Downstream']

     lowercase_					:       Dict     				=					WavaVecaConfig.from_pretrained(SCREAMING_SNAKE_CASE_							)
     lowercase_					:       Union[str, Any]     				=					WavaVecaFeatureExtractor.from_pretrained(
         SCREAMING_SNAKE_CASE_  ,       return_attention_mask=SCREAMING_SNAKE_CASE_  ,       do_normalize=SCREAMING_SNAKE_CASE_							)

     lowercase_					:       str     				=					hf_config.architectures[0]
     if arch.endswith('ForSequenceClassification'							):
          lowercase_					:       Union[str, Any]     				=					convert_classification(SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_							)
     elif arch.endswith('ForAudioFrameClassification'							):
          lowercase_					:       int     				=					convert_diarization(SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_							)
     elif arch.endswith('ForXVector'							):
          lowercase_					:       List[Any]     				=					convert_xvector(SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_							)
     else:
          raise NotImplementedError(f'''S3PRL weights conversion is not supported for {arch}'''							)

     if hf_config.use_weighted_layer_sum:
          lowercase_					:       Tuple     				=					checkpoint['Featurizer']['weights']

     hf_feature_extractor.save_pretrained(SCREAMING_SNAKE_CASE_							)
     hf_model.save_pretrained(SCREAMING_SNAKE_CASE_							)


if __name__ == "__main__":
 _A								=   argparse.ArgumentParser()
 parser.add_argument(
     '--base_model_name', default=None, type=str, help='Name of the huggingface pretrained base model.'
 )
 parser.add_argument('--config_path', default=None, type=str, help='Path to the huggingface classifier config.')
 parser.add_argument('--checkpoint_path', default=None, type=str, help='Path to the s3prl checkpoint.')
 parser.add_argument('--model_dump_path', default=None, type=str, help='Path to the final converted model.')
 _A								=   parser.parse_args()
 convert_saprl_checkpoint(args.base_model_name, args.config_path, args.checkpoint_path, args.model_dump_path)





'''simple docstring'''




import os
import string
import sys


_A								=   1 << 8

_A								=   {
    'tab': ord('\t'),
    'newline': ord('\r'),
    'esc': 2_7,
    'up': 6_5 + ARROW_KEY_FLAG,
    'down': 6_6 + ARROW_KEY_FLAG,
    'right': 6_7 + ARROW_KEY_FLAG,
    'left': 6_8 + ARROW_KEY_FLAG,
    'mod_int': 9_1,
    'undefined': sys.maxsize,
    'interrupt': 3,
    'insert': 5_0,
    'delete': 5_1,
    'pg_up': 5_3,
    'pg_down': 5_4,
}

_A								=   KEYMAP['up']
_A								=   KEYMAP['left']

if sys.platform == "win32":
 _A								=   []
 _A								=   {
     b'\xe0H': KEYMAP['up'] - ARROW_KEY_FLAG,
     b'\x00H': KEYMAP['up'] - ARROW_KEY_FLAG,
     b'\xe0P': KEYMAP['down'] - ARROW_KEY_FLAG,
     b'\x00P': KEYMAP['down'] - ARROW_KEY_FLAG,
     b'\xe0M': KEYMAP['right'] - ARROW_KEY_FLAG,
     b'\x00M': KEYMAP['right'] - ARROW_KEY_FLAG,
     b'\xe0K': KEYMAP['left'] - ARROW_KEY_FLAG,
     b'\x00K': KEYMAP['left'] - ARROW_KEY_FLAG,
 }

for i in range(1_0):
 _A								=   ord(str(i))

def _UpperCamelCase   (       ):
     if os.name == "nt":
          import msvcrt

          lowercase_					:       Optional[Any]     				=					'mbcs'
          # Flush the keyboard buffer
          while msvcrt.kbhit():
               msvcrt.getch()
          if len(SCREAMING_SNAKE_CASE_							) == 0:
               # Read the keystroke
               lowercase_					:       int     				=					msvcrt.getch()

               # If it is a prefix char, get second part
               if ch in (b"\x00", b"\xe0"):
                    lowercase_					:       int     				=					ch + msvcrt.getch()
                    # Translate actual Win chars to bullet char types
                    try:
                         lowercase_					:       List[Any]     				=					chr(WIN_KEYMAP[cha]							)
                         WIN_CH_BUFFER.append(chr(KEYMAP['mod_int']							)							)
                         WIN_CH_BUFFER.append(SCREAMING_SNAKE_CASE_							)
                         if ord(SCREAMING_SNAKE_CASE_							) in (
                             KEYMAP["insert"] - 1 << 9,
                             KEYMAP["delete"] - 1 << 9,
                             KEYMAP["pg_up"] - 1 << 9,
                             KEYMAP["pg_down"] - 1 << 9,
                         ):
                              WIN_CH_BUFFER.append(chr(126							)							)
                         lowercase_					:       Optional[int]     				=					chr(KEYMAP['esc']							)
                    except KeyError:
                         lowercase_					:       Tuple     				=					cha[1]
               else:
                    lowercase_					:       Tuple     				=					ch.decode(SCREAMING_SNAKE_CASE_							)
          else:
               lowercase_					:       Dict     				=					WIN_CH_BUFFER.pop(0							)
     elif os.name == "posix":
          import termios
          import tty

          lowercase_					:       int     				=					sys.stdin.fileno()
          lowercase_					:       Union[str, Any]     				=					termios.tcgetattr(SCREAMING_SNAKE_CASE_							)
          try:
               tty.setraw(SCREAMING_SNAKE_CASE_							)
               lowercase_					:       Any     				=					sys.stdin.read(1							)
          finally:
               termios.tcsetattr(SCREAMING_SNAKE_CASE_  ,       termios.TCSADRAIN  ,       SCREAMING_SNAKE_CASE_							)
     return ch






def _UpperCamelCase   (       ):
     lowercase_					:       Union[str, Any]     				=					get_raw_chars()
     if ord(SCREAMING_SNAKE_CASE_							) in [KEYMAP["interrupt"], KEYMAP["newline"]]:
          return char

     elif ord(SCREAMING_SNAKE_CASE_							) == KEYMAP["esc"]:
          lowercase_					:       Any     				=					get_raw_chars()
          if ord(SCREAMING_SNAKE_CASE_							) == KEYMAP["mod_int"]:
               lowercase_					:       Dict     				=					get_raw_chars()
               if ord(SCREAMING_SNAKE_CASE_							) >= KEYMAP["arrow_begin"] - ARROW_KEY_FLAG and ord(SCREAMING_SNAKE_CASE_							) <= KEYMAP["arrow_end"] - ARROW_KEY_FLAG:
                    return chr(ord(SCREAMING_SNAKE_CASE_							) + ARROW_KEY_FLAG							)
               else:
                    return KEYMAP["undefined"]
          else:
               return get_raw_chars()

     else:
          if char in string.printable:
               return char
          else:
               return KEYMAP["undefined"]




