

import argparse

import torch

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


logging.set_verbosity_info()
UpperCamelCase__  :      Dict			=    logging.get_logger(__name__)


def 					_UpperCAmelCase       (  _SCREAMING_SNAKE_CASE					:		List[str] ,   _SCREAMING_SNAKE_CASE					:		Union[str, Any] ,   _SCREAMING_SNAKE_CASE					:		Optional[Any]       ):





    """simple docstring"""


    SCREAMING_SNAKE_CASE_									=						WavaVecaForSequenceClassification.from_pretrained(_SCREAMING_SNAKE_CASE ,   config=_SCREAMING_SNAKE_CASE       )
    SCREAMING_SNAKE_CASE_									=						downstream_dict['projector.weight']
    SCREAMING_SNAKE_CASE_									=						downstream_dict['projector.bias']
    SCREAMING_SNAKE_CASE_									=						downstream_dict['model.post_net.linear.weight']
    SCREAMING_SNAKE_CASE_									=						downstream_dict['model.post_net.linear.bias']
    return model


def 					_UpperCAmelCase       (  _SCREAMING_SNAKE_CASE					:		Optional[int] ,   _SCREAMING_SNAKE_CASE					:		Optional[int] ,   _SCREAMING_SNAKE_CASE					:		Optional[int]       ):





    """simple docstring"""


    SCREAMING_SNAKE_CASE_									=						WavaVecaForAudioFrameClassification.from_pretrained(_SCREAMING_SNAKE_CASE ,   config=_SCREAMING_SNAKE_CASE       )
    SCREAMING_SNAKE_CASE_									=						downstream_dict['model.linear.weight']
    SCREAMING_SNAKE_CASE_									=						downstream_dict['model.linear.bias']
    return model


def 					_UpperCAmelCase       (  _SCREAMING_SNAKE_CASE					:		List[str] ,   _SCREAMING_SNAKE_CASE					:		str ,   _SCREAMING_SNAKE_CASE					:		Tuple       ):





    """simple docstring"""


    SCREAMING_SNAKE_CASE_									=						WavaVecaForXVector.from_pretrained(_SCREAMING_SNAKE_CASE ,   config=_SCREAMING_SNAKE_CASE       )
    SCREAMING_SNAKE_CASE_									=						downstream_dict['connector.weight']
    SCREAMING_SNAKE_CASE_									=						downstream_dict['connector.bias']
    for i, kernel_size in enumerate(hf_config.tdnn_kernel       ):
        SCREAMING_SNAKE_CASE_									=						downstream_dict[
            f"""model.framelevel_feature_extractor.module.{i}.kernel.weight"""
        ]
        SCREAMING_SNAKE_CASE_									=						downstream_dict[f"""model.framelevel_feature_extractor.module.{i}.kernel.bias"""]

    SCREAMING_SNAKE_CASE_									=						downstream_dict['model.utterancelevel_feature_extractor.linear1.weight']
    SCREAMING_SNAKE_CASE_									=						downstream_dict['model.utterancelevel_feature_extractor.linear1.bias']
    SCREAMING_SNAKE_CASE_									=						downstream_dict['model.utterancelevel_feature_extractor.linear2.weight']
    SCREAMING_SNAKE_CASE_									=						downstream_dict['model.utterancelevel_feature_extractor.linear2.bias']
    SCREAMING_SNAKE_CASE_									=						downstream_dict['objective.W']
    return model


@torch.no_grad()
def 					_UpperCAmelCase       (  _SCREAMING_SNAKE_CASE					:		Any ,   _SCREAMING_SNAKE_CASE					:		int ,   _SCREAMING_SNAKE_CASE					:		Dict ,   _SCREAMING_SNAKE_CASE					:		Union[str, Any]       ):





    """simple docstring"""


    SCREAMING_SNAKE_CASE_									=						torch.load(_SCREAMING_SNAKE_CASE ,   map_location='cpu'       )

    SCREAMING_SNAKE_CASE_									=						checkpoint['Downstream']

    SCREAMING_SNAKE_CASE_									=						WavaVecaConfig.from_pretrained(_SCREAMING_SNAKE_CASE       )
    SCREAMING_SNAKE_CASE_									=						WavaVecaFeatureExtractor.from_pretrained(
        _SCREAMING_SNAKE_CASE ,   return_attention_mask=_SCREAMING_SNAKE_CASE ,   do_normalize=_SCREAMING_SNAKE_CASE       )

    SCREAMING_SNAKE_CASE_									=						hf_config.architectures[0]
    if arch.endswith('ForSequenceClassification'       ):
        SCREAMING_SNAKE_CASE_									=						convert_classification(_SCREAMING_SNAKE_CASE ,   _SCREAMING_SNAKE_CASE ,   _SCREAMING_SNAKE_CASE       )
    elif arch.endswith('ForAudioFrameClassification'       ):
        SCREAMING_SNAKE_CASE_									=						convert_diarization(_SCREAMING_SNAKE_CASE ,   _SCREAMING_SNAKE_CASE ,   _SCREAMING_SNAKE_CASE       )
    elif arch.endswith('ForXVector'       ):
        SCREAMING_SNAKE_CASE_									=						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:
        SCREAMING_SNAKE_CASE_									=						checkpoint['Featurizer']['weights']

    hf_feature_extractor.save_pretrained(_SCREAMING_SNAKE_CASE       )
    hf_model.save_pretrained(_SCREAMING_SNAKE_CASE       )


if __name__ == "__main__":
       UpperCamelCase__  :      Optional[int]			=    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.")
       UpperCamelCase__  :      Optional[Any]			=    parser.parse_args()
       convert_saprl_checkpoint(args.base_model_name, args.config_path, args.checkpoint_path, args.model_dump_path)





import inspect
import os
import unittest
from pathlib import Path

import torch

import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command



class       __snake_case  (    unittest.TestCase       ):
  __lowerCAmelCase     :	Dict						 =  inspect.getfile(accelerate.test_utils       )
  __lowerCAmelCase     :	Optional[Any]						 =  os.path.sep.join(mod_file.split(os.path.sep       )[:-1] + ['scripts', 'test_cli.py']       )

  __lowerCAmelCase     :	Tuple						 =  ['accelerate', 'launch']
  __lowerCAmelCase     :	Union[str, Any]						 =  Path.home() / '.cache/huggingface/accelerate'
  __lowerCAmelCase     :	List[str]						 =  'default_config.yaml'
  __lowerCAmelCase     :	List[Any]						 =  config_folder / config_file
  __lowerCAmelCase     :	str						 =  config_folder / '_default_config.yaml'

  __lowerCAmelCase     :	Optional[int]						 =  Path('tests/test_configs'       )

  @classmethod
  def 						lowerCAmelCase__     (					cls):
      if cls.config_path.is_file():
          cls.config_path.rename(cls.changed_path)

  @classmethod
  def 						lowerCAmelCase__     (					cls):
      if cls.changed_path.is_file():
          cls.changed_path.rename(cls.config_path)

  def 						lowerCAmelCase__     (					self):
      SCREAMING_SNAKE_CASE_									=						self.base_cmd
      if torch.cuda.is_available() and (torch.cuda.device_count() > 1):
          cmd += ["--multi_gpu"]
      execute_subprocess_async(cmd + [self.test_file_path]						,		env=os.environ.copy())

  def 						lowerCAmelCase__     (					self):
      for config in sorted(self.test_config_path.glob('**/*.yaml')):
          with self.subTest(config_file=_A):
              execute_subprocess_async(
                  self.base_cmd + ['--config_file', str(_A), self.test_file_path]						,		env=os.environ.copy())


  def 						lowerCAmelCase__     (					self):
      execute_subprocess_async(['accelerate', 'test']						,		env=os.environ.copy())






class       __snake_case  (    unittest.TestCase       ):
  __lowerCAmelCase     :	Optional[Any]						 =  'test-tpu'
  __lowerCAmelCase     :	str						 =  'us-central1-a'
  __lowerCAmelCase     :	Union[str, Any]						 =  'ls'
  __lowerCAmelCase     :	Union[str, Any]						 =  ['accelerate', 'tpu-config']
  __lowerCAmelCase     :	Union[str, Any]						 =  'cd /usr/share'
  __lowerCAmelCase     :	List[Any]						 =  'tests/test_samples/test_command_file.sh'
  __lowerCAmelCase     :	Dict						 =  'Running gcloud compute tpus tpu-vm ssh'

  def 						lowerCAmelCase__     (					self):
      SCREAMING_SNAKE_CASE_									=						run_command(
          self.cmd
          + ['--command', self.command, '--tpu_zone', self.tpu_zone, '--tpu_name', self.tpu_name, '--debug']						,		return_stdout=_A						,		)
      self.assertIn(
          f"""{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; ls --worker all"""						,		_A						,		)

  def 						lowerCAmelCase__     (					self):
      SCREAMING_SNAKE_CASE_									=						run_command(
          self.cmd
          + [
              '--config_file',
              'tests/test_configs/0_12_0.yaml',
              '--command',
              self.command,
              '--tpu_zone',
              self.tpu_zone,
              '--tpu_name',
              self.tpu_name,
              '--debug',
          ]						,		return_stdout=_A						,		)
      self.assertIn(
          f"""{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; ls --worker all"""						,		_A						,		)

  def 						lowerCAmelCase__     (					self):
      SCREAMING_SNAKE_CASE_									=						run_command(
          self.cmd + ['--config_file', 'tests/test_configs/latest.yaml', '--debug']						,		return_stdout=_A)
      self.assertIn(
          f"""{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; echo \"hello world\"; echo \"this is a second command\" --worker all"""						,		_A						,		)

  def 						lowerCAmelCase__     (					self):
      SCREAMING_SNAKE_CASE_									=						run_command(
          self.cmd + ['--config_file', 'tests/test_configs/latest.yaml', '--command', self.command, '--debug']						,		return_stdout=_A						,		)
      self.assertIn(
          f"""{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; ls --worker all"""						,		_A						,		)

  def 						lowerCAmelCase__     (					self):
      SCREAMING_SNAKE_CASE_									=						run_command(
          self.cmd
          + [
              '--config_file',
              'tests/test_configs/latest.yaml',
              '--command',
              self.command,
              '--command',
              'echo "Hello World"',
              '--debug',
          ]						,		return_stdout=_A						,		)
      self.assertIn(
          f"""{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; ls; echo \"Hello World\" --worker all"""						,		_A						,		)

  def 						lowerCAmelCase__     (					self):
      SCREAMING_SNAKE_CASE_									=						run_command(
          self.cmd
          + ['--config_file', 'tests/test_configs/latest.yaml', '--command_file', self.command_file, '--debug']						,		return_stdout=_A						,		)
      self.assertIn(
          f"""{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; echo \"hello world\"; echo \"this is a second command\" --worker all"""						,		_A						,		)

  def 						lowerCAmelCase__     (					self):
      SCREAMING_SNAKE_CASE_									=						run_command(
          self.cmd
          + [
              '--config_file',
              'tests/test_configs/0_12_0.yaml',
              '--command_file',
              self.command_file,
              '--tpu_zone',
              self.tpu_zone,
              '--tpu_name',
              self.tpu_name,
              '--debug',
          ]						,		return_stdout=_A						,		)
      self.assertIn(
          f"""{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; echo \"hello world\"; echo \"this is a second command\" --worker all"""						,		_A						,		)

  def 						lowerCAmelCase__     (					self):
      SCREAMING_SNAKE_CASE_									=						run_command(
          self.cmd + ['--config_file', 'tests/test_configs/latest.yaml', '--install_accelerate', '--debug']						,		return_stdout=_A						,		)
      self.assertIn(
          f"""{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; pip install accelerate -U; echo \"hello world\"; echo \"this is a second command\" --worker all"""						,		_A						,		)


  def 						lowerCAmelCase__     (					self):
      SCREAMING_SNAKE_CASE_									=						run_command(
          self.cmd
          + [
              '--config_file',
              'tests/test_configs/latest.yaml',
              '--install_accelerate',
              '--accelerate_version',
              '12.0.0',
              '--debug',
          ]						,		return_stdout=_A						,		)
      self.assertIn(
          f"""{self.gcloud} test-tpu --zone us-central1-a --command {self.base_output}; pip install accelerate==12.0.0; echo \"hello world\"; echo \"this is a second command\" --worker all"""						,		_A						,		)


