import argparse

import torch

from transformers import (
    UniSpeechSatConfig,
    UniSpeechSatForAudioFrameClassification,
    UniSpeechSatForSequenceClassification,
    UniSpeechSatForXVector,
    WavaVecaFeatureExtractor,
    logging,
)


logging.set_verbosity_info()
__lowerCamelCase      :			List[str]							       =		logging.get_logger(__name__)



def      __SCREAMING_SNAKE_CASE  ( __UpperCamelCase   :	List[Any]			,					__UpperCamelCase   :	Union[str, Any]			,					__UpperCamelCase   :	str     )							-> Optional[Any]:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__      							=				UniSpeechSatForSequenceClassification.from_pretrained(__UpperCamelCase			,					config=__UpperCamelCase     )
  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      __SCREAMING_SNAKE_CASE  ( __UpperCamelCase   :	List[Any]			,					__UpperCamelCase   :	Tuple			,					__UpperCamelCase   :	List[str]     )							-> List[str]:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__      							=				UniSpeechSatForAudioFrameClassification.from_pretrained(__UpperCamelCase			,					config=__UpperCamelCase     )
  SCREAMING_SNAKE_CASE__      							=				downstream_dict["""model.linear.weight"""]
  SCREAMING_SNAKE_CASE__      							=				downstream_dict["""model.linear.bias"""]
  return model



def      __SCREAMING_SNAKE_CASE  ( __UpperCamelCase   :	Union[str, Any]			,					__UpperCamelCase   :	Dict			,					__UpperCamelCase   :	Optional[int]     )							-> Optional[int]:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__      							=				UniSpeechSatForXVector.from_pretrained(__UpperCamelCase			,					config=__UpperCamelCase     )
  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      __SCREAMING_SNAKE_CASE  ( __UpperCamelCase   :	Optional[Any]			,					__UpperCamelCase   :	List[str]			,					__UpperCamelCase   :	Optional[Any]			,					__UpperCamelCase   :	List[str]     )							-> Union[str, Any]:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__      							=				torch.load(__UpperCamelCase			,					map_location="""cpu"""     )

  SCREAMING_SNAKE_CASE__      							=				checkpoint["""Downstream"""]

  SCREAMING_SNAKE_CASE__      							=				UniSpeechSatConfig.from_pretrained(__UpperCamelCase     )
  SCREAMING_SNAKE_CASE__      							=				WavaVecaFeatureExtractor.from_pretrained(
      __UpperCamelCase			,					return_attention_mask=__UpperCamelCase			,					do_normalize=__UpperCamelCase     )

  SCREAMING_SNAKE_CASE__      							=				hf_config.architectures[0]
  if arch.endswith("""ForSequenceClassification"""     ):
    SCREAMING_SNAKE_CASE__      							=				convert_classification(__UpperCamelCase			,					__UpperCamelCase			,					__UpperCamelCase     )
  elif arch.endswith("""ForAudioFrameClassification"""     ):
    SCREAMING_SNAKE_CASE__      							=				convert_diarization(__UpperCamelCase			,					__UpperCamelCase			,					__UpperCamelCase     )
  elif arch.endswith("""ForXVector"""     ):
    SCREAMING_SNAKE_CASE__      							=				convert_xvector(__UpperCamelCase			,					__UpperCamelCase			,					__UpperCamelCase     )
  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(__UpperCamelCase     )
  hf_model.save_pretrained(__UpperCamelCase     )


if __name__ == "__main__":
   __lowerCamelCase      :			List[str]							       =		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.''')
   __lowerCamelCase      :			int							       =		parser.parse_args()
   convert_saprl_checkpoint(args.base_model_name, args.config_path, args.checkpoint_path, args.model_dump_path)

import unittest

from .lib import (
    Matrix,
    Vector,
    axpy,
    square_zero_matrix,
    unit_basis_vector,
    zero_vector,
)







class __snake_case    (						unittest.TestCase		):




   def      __a						(   self      :    Dict				):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				Vector([1, 2, 3]				)
     self.assertEqual(x.component(0				)	,     1				)
     self.assertEqual(x.component(2				)	,     3				)
     SCREAMING_SNAKE_CASE__      							=				Vector()




   def      __a						(   self      :    int				):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				Vector([0, 0, 0, 0, 0, 1]				)
     self.assertEqual(str(_lowercase				)	,     """(0,0,0,0,0,1)"""				)




   def      __a						(   self      :    Tuple				):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				Vector([1, 2, 3, 4]				)
     self.assertEqual(len(_lowercase				)	,     4				)




   def      __a						(   self      :    Optional[Any]				):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				Vector([1, 2]				)
     SCREAMING_SNAKE_CASE__      							=				Vector([1, 2, 3, 4, 5]				)
     SCREAMING_SNAKE_CASE__      							=				Vector([0, 0, 0, 0, 0, 0, 0, 0, 0, 0]				)
     SCREAMING_SNAKE_CASE__      							=				Vector([1, -1, 1, -1, 2, -3, 4, -5]				)
     self.assertAlmostEqual(x.euclidean_length()	,     2.2_36	,     3				)
     self.assertAlmostEqual(y.euclidean_length()	,     7.4_16	,     3				)
     self.assertEqual(z.euclidean_length()	,     0				)
     self.assertAlmostEqual(w.euclidean_length()	,     7.6_16	,     3				)




   def      __a						(   self      :    Optional[int]				):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				Vector([1, 2, 3]				)
     SCREAMING_SNAKE_CASE__      							=				Vector([1, 1, 1]				)
     self.assertEqual((x + y).component(0				)	,     2				)
     self.assertEqual((x + y).component(1				)	,     3				)
     self.assertEqual((x + y).component(2				)	,     4				)




   def      __a						(   self      :    Any				):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				Vector([1, 2, 3]				)
     SCREAMING_SNAKE_CASE__      							=				Vector([1, 1, 1]				)
     self.assertEqual((x - y).component(0				)	,     0				)
     self.assertEqual((x - y).component(1				)	,     1				)
     self.assertEqual((x - y).component(2				)	,     2				)




   def      __a						(   self      :    str				):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				Vector([1, 2, 3]				)
     SCREAMING_SNAKE_CASE__      							=				Vector([2, -1, 4]				)  # for test of dot product
     SCREAMING_SNAKE_CASE__      							=				Vector([1, -2, -1]				)
     self.assertEqual(str(x * 3.0				)	,     """(3.0,6.0,9.0)"""				)
     self.assertEqual((a * b)	,     0				)




   def      __a						(   self      :    Union[str, Any]				):



     """simple docstring"""






     self.assertEqual(str(zero_vector(10				)				).count("""0"""				)	,     10				)




   def      __a						(   self      :    str				):



     """simple docstring"""






     self.assertEqual(str(unit_basis_vector(3	,     1				)				)	,     """(0,1,0)"""				)




   def      __a						(   self      :    Any				):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				Vector([1, 2, 3]				)
     SCREAMING_SNAKE_CASE__      							=				Vector([1, 0, 1]				)
     self.assertEqual(str(axpy(2	,     _lowercase	,     _lowercase				)				)	,     """(3,4,7)"""				)




   def      __a						(   self      :    str				):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				Vector([1, 0, 0, 0, 0, 0]				)
     SCREAMING_SNAKE_CASE__      							=				x.copy()
     self.assertEqual(str(_lowercase				)	,     str(_lowercase				)				)




   def      __a						(   self      :    str				):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				Vector([1, 0, 0]				)
     x.change_component(0	,     0				)
     x.change_component(1	,     1				)
     self.assertEqual(str(_lowercase				)	,     """(0,1,0)"""				)




   def      __a						(   self      :    Optional[Any]				):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]	,     3	,     3				)
     self.assertEqual("""|1,2,3|\n|2,4,5|\n|6,7,8|\n"""	,     str(_lowercase				)				)




   def      __a						(   self      :    List[Any]				):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]	,     3	,     3				)
     SCREAMING_SNAKE_CASE__      							=				[[-3, -14, -10], [-5, -10, -5], [-2, -1, 0]]
     for x in range(a.height()				):
       for y in range(a.width()				):
         self.assertEqual(minors[x][y]	,     a.minor(_lowercase	,     _lowercase				)				)




   def      __a						(   self      :    Dict				):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]	,     3	,     3				)
     SCREAMING_SNAKE_CASE__      							=				[[-3, 14, -10], [5, -10, 5], [-2, 1, 0]]
     for x in range(a.height()				):
       for y in range(a.width()				):
         self.assertEqual(cofactors[x][y]	,     a.cofactor(_lowercase	,     _lowercase				)				)




   def      __a						(   self      :    Union[str, Any]				):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]	,     3	,     3				)
     self.assertEqual(-5	,     a.determinant()				)




   def      __a						(   self      :    List[Any]				):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				Matrix([[1, 2, 3], [4, 5, 6], [7, 8, 9]]	,     3	,     3				)
     SCREAMING_SNAKE_CASE__      							=				Vector([1, 2, 3]				)
     self.assertEqual("""(14,32,50)"""	,     str(a * x				)				)
     self.assertEqual("""|2,4,6|\n|8,10,12|\n|14,16,18|\n"""	,     str(a * 2				)				)




   def      __a						(   self      :    Optional[Any]				):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]	,     3	,     3				)
     a.change_component(0	,     2	,     5				)
     self.assertEqual("""|1,2,5|\n|2,4,5|\n|6,7,8|\n"""	,     str(_lowercase				)				)




   def      __a						(   self      :    Union[str, Any]				):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]	,     3	,     3				)
     self.assertEqual(7	,     a.component(2	,     1				)	,     0.01				)




   def      __a						(   self      :    List[Any]				):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]	,     3	,     3				)
     SCREAMING_SNAKE_CASE__      							=				Matrix([[1, 2, 7], [2, 4, 5], [6, 7, 10]]	,     3	,     3				)
     self.assertEqual("""|2,4,10|\n|4,8,10|\n|12,14,18|\n"""	,     str(a + b				)				)




   def      __a						(   self      :    Optional[Any]				):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				Matrix([[1, 2, 3], [2, 4, 5], [6, 7, 8]]	,     3	,     3				)
     SCREAMING_SNAKE_CASE__      							=				Matrix([[1, 2, 7], [2, 4, 5], [6, 7, 10]]	,     3	,     3				)
     self.assertEqual("""|0,0,-4|\n|0,0,0|\n|0,0,-2|\n"""	,     str(a - b				)				)




   def      __a						(   self      :    Any				):



     """simple docstring"""






     self.assertEqual(
         """|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n|0,0,0,0,0|\n"""	,     str(square_zero_matrix(5				)				)	,     )


if __name__ == "__main__":
   unittest.main()
