
'''simple docstring'''





import json
import os
import pickle
import subprocess
from hashlib import mda
from pathlib import Path
from tempfile import gettempdir
from textwrap import dedent
from types import CodeType, FunctionType
from unittest import TestCase
from unittest.mock import patch

import pytest
from multiprocess import Pool
from packaging import version

import datasets
from datasets.fingerprint import Hasher, fingerprint_transform
from datasets.table import InMemoryTable

from .utils import (
    require_regex,
    require_spacy,
    require_spacy_model,
    require_tiktoken,
    require_torch,
    require_transformers,
)



class 			lowerCAmelCase__ :



  '''simple docstring'''






  def __init__(self	:			List[str]						,			lowerCAmelCase_	:			Union[str, Any]     ) ->							Any:
        snake_case_    							=				foo


  def __call__(self	:			List[str]     ) ->							Any:
        return self.foo



class 			lowerCAmelCase__ (							datasets.Dataset							):



  '''simple docstring'''






  @fingerprint_transform(inplace=lowerCAmelCase_     )
  def 		_lowerCamelCase						(self	:			Any						,			lowerCAmelCase_	:			Dict						,			*lowerCAmelCase_	:			int						,			**lowerCAmelCase_	:			str     ) ->							Tuple:
        return DatasetChild(self.data						,			fingerprint=lowerCAmelCase_     )


  @fingerprint_transform(inplace=lowerCAmelCase_     )
  def 		_lowerCamelCase						(self	:			str						,			lowerCAmelCase_	:			Tuple						,			*lowerCAmelCase_	:			List[str]						,			**lowerCAmelCase_	:			int     ) ->							List[Any]:
        return DatasetChild(self.data						,			fingerprint=lowerCAmelCase_     )



class 			lowerCAmelCase__ :



  '''simple docstring'''






  def __init__(self	:			str						,			lowerCAmelCase_	:			int     ) ->							Dict:
        snake_case_    							=				callable

  def __call__(self	:			Dict						,			*lowerCAmelCase_	:			List[str]						,			**lowerCAmelCase_	:			Any     ) ->							Any:
        if self.callable is not None:
              return self.callable(*lowerCAmelCase_						,			**lowerCAmelCase_     )


  def __getstate__(self	:			Any     ) ->							List[str]:
        raise pickle.PicklingError()



class 			lowerCAmelCase__ (							UpperCamelCase							):



  '''simple docstring'''






  @require_transformers
  @pytest.mark.integration
  def 		_lowerCamelCase						(self	:			Dict     ) ->							str:
        from transformers import AutoTokenizer

        def encode(lowerCAmelCase_	:			int     ):
              return tokenizer(lowerCAmelCase_     )

        # TODO: add hash consistency tests across sessions
        snake_case_    							=				AutoTokenizer.from_pretrained("bert-base-uncased"     )
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(lowerCAmelCase_     )     ).hexdigest()
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(lambda lowerCAmelCase_     : tokenizer(lowerCAmelCase_     )     )     ).hexdigest()
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(lowerCAmelCase_     )     ).hexdigest()
        snake_case_    							=				AutoTokenizer.from_pretrained("bert-base-cased"     )
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(lowerCAmelCase_     )     ).hexdigest()
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(lambda lowerCAmelCase_     : tokenizer(lowerCAmelCase_     )     )     ).hexdigest()
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(lowerCAmelCase_     )     ).hexdigest()
        snake_case_    							=				AutoTokenizer.from_pretrained("bert-base-uncased"     )
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(lowerCAmelCase_     )     ).hexdigest()
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(lambda lowerCAmelCase_     : tokenizer(lowerCAmelCase_     )     )     ).hexdigest()
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(lowerCAmelCase_     )     ).hexdigest()
        self.assertEqual(lowerCAmelCase_						,			lowerCAmelCase_     )
        self.assertNotEqual(lowerCAmelCase_						,			lowerCAmelCase_     )
        self.assertEqual(lowerCAmelCase_						,			lowerCAmelCase_     )
        self.assertNotEqual(lowerCAmelCase_						,			lowerCAmelCase_     )
        self.assertEqual(lowerCAmelCase_						,			lowerCAmelCase_     )
        self.assertNotEqual(lowerCAmelCase_						,			lowerCAmelCase_     )

  @require_transformers
  @pytest.mark.integration
  def 		_lowerCamelCase						(self	:			List[str]     ) ->							List[str]:
        from transformers import AutoTokenizer

        snake_case_    							=				AutoTokenizer.from_pretrained("gpt2"     )
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(lowerCAmelCase_     )     ).hexdigest()
        tokenizer("Hello world !"     )  # call once to change the tokenizer's cache
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(lowerCAmelCase_     )     ).hexdigest()
        self.assertEqual(lowerCAmelCase_						,			lowerCAmelCase_     )


  @require_regex
  def 		_lowerCamelCase						(self	:			List[str]     ) ->							List[Any]:
        import regex

        snake_case_    							=				regex.Regex("foo"     )
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(lowerCAmelCase_     )     ).hexdigest()
        snake_case_    							=				regex.Regex("bar"     )
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(lowerCAmelCase_     )     ).hexdigest()
        snake_case_    							=				regex.Regex("foo"     )
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(lowerCAmelCase_     )     ).hexdigest()
        self.assertEqual(lowerCAmelCase_						,			lowerCAmelCase_     )
        self.assertNotEqual(lowerCAmelCase_						,			lowerCAmelCase_     )



class 			lowerCAmelCase__ (							UpperCamelCase							):



  '''simple docstring'''






  def 		_lowerCamelCase						(self	:			Optional[Any]     ) ->							str:
        def func():
              return foo

        snake_case_    							=				[0]
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(lowerCAmelCase_     )     ).hexdigest()
        snake_case_    							=				[1]
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(lowerCAmelCase_     )     ).hexdigest()
        snake_case_    							=				[0]
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(lowerCAmelCase_     )     ).hexdigest()
        self.assertEqual(lowerCAmelCase_						,			lowerCAmelCase_     )
        self.assertNotEqual(lowerCAmelCase_						,			lowerCAmelCase_     )

  def 		_lowerCamelCase						(self	:			Tuple     ) ->							Optional[Any]:
        def func():
              pass

        snake_case_    							=				mda(datasets.utils.py_utils.dumps(lowerCAmelCase_     )     ).hexdigest()

        def func():
              pass

        snake_case_    							=				mda(datasets.utils.py_utils.dumps(lowerCAmelCase_     )     ).hexdigest()
        self.assertEqual(lowerCAmelCase_						,			lowerCAmelCase_     )

  def 		_lowerCamelCase						(self	:			List[str]     ) ->							Optional[Any]:
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(Foo([0]     )     )     ).hexdigest()
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(Foo([1]     )     )     ).hexdigest()
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(Foo([0]     )     )     ).hexdigest()
        self.assertEqual(lowerCAmelCase_						,			lowerCAmelCase_     )
        self.assertNotEqual(lowerCAmelCase_						,			lowerCAmelCase_     )

  def 		_lowerCamelCase						(self	:			int     ) ->							List[Any]:
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(Foo([0]     ).__call__     )     ).hexdigest()
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(Foo([1]     ).__call__     )     ).hexdigest()
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(Foo([0]     ).__call__     )     ).hexdigest()
        self.assertEqual(lowerCAmelCase_						,			lowerCAmelCase_     )
        self.assertNotEqual(lowerCAmelCase_						,			lowerCAmelCase_     )

  def 		_lowerCamelCase						(self	:			List[str]     ) ->							List[str]:
        snake_case_    							=				(
            "co_argcount",
            "co_kwonlyargcount",
            "co_nlocals",
            "co_stacksize",
            "co_flags",
            "co_code",
            "co_consts",
            "co_names",
            "co_varnames",
            "co_filename",
            "co_name",
            "co_firstlineno",
            "co_lnotab",
            "co_freevars",
            "co_cellvars",
        )

        def _create_code_pyaa(*lowerCAmelCase_	:			Union[str, Any]     ):
              if hasattr(args[-3]						,			"encode"     ):
                    snake_case_    							=				list(lowerCAmelCase_     )
                    snake_case_    							=				args[-3].encode()  # co_lnotab
                    snake_case_    							=				args[-10].encode()  # co_code
              if hasattr(lowerCAmelCase_						,			"co_posonlyargcount"     ):
                    if len(lowerCAmelCase_     ) == 16:
                          return CodeType(*lowerCAmelCase_     )
                    elif len(lowerCAmelCase_     ) == 15:
                          return CodeType(args[0]						,			0						,			*args[1:]     )
                    return CodeType(args[0]						,			0						,			0						,			*args[1:]     )
              elif hasattr(lowerCAmelCase_						,			"co_kwonlyargcount"     ):
                    if len(lowerCAmelCase_     ) == 16:
                          return CodeType(args[0]						,			*args[2:]     )
                    elif len(lowerCAmelCase_     ) == 15:
                          return CodeType(*lowerCAmelCase_     )
                    return CodeType(args[0]						,			0						,			*args[1:]     )
              if len(lowerCAmelCase_     ) == 16:
                    return CodeType(args[0]						,			*args[3:]     )
              elif len(lowerCAmelCase_     ) == 15:
                    return CodeType(args[0]						,			*args[2:]     )
              return CodeType(*lowerCAmelCase_     )

        def create_ipython_func(lowerCAmelCase_	:			int						,			lowerCAmelCase_	:			List[str]     ):
              def func():
                    return returned_obj

              snake_case_    							=				func.__code__
              # Use _create_code from dill in order to make it work for different python versions
              if datasets.config.PY_VERSION < version.parse("3.8"     ):
                    snake_case_    							=				_create_code_pyaa(
                        *[getattr(lowerCAmelCase_						,			lowerCAmelCase_     ) if k != "co_filename" else co_filename for k in code_args_pyaa]     )
              else:
                    snake_case_    							=				code.replace(co_filename=lowerCAmelCase_     )
              return FunctionType(lowerCAmelCase_						,			func.__globals__						,			func.__name__						,			func.__defaults__						,			func.__closure__     )

        snake_case_							,						snake_case_    							=				"<ipython-input-2-e0383a102aae>", [0]
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(create_ipython_func(lowerCAmelCase_						,			lowerCAmelCase_     )     )     ).hexdigest()
        snake_case_							,						snake_case_    							=				"<ipython-input-2-e0383a102aae>", [1]
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(create_ipython_func(lowerCAmelCase_						,			lowerCAmelCase_     )     )     ).hexdigest()
        snake_case_							,						snake_case_    							=				"<ipython-input-5-713f6613acf3>", [0]
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(create_ipython_func(lowerCAmelCase_						,			lowerCAmelCase_     )     )     ).hexdigest()
        self.assertEqual(lowerCAmelCase_						,			lowerCAmelCase_     )
        self.assertNotEqual(lowerCAmelCase_						,			lowerCAmelCase_     )

        snake_case_							,						snake_case_    							=				os.path.join(gettempdir()						,			"ipykernel_12345"						,			"321456789.py"     ), [0]
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(create_ipython_func(lowerCAmelCase_						,			lowerCAmelCase_     )     )     ).hexdigest()
        snake_case_							,						snake_case_    							=				os.path.join(gettempdir()						,			"ipykernel_12345"						,			"321456789.py"     ), [1]
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(create_ipython_func(lowerCAmelCase_						,			lowerCAmelCase_     )     )     ).hexdigest()
        snake_case_							,						snake_case_    							=				os.path.join(gettempdir()						,			"ipykernel_12345"						,			"654123987.py"     ), [0]
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(create_ipython_func(lowerCAmelCase_						,			lowerCAmelCase_     )     )     ).hexdigest()
        self.assertEqual(lowerCAmelCase_						,			lowerCAmelCase_     )
        self.assertNotEqual(lowerCAmelCase_						,			lowerCAmelCase_     )


  def 		_lowerCamelCase						(self	:			Dict     ) ->							int:
        snake_case_							,						snake_case_    							=				[0], [1]

        def func():
              return foo, bar

        snake_case_    							=				"__main__"

        def globalvars_mocka_side_effect(lowerCAmelCase_	:			Optional[Any]						,			*lowerCAmelCase_	:			Optional[int]						,			**lowerCAmelCase_	:			Optional[Any]     ):
              return {"foo": foo, "bar": bar}

        def globalvars_mocka_side_effect(lowerCAmelCase_	:			Any						,			*lowerCAmelCase_	:			Optional[Any]						,			**lowerCAmelCase_	:			List[Any]     ):
              return {"bar": bar, "foo": foo}

        with patch("dill.detect.globalvars"						,			side_effect=lowerCAmelCase_     ) as globalvars_mocka:
              snake_case_    							=				mda(datasets.utils.py_utils.dumps(lowerCAmelCase_     )     ).hexdigest()
              self.assertGreater(globalvars_mocka.call_count						,			0     )
        with patch("dill.detect.globalvars"						,			side_effect=lowerCAmelCase_     ) as globalvars_mocka:
              snake_case_    							=				mda(datasets.utils.py_utils.dumps(lowerCAmelCase_     )     ).hexdigest()
              self.assertGreater(globalvars_mocka.call_count						,			0     )
        self.assertEqual(lowerCAmelCase_						,			lowerCAmelCase_     )



class 			lowerCAmelCase__ (							UpperCamelCase							):



  '''simple docstring'''






  def 		_lowerCamelCase						(self	:			Union[str, Any]     ) ->							int:
        snake_case_    							=				Hasher.hash("hello"     )
        snake_case_    							=				Hasher.hash("hello"     )
        snake_case_    							=				Hasher.hash("there"     )
        self.assertEqual(lowerCAmelCase_						,			lowerCAmelCase_     )
        self.assertNotEqual(lowerCAmelCase_						,			lowerCAmelCase_     )

  def 		_lowerCamelCase						(self	:			Union[str, Any]     ) ->							int:
        snake_case_    							=				Hasher.hash(Foo("hello"     )     )
        snake_case_    							=				Hasher.hash(Foo("hello"     )     )
        snake_case_    							=				Hasher.hash(Foo("there"     )     )
        self.assertEqual(lowerCAmelCase_						,			lowerCAmelCase_     )
        self.assertNotEqual(lowerCAmelCase_						,			lowerCAmelCase_     )

  def 		_lowerCamelCase						(self	:			List[Any]     ) ->							List[str]:
        snake_case_    							=				Hasher()
        for x in ["hello", Foo("hello"     )]:
              hasher.update(lowerCAmelCase_     )
        snake_case_    							=				hasher.hexdigest()
        snake_case_    							=				Hasher()
        for x in ["hello", Foo("hello"     )]:
              hasher.update(lowerCAmelCase_     )
        snake_case_    							=				hasher.hexdigest()
        snake_case_    							=				Hasher()
        for x in ["there", Foo("there"     )]:
              hasher.update(lowerCAmelCase_     )
        snake_case_    							=				hasher.hexdigest()
        self.assertEqual(lowerCAmelCase_						,			lowerCAmelCase_     )
        self.assertNotEqual(lowerCAmelCase_						,			lowerCAmelCase_     )

  def 		_lowerCamelCase						(self	:			str     ) ->							List[str]:
        with self.assertRaises(pickle.PicklingError     ):
              Hasher.hash(UnpicklableCallable(Foo("hello"     )     )     )

  def 		_lowerCamelCase						(self	:			List[str]     ) ->							Any:
        snake_case_    							=				"abc"
        snake_case_    							=				[string, string]  # two strings have the same ids
        snake_case_    							=				[string, string]
        snake_case_    							=				json.loads(f'''["{string}", "{string}"]'''     )  # two strings have different ids
        self.assertIs(obja[0]						,			lowerCAmelCase_     )
        self.assertIs(obja[0]						,			obja[1]     )
        self.assertIs(obja[0]						,			lowerCAmelCase_     )
        self.assertIs(obja[0]						,			obja[1]     )
        self.assertIsNot(obja[0]						,			lowerCAmelCase_     )
        self.assertIsNot(obja[0]						,			obja[1]     )
        snake_case_    							=				Hasher.hash(lowerCAmelCase_     )
        snake_case_    							=				Hasher.hash(lowerCAmelCase_     )
        snake_case_    							=				Hasher.hash(lowerCAmelCase_     )
        self.assertEqual(lowerCAmelCase_						,			lowerCAmelCase_     )
        self.assertEqual(lowerCAmelCase_						,			lowerCAmelCase_     )

  @require_tiktoken
  def 		_lowerCamelCase						(self	:			Optional[Any]     ) ->							Union[str, Any]:
        import tiktoken

        snake_case_    							=				tiktoken.get_encoding("gpt2"     )
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(lowerCAmelCase_     )     ).hexdigest()
        snake_case_    							=				tiktoken.get_encoding("r50k_base"     )
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(lowerCAmelCase_     )     ).hexdigest()
        snake_case_    							=				tiktoken.get_encoding("gpt2"     )
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(lowerCAmelCase_     )     ).hexdigest()
        self.assertEqual(lowerCAmelCase_						,			lowerCAmelCase_     )
        self.assertNotEqual(lowerCAmelCase_						,			lowerCAmelCase_     )

  @require_torch
  def 		_lowerCamelCase						(self	:			int     ) ->							Optional[int]:
        import torch

        snake_case_    							=				torch.tensor([1.0]     )
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(lowerCAmelCase_     )     ).hexdigest()
        snake_case_    							=				torch.tensor([2.0]     )
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(lowerCAmelCase_     )     ).hexdigest()
        snake_case_    							=				torch.tensor([1.0]     )
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(lowerCAmelCase_     )     ).hexdigest()
        self.assertEqual(lowerCAmelCase_						,			lowerCAmelCase_     )
        self.assertNotEqual(lowerCAmelCase_						,			lowerCAmelCase_     )


  @require_spacy
  @require_spacy_model("en_core_web_sm"     )
  @require_spacy_model("fr_core_news_sm"     )
  @pytest.mark.integration
  def 		_lowerCamelCase						(self	:			int     ) ->							List[str]:
        import spacy

        snake_case_    							=				spacy.load("en_core_web_sm"     )
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(lowerCAmelCase_     )     ).hexdigest()
        snake_case_    							=				spacy.load("fr_core_news_sm"     )
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(lowerCAmelCase_     )     ).hexdigest()
        snake_case_    							=				spacy.load("en_core_web_sm"     )
        snake_case_    							=				mda(datasets.utils.py_utils.dumps(lowerCAmelCase_     )     ).hexdigest()
        self.assertEqual(lowerCAmelCase_						,			lowerCAmelCase_     )
        self.assertNotEqual(lowerCAmelCase_						,			lowerCAmelCase_     )

@pytest.mark.integration
def 	snake_case_							(				_a  :				Path      ):
      snake_case_    							=				tmp_path / "dir1"
      snake_case_    							=				tmp_path / "dir2"
      dira.mkdir()
      dira.mkdir()
      snake_case_    							=				"script.py"
      snake_case_    							=				dedent(
          "\n    from datasets.fingerprint import Hasher\n    def foo():\n        pass\n    print(Hasher.hash(foo))\n    "      )
      snake_case_    							=				dira / script_filename
      snake_case_    							=				dira / script_filename
      with script_patha.open("w"      ) as f:
            f.write(_a      )
      with script_patha.open("w"      ) as f:
            f.write(_a      )
      snake_case_    							=				subprocess.check_output(["python", str(_a      )]      )
      snake_case_    							=				subprocess.check_output(["python", str(_a      )]      )
      assert fingerprinta == fingerprinta
def 	snake_case_							(				):
      snake_case_    							=				{"a": [0, 1, 2]}
      snake_case_    							=				DatasetChild(InMemoryTable.from_pydict(_a      )      )
      snake_case_    							=				dataset.funca()._fingerprint
      assert expected_fingerprint == dataset.funca()._fingerprint
      assert expected_fingerprint != dataset.funca()._fingerprint

      with Pool(2      ) as p:
            assert expected_fingerprint == p.apply_async(dataset.funca      ).get()._fingerprint
            assert expected_fingerprint != p.apply_async(dataset.funca      ).get()._fingerprint
def 	snake_case_							(				):
      snake_case_    							=				{"a": [0, 1, 2]}



      class 			lowerCAmelCase__ (							datasets.Dataset							):



        '''simple docstring'''






        @fingerprint_transform(inplace=lowerCAmelCase_     )
        def 		_lowerCamelCase						(self	:			str						,			lowerCAmelCase_	:			Any     ) ->							int:
              return DummyDatasetChild(self.data						,			fingerprint=lowerCAmelCase_     )

      snake_case_    							=				DummyDatasetChild(InMemoryTable.from_pydict(_a      )      ).func()



      class 			lowerCAmelCase__ (							datasets.Dataset							):



        '''simple docstring'''






        @fingerprint_transform(inplace=lowerCAmelCase_						,			version="1.0.0"     )
        def 		_lowerCamelCase						(self	:			Any						,			lowerCAmelCase_	:			Any     ) ->							str:
              return DummyDatasetChild(self.data						,			fingerprint=lowerCAmelCase_     )

      snake_case_    							=				DummyDatasetChild(InMemoryTable.from_pydict(_a      )      ).func()



      class 			lowerCAmelCase__ (							datasets.Dataset							):



        '''simple docstring'''






        @fingerprint_transform(inplace=lowerCAmelCase_						,			version="2.0.0"     )
        def 		_lowerCamelCase						(self	:			int						,			lowerCAmelCase_	:			Union[str, Any]     ) ->							Union[str, Any]:
              return DummyDatasetChild(self.data						,			fingerprint=lowerCAmelCase_     )

      snake_case_    							=				DummyDatasetChild(InMemoryTable.from_pydict(_a      )      ).func()

      assert len({fingeprint_no_version, fingeprint_a, fingeprint_a}      ) == 3




def 	snake_case_							(				):
      # AttributeError: module 'dill._dill' has no attribute 'stack'
      snake_case_    							=				Hasher()
      hasher.update(lambda _a      : x      )



'''simple docstring'''





import argparse

import torch

from transformers import (
    WavaVecaFeatureExtractor,
    WavLMConfig,
    WavLMForAudioFrameClassification,
    WavLMForSequenceClassification,
    WavLMForXVector,
    logging,
)


logging.set_verbosity_info()
A							     = logging.get_logger(__name__)
def 	snake_case_							(				_a  :				Optional[Any]			,       _a  :				Tuple			,       _a  :				int      ):
      snake_case_    							=				WavLMForSequenceClassification.from_pretrained(_a			,       config=_a      )
      snake_case_    							=				downstream_dict["projector.weight"]
      snake_case_    							=				downstream_dict["projector.bias"]
      snake_case_    							=				downstream_dict["model.post_net.linear.weight"]
      snake_case_    							=				downstream_dict["model.post_net.linear.bias"]
      return model
def 	snake_case_							(				_a  :				List[str]			,       _a  :				Optional[Any]			,       _a  :				List[str]      ):
      snake_case_    							=				WavLMForAudioFrameClassification.from_pretrained(_a			,       config=_a      )
      snake_case_    							=				downstream_dict["model.linear.weight"]
      snake_case_    							=				downstream_dict["model.linear.bias"]
      return model
def 	snake_case_							(				_a  :				Dict			,       _a  :				Tuple			,       _a  :				Any      ):
      snake_case_    							=				WavLMForXVector.from_pretrained(_a			,       config=_a      )
      snake_case_    							=				downstream_dict["connector.weight"]
      snake_case_    							=				downstream_dict["connector.bias"]
      for i, kernel_size in enumerate(hf_config.tdnn_kernel      ):
            snake_case_    							=				downstream_dict[
                F'''model.framelevel_feature_extractor.module.{i}.kernel.weight'''
            ]
            snake_case_    							=				downstream_dict[F'''model.framelevel_feature_extractor.module.{i}.kernel.bias''']

      snake_case_    							=				downstream_dict["model.utterancelevel_feature_extractor.linear1.weight"]
      snake_case_    							=				downstream_dict["model.utterancelevel_feature_extractor.linear1.bias"]
      snake_case_    							=				downstream_dict["model.utterancelevel_feature_extractor.linear2.weight"]
      snake_case_    							=				downstream_dict["model.utterancelevel_feature_extractor.linear2.bias"]
      snake_case_    							=				downstream_dict["objective.W"]
      return model
@torch.no_grad()
def 	snake_case_							(				_a  :				Union[str, Any]			,       _a  :				int			,       _a  :				str			,       _a  :				List[Any]      ):
      snake_case_    							=				torch.load(_a			,       map_location="cpu"      )

      snake_case_    							=				checkpoint["Downstream"]

      snake_case_    							=				WavLMConfig.from_pretrained(_a      )
      snake_case_    							=				WavaVecaFeatureExtractor.from_pretrained(
          _a			,       return_attention_mask=_a			,       do_normalize=_a      )

      snake_case_    							=				hf_config.architectures[0]
      if arch.endswith("ForSequenceClassification"      ):
            snake_case_    							=				convert_classification(_a			,       _a			,       _a      )
      elif arch.endswith("ForAudioFrameClassification"      ):
            snake_case_    							=				convert_diarization(_a			,       _a			,       _a      )
      elif arch.endswith("ForXVector"      ):
            snake_case_    							=				convert_xvector(_a			,       _a			,       _a      )
      else:
            raise NotImplementedError(F'''S3PRL weights conversion is not supported for {arch}'''      )

      if hf_config.use_weighted_layer_sum:
            snake_case_    							=				checkpoint["Featurizer"]["weights"]

      hf_feature_extractor.save_pretrained(_a      )
      hf_model.save_pretrained(_a      )


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)

