




import argparse

import torch

from transformers import NystromformerConfig, NystromformerForMaskedLM

def 			lowerCAmelCase_			(  lowerCamelCase:       List[Any]						)					->			Union[str, Any]:


      '''simple docstring'''




      if "model" in orig_key:
            lowerCamelCase__        =				orig_key.replace('model.'     ,				''						)
      if "norm1" in orig_key:
            lowerCamelCase__        =				orig_key.replace('norm1'     ,				'attention.output.LayerNorm'						)
      if "norm2" in orig_key:
            lowerCamelCase__        =				orig_key.replace('norm2'     ,				'output.LayerNorm'						)
      if "norm" in orig_key:
            lowerCamelCase__        =				orig_key.replace('norm'     ,				'LayerNorm'						)
      if "transformer" in orig_key:
            lowerCamelCase__        =				orig_key.split('.'						)[0].split('_'						)[-1]
            lowerCamelCase__        =				orig_key.replace(f"""transformer_{layer_num}"""     ,				f"""encoder.layer.{layer_num}"""						)
      if "mha.attn" in orig_key:
            lowerCamelCase__        =				orig_key.replace('mha.attn'     ,				'attention.self'						)
      if "mha" in orig_key:
            lowerCamelCase__        =				orig_key.replace('mha'     ,				'attention'						)
      if "W_q" in orig_key:
            lowerCamelCase__        =				orig_key.replace('W_q'     ,				'self.query'						)
      if "W_k" in orig_key:
            lowerCamelCase__        =				orig_key.replace('W_k'     ,				'self.key'						)
      if "W_v" in orig_key:
            lowerCamelCase__        =				orig_key.replace('W_v'     ,				'self.value'						)
      if "ff1" in orig_key:
            lowerCamelCase__        =				orig_key.replace('ff1'     ,				'intermediate.dense'						)
      if "ff2" in orig_key:
            lowerCamelCase__        =				orig_key.replace('ff2'     ,				'output.dense'						)
      if "ff" in orig_key:
            lowerCamelCase__        =				orig_key.replace('ff'     ,				'output.dense'						)
      if "mlm_class" in orig_key:
            lowerCamelCase__        =				orig_key.replace('mlm.mlm_class'     ,				'cls.predictions.decoder'						)
      if "mlm" in orig_key:
            lowerCamelCase__        =				orig_key.replace('mlm'     ,				'cls.predictions.transform'						)
      if "cls" not in orig_key:
            lowerCamelCase__        =				"nystromformer." + orig_key

      return orig_key

def 			lowerCAmelCase_			(  lowerCamelCase:       List[str]     ,				lowerCamelCase:       Any						)					->			Tuple:


      '''simple docstring'''




      for key in orig_state_dict.copy().keys():
            lowerCamelCase__        =				orig_state_dict.pop(lowerCamelCase						)

            if ("pooler" in key) or ("sen_class" in key) or ("conv.bias" in key):
                  continue
            else:
                  lowerCamelCase__        =				val

      lowerCamelCase__        =				orig_state_dict["cls.predictions.decoder.bias"]
      lowerCamelCase__        =				(
          torch.arange(config.max_position_embeddings						).expand((1, -1)						) + 2
      )

      return orig_state_dict

def 			lowerCAmelCase_			(  lowerCamelCase:       str     ,				lowerCamelCase:       Tuple     ,				lowerCamelCase:       int						)					->			Optional[int]:


      '''simple docstring'''




      lowerCamelCase__        =				torch.load(lowerCamelCase     ,				map_location='cpu'						)["model_state_dict"]
      lowerCamelCase__        =				NystromformerConfig.from_json_file(lowerCamelCase						)
      lowerCamelCase__        =				NystromformerForMaskedLM(lowerCamelCase						)

      lowerCamelCase__        =				convert_checkpoint_helper(lowerCamelCase     ,				lowerCamelCase						)

      model.load_state_dict(lowerCamelCase						)
      model.eval()
      model.save_pretrained(lowerCamelCase						)

      print(f"""Checkpoint successfuly converted. Model saved at {pytorch_dump_path}"""						)


if __name__ == "__main__":
      __SCREAMING_SNAKE_CASE       =argparse.ArgumentParser()
      # Required parameters
      parser.add_argument(
          """--pytorch_model_path""", default=None, type=str, required=True, help="""Path to Nystromformer pytorch checkpoint."""
      )
      parser.add_argument(
          """--config_file""",
          default=None,
          type=str,
          required=True,
          help="""The json file for Nystromformer model config.""",
      )
      parser.add_argument(
          """--pytorch_dump_path""", default=None, type=str, required=True, help="""Path to the output PyTorch model."""
      )
      __SCREAMING_SNAKE_CASE       =parser.parse_args()
      convert_nystromformer_checkpoint(args.pytorch_model_path, args.config_file, args.pytorch_dump_path)





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 			A			:
     """simple docstring"""

     def __init__(    self  :   Optional[int]	,  A__  :   Optional[Any]			)				->       Dict:
           lowerCamelCase__        =				foo




     def __call__(    self  :   Dict			)				->       Optional[int]:
           return self.foo






class 			A			(		datasets.Dataset		):
     """simple docstring"""

     @fingerprint_transform(inplace=A__			)
     def  __snake_case   (    self  :   Optional[Any]	,  A__  :   Tuple	,  *A__  :   List[str]	,  **A__  :   List[Any]			)				->       Dict:
           return DatasetChild(self.data	,  fingerprint=A__			)




     @fingerprint_transform(inplace=A__			)
     def  __snake_case   (    self  :   Any	,  A__  :   Optional[int]	,  *A__  :   List[str]	,  **A__  :   Union[str, Any]			)				->       List[Any]:
           return DatasetChild(self.data	,  fingerprint=A__			)






class 			A			:
     """simple docstring"""

     def __init__(    self  :   List[Any]	,  A__  :   Tuple			)				->       List[Any]:
           lowerCamelCase__        =				callable




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




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






class 			A			(		_lowerCAmelCase		):
     """simple docstring"""

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

           def encode(A__  :   List[Any]			):
                 return tokenizer(A__			)

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




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

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




     @require_regex
     def  __snake_case   (    self  :   Dict			)				->       Dict:
           import regex

           lowerCamelCase__        =				regex.Regex('foo'			)
           lowerCamelCase__        =				mda(datasets.utils.py_utils.dumps(A__			)			).hexdigest()
           lowerCamelCase__        =				regex.Regex('bar'			)
           lowerCamelCase__        =				mda(datasets.utils.py_utils.dumps(A__			)			).hexdigest()
           lowerCamelCase__        =				regex.Regex('foo'			)
           lowerCamelCase__        =				mda(datasets.utils.py_utils.dumps(A__			)			).hexdigest()
           self.assertEqual(A__	,  A__			)
           self.assertNotEqual(A__	,  A__			)






class 			A			(		_lowerCAmelCase		):
     """simple docstring"""

     def  __snake_case   (    self  :   Tuple			)				->       List[Any]:
           def func():
                 return foo

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




     def  __snake_case   (    self  :   Optional[int]			)				->       str:
           def func():
                 pass

           lowerCamelCase__        =				mda(datasets.utils.py_utils.dumps(A__			)			).hexdigest()

           def func():
                 pass

           lowerCamelCase__        =				mda(datasets.utils.py_utils.dumps(A__			)			).hexdigest()
           self.assertEqual(A__	,  A__			)




     def  __snake_case   (    self  :   List[Any]			)				->       Optional[Any]:
           lowerCamelCase__        =				mda(datasets.utils.py_utils.dumps(Foo([0]			)			)			).hexdigest()
           lowerCamelCase__        =				mda(datasets.utils.py_utils.dumps(Foo([1]			)			)			).hexdigest()
           lowerCamelCase__        =				mda(datasets.utils.py_utils.dumps(Foo([0]			)			)			).hexdigest()
           self.assertEqual(A__	,  A__			)
           self.assertNotEqual(A__	,  A__			)




     def  __snake_case   (    self  :   Union[str, Any]			)				->       str:
           lowerCamelCase__        =				mda(datasets.utils.py_utils.dumps(Foo([0]			).__call__			)			).hexdigest()
           lowerCamelCase__        =				mda(datasets.utils.py_utils.dumps(Foo([1]			).__call__			)			).hexdigest()
           lowerCamelCase__        =				mda(datasets.utils.py_utils.dumps(Foo([0]			).__call__			)			).hexdigest()
           self.assertEqual(A__	,  A__			)
           self.assertNotEqual(A__	,  A__			)




     def  __snake_case   (    self  :   Optional[Any]			)				->       Optional[Any]:
           lowerCamelCase__        =				(
               '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(*A__  :   Any			):
                 if hasattr(args[-3]	,  'encode'			):
                       lowerCamelCase__        =				list(A__			)
                       lowerCamelCase__        =				args[-3].encode()  # co_lnotab
                       lowerCamelCase__        =				args[-1_0].encode()  # co_code
                 if hasattr(A__	,  'co_posonlyargcount'			):
                       if len(A__			) == 1_6:
                             return CodeType(*A__			)
                       elif len(A__			) == 1_5:
                             return CodeType(args[0]	,  0	,  *args[1:]			)
                       return CodeType(args[0]	,  0	,  0	,  *args[1:]			)
                 elif hasattr(A__	,  'co_kwonlyargcount'			):
                       if len(A__			) == 1_6:
                             return CodeType(args[0]	,  *args[2:]			)
                       elif len(A__			) == 1_5:
                             return CodeType(*A__			)
                       return CodeType(args[0]	,  0	,  *args[1:]			)
                 if len(A__			) == 1_6:
                       return CodeType(args[0]	,  *args[3:]			)
                 elif len(A__			) == 1_5:
                       return CodeType(args[0]	,  *args[2:]			)
                 return CodeType(*A__			)

           def create_ipython_func(A__  :   Any	,  A__  :   Tuple			):
                 def func():
                       return returned_obj

                 lowerCamelCase__        =				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'			):
                       lowerCamelCase__        =				_create_code_pyaa(
                           *[getattr(A__	,  A__			) if k != 'co_filename' else co_filename for k in code_args_pyaa]			)
                 else:
                       lowerCamelCase__        =				code.replace(co_filename=A__			)
                 return FunctionType(A__	,  func.__globals__	,  func.__name__	,  func.__defaults__	,  func.__closure__			)

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

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




     def  __snake_case   (    self  :   Optional[Any]			)				->       List[Any]:
           lowerCamelCase__  ,		lowerCamelCase__        =				[0], [1]

           def func():
                 return foo, bar

           lowerCamelCase__        =				'__main__'

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

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

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






class 			A			(		_lowerCAmelCase		):
     """simple docstring"""

     def  __snake_case   (    self  :   str			)				->       List[str]:
           lowerCamelCase__        =				Hasher.hash('hello'			)
           lowerCamelCase__        =				Hasher.hash('hello'			)
           lowerCamelCase__        =				Hasher.hash('there'			)
           self.assertEqual(A__	,  A__			)
           self.assertNotEqual(A__	,  A__			)




     def  __snake_case   (    self  :   List[str]			)				->       Optional[Any]:
           lowerCamelCase__        =				Hasher.hash(Foo('hello'			)			)
           lowerCamelCase__        =				Hasher.hash(Foo('hello'			)			)
           lowerCamelCase__        =				Hasher.hash(Foo('there'			)			)
           self.assertEqual(A__	,  A__			)
           self.assertNotEqual(A__	,  A__			)




     def  __snake_case   (    self  :   Tuple			)				->       str:
           lowerCamelCase__        =				Hasher()
           for x in ["hello", Foo('hello'			)]:
                 hasher.update(A__			)
           lowerCamelCase__        =				hasher.hexdigest()
           lowerCamelCase__        =				Hasher()
           for x in ["hello", Foo('hello'			)]:
                 hasher.update(A__			)
           lowerCamelCase__        =				hasher.hexdigest()
           lowerCamelCase__        =				Hasher()
           for x in ["there", Foo('there'			)]:
                 hasher.update(A__			)
           lowerCamelCase__        =				hasher.hexdigest()
           self.assertEqual(A__	,  A__			)
           self.assertNotEqual(A__	,  A__			)




     def  __snake_case   (    self  :   Any			)				->       Tuple:
           with self.assertRaises(pickle.PicklingError			):
                 Hasher.hash(UnpicklableCallable(Foo('hello'			)			)			)




     def  __snake_case   (    self  :   Optional[int]			)				->       Optional[Any]:
           lowerCamelCase__        =				'abc'
           lowerCamelCase__        =				[string, string]  # two strings have the same ids
           lowerCamelCase__        =				[string, string]
           lowerCamelCase__        =				json.loads(F"""[\"{string}\", \"{string}\"]"""			)  # two strings have different ids
           self.assertIs(obja[0]	,  A__			)
           self.assertIs(obja[0]	,  obja[1]			)
           self.assertIs(obja[0]	,  A__			)
           self.assertIs(obja[0]	,  obja[1]			)
           self.assertIsNot(obja[0]	,  A__			)
           self.assertIsNot(obja[0]	,  obja[1]			)
           lowerCamelCase__        =				Hasher.hash(A__			)
           lowerCamelCase__        =				Hasher.hash(A__			)
           lowerCamelCase__        =				Hasher.hash(A__			)
           self.assertEqual(A__	,  A__			)
           self.assertEqual(A__	,  A__			)




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

           lowerCamelCase__        =				tiktoken.get_encoding('gpt2'			)
           lowerCamelCase__        =				mda(datasets.utils.py_utils.dumps(A__			)			).hexdigest()
           lowerCamelCase__        =				tiktoken.get_encoding('r50k_base'			)
           lowerCamelCase__        =				mda(datasets.utils.py_utils.dumps(A__			)			).hexdigest()
           lowerCamelCase__        =				tiktoken.get_encoding('gpt2'			)
           lowerCamelCase__        =				mda(datasets.utils.py_utils.dumps(A__			)			).hexdigest()
           self.assertEqual(A__	,  A__			)
           self.assertNotEqual(A__	,  A__			)




     @require_torch
     def  __snake_case   (    self  :   Optional[Any]			)				->       List[Any]:
           import torch

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




     @require_spacy
     @require_spacy_model('en_core_web_sm'			)
     @require_spacy_model('fr_core_news_sm'			)
     @pytest.mark.integration
     def  __snake_case   (    self  :   Tuple			)				->       List[str]:
           import spacy

           lowerCamelCase__        =				spacy.load('en_core_web_sm'			)
           lowerCamelCase__        =				mda(datasets.utils.py_utils.dumps(A__			)			).hexdigest()
           lowerCamelCase__        =				spacy.load('fr_core_news_sm'			)
           lowerCamelCase__        =				mda(datasets.utils.py_utils.dumps(A__			)			).hexdigest()
           lowerCamelCase__        =				spacy.load('en_core_web_sm'			)
           lowerCamelCase__        =				mda(datasets.utils.py_utils.dumps(A__			)			).hexdigest()
           self.assertEqual(A__	,  A__			)
           self.assertNotEqual(A__	,  A__			)

@pytest.mark.integration
def 			lowerCAmelCase_			(  lowerCamelCase:       Path						)					->			Optional[int]:


      '''simple docstring'''




      lowerCamelCase__        =				tmp_path / 'dir1'
      lowerCamelCase__        =				tmp_path / 'dir2'
      dira.mkdir()
      dira.mkdir()
      lowerCamelCase__        =				'script.py'
      lowerCamelCase__        =				dedent(
          '\n    from datasets.fingerprint import Hasher\n    def foo():\n        pass\n    print(Hasher.hash(foo))\n    '						)
      lowerCamelCase__        =				dira / script_filename
      lowerCamelCase__        =				dira / script_filename
      with script_patha.open('w'						) as f:
            f.write(lowerCamelCase						)
      with script_patha.open('w'						) as f:
            f.write(lowerCamelCase						)
      lowerCamelCase__        =				subprocess.check_output(['python', str(lowerCamelCase						)]						)
      lowerCamelCase__        =				subprocess.check_output(['python', str(lowerCamelCase						)]						)
      assert fingerprinta == fingerprinta

def 			lowerCAmelCase_			(  )					->			int:


      '''simple docstring'''




      lowerCamelCase__        =				{'a': [0, 1, 2]}
      lowerCamelCase__        =				DatasetChild(InMemoryTable.from_pydict(lowerCamelCase						)						)
      lowerCamelCase__        =				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 			lowerCAmelCase_			(  )					->			Union[str, Any]:


      '''simple docstring'''




      lowerCamelCase__        =				{'a': [0, 1, 2]}






      class 			A			(		datasets.Dataset		):
           """simple docstring"""

           @fingerprint_transform(inplace=A__			)
           def  __snake_case   (    self  :   Any	,  A__  :   Union[str, Any]			)				->       List[Any]:
                 return DummyDatasetChild(self.data	,  fingerprint=A__			)
      lowerCamelCase__        =				DummyDatasetChild(InMemoryTable.from_pydict(lowerCamelCase						)						).func()






      class 			A			(		datasets.Dataset		):
           """simple docstring"""

           @fingerprint_transform(inplace=A__	,  version='1.0.0'			)
           def  __snake_case   (    self  :   str	,  A__  :   List[Any]			)				->       List[str]:
                 return DummyDatasetChild(self.data	,  fingerprint=A__			)
      lowerCamelCase__        =				DummyDatasetChild(InMemoryTable.from_pydict(lowerCamelCase						)						).func()






      class 			A			(		datasets.Dataset		):
           """simple docstring"""

           @fingerprint_transform(inplace=A__	,  version='2.0.0'			)
           def  __snake_case   (    self  :   List[str]	,  A__  :   int			)				->       int:
                 return DummyDatasetChild(self.data	,  fingerprint=A__			)
      lowerCamelCase__        =				DummyDatasetChild(InMemoryTable.from_pydict(lowerCamelCase						)						).func()

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


def 			lowerCAmelCase_			(  )					->			int:


      '''simple docstring'''




      lowerCamelCase__        =				Hasher()
      hasher.update(lambda lowerCamelCase						: x						)