"""simple docstring"""




import importlib
from typing import List, Optional, Union

from seqeval.metrics import accuracy_score, classification_report

import datasets


__lowerCamelCase									=	"\\n@inproceedings{ramshaw-marcus-1995-text,\n    title = \"Text Chunking using Transformation-Based Learning\",\n    author = \"Ramshaw, Lance  and\n      Marcus, Mitch\",\n    booktitle = \"Third Workshop on Very Large Corpora\",\n    year = \"1995\",\n    url = \"https://www.aclweb.org/anthology/W95-0107\",\n}\n@misc{seqeval,\n  title={{seqeval}: A Python framework for sequence labeling evaluation},\n  url={https://github.com/chakki-works/seqeval},\n  note={Software available from https://github.com/chakki-works/seqeval},\n  author={Hiroki Nakayama},\n  year={2018},\n}\n"

__lowerCamelCase									=	"\\nseqeval is a Python framework for sequence labeling evaluation.\nseqeval can evaluate the performance of chunking tasks such as named-entity recognition, part-of-speech tagging, semantic role labeling and so on.\n\nThis is well-tested by using the Perl script conlleval, which can be used for\nmeasuring the performance of a system that has processed the CoNLL-2000 shared task data.\n\nseqeval supports following formats:\nIOB1\nIOB2\nIOE1\nIOE2\nIOBES\n\nSee the [README.md] file at https://github.com/chakki-works/seqeval for more information.\n"

__lowerCamelCase									=	"\nProduces labelling scores along with its sufficient statistics\nfrom a source against one or more references.\n\nArgs:\n    predictions: List of List of predicted labels (Estimated targets as returned by a tagger)\n    references: List of List of reference labels (Ground truth (correct) target values)\n    suffix: True if the IOB prefix is after type, False otherwise. default: False\n    scheme: Specify target tagging scheme. Should be one of [\"IOB1\", \"IOB2\", \"IOE1\", \"IOE2\", \"IOBES\", \"BILOU\"].\n        default: None\n    mode: Whether to count correct entity labels with incorrect I/B tags as true positives or not.\n        If you want to only count exact matches, pass mode=\"strict\". default: None.\n    sample_weight: Array-like of shape (n_samples,), weights for individual samples. default: None\n    zero_division: Which value to substitute as a metric value when encountering zero division. Should be on of 0, 1,\n        \"warn\". \"warn\" acts as 0, but the warning is raised.\n\nReturns:\n    'scores': dict. Summary of the scores for overall and per type\n        Overall:\n            'accuracy': accuracy,\n            'precision': precision,\n            'recall': recall,\n            'f1': F1 score, also known as balanced F-score or F-measure,\n        Per type:\n            'precision': precision,\n            'recall': recall,\n            'f1': F1 score, also known as balanced F-score or F-measure\nExamples:\n\n    >>> predictions = [['O', 'O', 'B-MISC', 'I-MISC', 'I-MISC', 'I-MISC', 'O'], ['B-PER', 'I-PER', 'O']]\n    >>> references = [['O', 'O', 'O', 'B-MISC', 'I-MISC', 'I-MISC', 'O'], ['B-PER', 'I-PER', 'O']]\n    >>> seqeval = datasets.load_metric(\"seqeval\")\n    >>> results = seqeval.compute(predictions=predictions, references=references)\n    >>> print(list(results.keys()))\n    ['MISC', 'PER', 'overall_precision', 'overall_recall', 'overall_f1', 'overall_accuracy']\n    >>> print(results[\"overall_f1\"])\n    0.5\n    >>> print(results[\"PER\"][\"f1\"])\n    1.0\n"
@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION		,    _KWARGS_DESCRIPTION			)
class      UpperCamelCase__(      datasets.Metric			):





						def 					snake_case__						(							self  )       ->					int:
													return datasets.MetricInfo(
													    description=_DESCRIPTION		,citation=_CITATION		,homepage='https://github.com/chakki-works/seqeval'		,inputs_description=_KWARGS_DESCRIPTION		,features=datasets.Features(
													        {
													            'predictions': datasets.Sequence(datasets.Value('string'		,id='label'  )		,id='sequence'  ),
													            'references': datasets.Sequence(datasets.Value('string'		,id='label'  )		,id='sequence'  ),
													        }  )		,codebase_urls=['https://github.com/chakki-works/seqeval']		,reference_urls=['https://github.com/chakki-works/seqeval']		,)





						def 					snake_case__						(							self		,__UpperCAmelCase		,__UpperCAmelCase		,__UpperCAmelCase = False		,__UpperCAmelCase = None		,__UpperCAmelCase = None		,__UpperCAmelCase = None		,__UpperCAmelCase = "warn"		,)       ->					List[Any]:




													if scheme is not None:
																				try:
																											A__						  =				importlib.import_module('seqeval.scheme'  )
																											A__						  =				getattr(UpperCAmelCase_		,UpperCAmelCase_  )
																				except AttributeError:
																											raise ValueError(f'''Scheme should be one of [IOB1, IOB2, IOE1, IOE2, IOBES, BILOU], got {scheme}'''  )
													A__						  =				classification_report(
													    y_true=UpperCAmelCase_		,y_pred=UpperCAmelCase_		,suffix=UpperCAmelCase_		,output_dict=UpperCAmelCase_		,scheme=UpperCAmelCase_		,mode=UpperCAmelCase_		,sample_weight=UpperCAmelCase_		,zero_division=UpperCAmelCase_		,)
													report.pop('macro avg'  )
													report.pop('weighted avg'  )
													A__						  =				report.pop('micro avg'  )

													A__						  =				{
													    type_name: {
													        "precision": score["precision"],
													        "recall": score["recall"],
													        "f1": score["f1-score"],
													        "number": score["support"],
													    }
													    for type_name, score in report.items()
													}
													A__						  =				overall_score["precision"]
													A__						  =				overall_score["recall"]
													A__						  =				overall_score["f1-score"]
													A__						  =				accuracy_score(y_true=UpperCAmelCase_		,y_pred=UpperCAmelCase_  )

													return scores













"""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 						_a  :





   '''simple docstring'''






   def __init__(       self					, UpperCAmelCase_)			->   List[Any]:




          '''simple docstring'''




          lowercase__:							List[str]         =     foo





   def __call__(       self)			->   Union[str, Any]:




          '''simple docstring'''




          return self.foo







class 						_a  (		datasets.Dataset       ):





   '''simple docstring'''






   @fingerprint_transform(inplace=UpperCAmelCase_)
   def __lowercase							(       self					, UpperCAmelCase_					, *UpperCAmelCase_					, **UpperCAmelCase_)			->   int:




          '''simple docstring'''




          return DatasetChild(self.data					, fingerprint=UpperCAmelCase_)





   @fingerprint_transform(inplace=UpperCAmelCase_)
   def __lowercase							(       self					, UpperCAmelCase_					, *UpperCAmelCase_					, **UpperCAmelCase_)			->   int:




          '''simple docstring'''




          return DatasetChild(self.data					, fingerprint=UpperCAmelCase_)







class 						_a  :





   '''simple docstring'''






   def __init__(       self					, UpperCAmelCase_)			->   Optional[int]:




          '''simple docstring'''




          lowercase__:							Tuple         =     callable





   def __call__(       self					, *UpperCAmelCase_					, **UpperCAmelCase_)			->   Optional[int]:




          '''simple docstring'''




          if self.callable is not None:
                 return self.callable(*UpperCAmelCase_					, **UpperCAmelCase_)





   def __getstate__(       self)			->   int:




          '''simple docstring'''




          raise pickle.PicklingError()







class 						_a  (		lowercase_       ):





   '''simple docstring'''






   @require_transformers
   @pytest.mark.integration
   def __lowercase							(       self)			->   List[Any]:




          '''simple docstring'''




          from transformers import AutoTokenizer

          def encode(UpperCAmelCase_):
                 return tokenizer(UpperCAmelCase_)

          # TODO: add hash consistency tests across sessions
          lowercase__:							Tuple         =     AutoTokenizer.from_pretrained("bert-base-uncased")
          lowercase__:							Optional[Any]         =     mda(datasets.utils.py_utils.dumps(UpperCAmelCase_)).hexdigest()
          lowercase__:							Any         =     mda(datasets.utils.py_utils.dumps(lambda UpperCAmelCase_: tokenizer(UpperCAmelCase_))).hexdigest()
          lowercase__:							Optional[Any]         =     mda(datasets.utils.py_utils.dumps(UpperCAmelCase_)).hexdigest()
          lowercase__:							Tuple         =     AutoTokenizer.from_pretrained("bert-base-cased")
          lowercase__:							int         =     mda(datasets.utils.py_utils.dumps(UpperCAmelCase_)).hexdigest()
          lowercase__:							Tuple         =     mda(datasets.utils.py_utils.dumps(lambda UpperCAmelCase_: tokenizer(UpperCAmelCase_))).hexdigest()
          lowercase__:							List[str]         =     mda(datasets.utils.py_utils.dumps(UpperCAmelCase_)).hexdigest()
          lowercase__:							Optional[int]         =     AutoTokenizer.from_pretrained("bert-base-uncased")
          lowercase__:							Tuple         =     mda(datasets.utils.py_utils.dumps(UpperCAmelCase_)).hexdigest()
          lowercase__:							str         =     mda(datasets.utils.py_utils.dumps(lambda UpperCAmelCase_: tokenizer(UpperCAmelCase_))).hexdigest()
          lowercase__:							Tuple         =     mda(datasets.utils.py_utils.dumps(UpperCAmelCase_)).hexdigest()
          self.assertEqual(UpperCAmelCase_					, UpperCAmelCase_)
          self.assertNotEqual(UpperCAmelCase_					, UpperCAmelCase_)
          self.assertEqual(UpperCAmelCase_					, UpperCAmelCase_)
          self.assertNotEqual(UpperCAmelCase_					, UpperCAmelCase_)
          self.assertEqual(UpperCAmelCase_					, UpperCAmelCase_)
          self.assertNotEqual(UpperCAmelCase_					, UpperCAmelCase_)





   @require_transformers
   @pytest.mark.integration
   def __lowercase							(       self)			->   Optional[int]:




          '''simple docstring'''




          from transformers import AutoTokenizer

          lowercase__:							Optional[int]         =     AutoTokenizer.from_pretrained("gpt2")
          lowercase__:							Any         =     mda(datasets.utils.py_utils.dumps(UpperCAmelCase_)).hexdigest()
          tokenizer("Hello world !")  # call once to change the tokenizer's cache
          lowercase__:							Tuple         =     mda(datasets.utils.py_utils.dumps(UpperCAmelCase_)).hexdigest()
          self.assertEqual(UpperCAmelCase_					, UpperCAmelCase_)





   @require_regex
   def __lowercase							(       self)			->   str:




          '''simple docstring'''




          import regex

          lowercase__:							List[Any]         =     regex.Regex("foo")
          lowercase__:							Optional[int]         =     mda(datasets.utils.py_utils.dumps(UpperCAmelCase_)).hexdigest()
          lowercase__:							List[Any]         =     regex.Regex("bar")
          lowercase__:							List[str]         =     mda(datasets.utils.py_utils.dumps(UpperCAmelCase_)).hexdigest()
          lowercase__:							Union[str, Any]         =     regex.Regex("foo")
          lowercase__:							Optional[Any]         =     mda(datasets.utils.py_utils.dumps(UpperCAmelCase_)).hexdigest()
          self.assertEqual(UpperCAmelCase_					, UpperCAmelCase_)
          self.assertNotEqual(UpperCAmelCase_					, UpperCAmelCase_)







class 						_a  (		lowercase_       ):





   '''simple docstring'''






   def __lowercase							(       self)			->   int:




          '''simple docstring'''




          def func():
                 return foo

          lowercase__:							int         =     [0]
          lowercase__:							Optional[Any]         =     mda(datasets.utils.py_utils.dumps(UpperCAmelCase_)).hexdigest()
          lowercase__:							Dict         =     [1]
          lowercase__:							int         =     mda(datasets.utils.py_utils.dumps(UpperCAmelCase_)).hexdigest()
          lowercase__:							Union[str, Any]         =     [0]
          lowercase__:							List[Any]         =     mda(datasets.utils.py_utils.dumps(UpperCAmelCase_)).hexdigest()
          self.assertEqual(UpperCAmelCase_					, UpperCAmelCase_)
          self.assertNotEqual(UpperCAmelCase_					, UpperCAmelCase_)





   def __lowercase							(       self)			->   Dict:




          '''simple docstring'''




          def func():
                 pass

          lowercase__:							Any         =     mda(datasets.utils.py_utils.dumps(UpperCAmelCase_)).hexdigest()

          def func():
                 pass

          lowercase__:							List[Any]         =     mda(datasets.utils.py_utils.dumps(UpperCAmelCase_)).hexdigest()
          self.assertEqual(UpperCAmelCase_					, UpperCAmelCase_)





   def __lowercase							(       self)			->   str:




          '''simple docstring'''




          lowercase__:							Optional[int]         =     mda(datasets.utils.py_utils.dumps(Foo([0]))).hexdigest()
          lowercase__:							Optional[Any]         =     mda(datasets.utils.py_utils.dumps(Foo([1]))).hexdigest()
          lowercase__:							int         =     mda(datasets.utils.py_utils.dumps(Foo([0]))).hexdigest()
          self.assertEqual(UpperCAmelCase_					, UpperCAmelCase_)
          self.assertNotEqual(UpperCAmelCase_					, UpperCAmelCase_)





   def __lowercase							(       self)			->   Union[str, Any]:




          '''simple docstring'''




          lowercase__:							Any         =     mda(datasets.utils.py_utils.dumps(Foo([0]).__call__)).hexdigest()
          lowercase__:							List[Any]         =     mda(datasets.utils.py_utils.dumps(Foo([1]).__call__)).hexdigest()
          lowercase__:							Optional[Any]         =     mda(datasets.utils.py_utils.dumps(Foo([0]).__call__)).hexdigest()
          self.assertEqual(UpperCAmelCase_					, UpperCAmelCase_)
          self.assertNotEqual(UpperCAmelCase_					, UpperCAmelCase_)





   def __lowercase							(       self)			->   Union[str, Any]:




          '''simple docstring'''




          lowercase__:							List[Any]         =     (
              "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(*UpperCAmelCase_):
                 if hasattr(args[-3]					, "encode"):
                        lowercase__:							Tuple         =     list(UpperCAmelCase_)
                        lowercase__:							str         =     args[-3].encode()  # co_lnotab
                        lowercase__:							Any         =     args[-10].encode()  # co_code
                 if hasattr(UpperCAmelCase_					, "co_posonlyargcount"):
                        if len(UpperCAmelCase_) == 16:
                               return CodeType(*UpperCAmelCase_)
                        elif len(UpperCAmelCase_) == 15:
                               return CodeType(args[0]					, 0					, *args[1:])
                        return CodeType(args[0]					, 0					, 0					, *args[1:])
                 elif hasattr(UpperCAmelCase_					, "co_kwonlyargcount"):
                        if len(UpperCAmelCase_) == 16:
                               return CodeType(args[0]					, *args[2:])
                        elif len(UpperCAmelCase_) == 15:
                               return CodeType(*UpperCAmelCase_)
                        return CodeType(args[0]					, 0					, *args[1:])
                 if len(UpperCAmelCase_) == 16:
                        return CodeType(args[0]					, *args[3:])
                 elif len(UpperCAmelCase_) == 15:
                        return CodeType(args[0]					, *args[2:])
                 return CodeType(*UpperCAmelCase_)

          def create_ipython_func(UpperCAmelCase_					, UpperCAmelCase_):
                 def func():
                        return returned_obj

                 lowercase__:							Dict         =     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"):
                        lowercase__:							Union[str, Any]         =     _create_code_pyaa(
                            *[getattr(UpperCAmelCase_					, UpperCAmelCase_) if k != "co_filename" else co_filename for k in code_args_pyaa])
                 else:
                        lowercase__:							Tuple         =     code.replace(co_filename=UpperCAmelCase_)
                 return FunctionType(UpperCAmelCase_					, func.__globals__					, func.__name__					, func.__defaults__					, func.__closure__)

          lowercase__    ,      lowercase__:							Any         =     "<ipython-input-2-e0383a102aae>", [0]
          lowercase__:							List[str]         =     mda(datasets.utils.py_utils.dumps(create_ipython_func(UpperCAmelCase_					, UpperCAmelCase_))).hexdigest()
          lowercase__    ,      lowercase__:							Optional[Any]         =     "<ipython-input-2-e0383a102aae>", [1]
          lowercase__:							Optional[int]         =     mda(datasets.utils.py_utils.dumps(create_ipython_func(UpperCAmelCase_					, UpperCAmelCase_))).hexdigest()
          lowercase__    ,      lowercase__:							Tuple         =     "<ipython-input-5-713f6613acf3>", [0]
          lowercase__:							List[str]         =     mda(datasets.utils.py_utils.dumps(create_ipython_func(UpperCAmelCase_					, UpperCAmelCase_))).hexdigest()
          self.assertEqual(UpperCAmelCase_					, UpperCAmelCase_)
          self.assertNotEqual(UpperCAmelCase_					, UpperCAmelCase_)

          lowercase__    ,      lowercase__:							Dict         =     os.path.join(gettempdir()					, "ipykernel_12345"					, "321456789.py"), [0]
          lowercase__:							Tuple         =     mda(datasets.utils.py_utils.dumps(create_ipython_func(UpperCAmelCase_					, UpperCAmelCase_))).hexdigest()
          lowercase__    ,      lowercase__:							Dict         =     os.path.join(gettempdir()					, "ipykernel_12345"					, "321456789.py"), [1]
          lowercase__:							Any         =     mda(datasets.utils.py_utils.dumps(create_ipython_func(UpperCAmelCase_					, UpperCAmelCase_))).hexdigest()
          lowercase__    ,      lowercase__:							Any         =     os.path.join(gettempdir()					, "ipykernel_12345"					, "654123987.py"), [0]
          lowercase__:							Dict         =     mda(datasets.utils.py_utils.dumps(create_ipython_func(UpperCAmelCase_					, UpperCAmelCase_))).hexdigest()
          self.assertEqual(UpperCAmelCase_					, UpperCAmelCase_)
          self.assertNotEqual(UpperCAmelCase_					, UpperCAmelCase_)





   def __lowercase							(       self)			->   Dict:




          '''simple docstring'''




          lowercase__    ,      lowercase__:							str         =     [0], [1]

          def func():
                 return foo, bar

          lowercase__:							List[str]         =     "__main__"

          def globalvars_mocka_side_effect(UpperCAmelCase_					, *UpperCAmelCase_					, **UpperCAmelCase_):
                 return {"foo": foo, "bar": bar}

          def globalvars_mocka_side_effect(UpperCAmelCase_					, *UpperCAmelCase_					, **UpperCAmelCase_):
                 return {"bar": bar, "foo": foo}

          with patch("dill.detect.globalvars"					, side_effect=UpperCAmelCase_) as globalvars_mocka:
                 lowercase__:							Optional[Any]         =     mda(datasets.utils.py_utils.dumps(UpperCAmelCase_)).hexdigest()
                 self.assertGreater(globalvars_mocka.call_count					, 0)
          with patch("dill.detect.globalvars"					, side_effect=UpperCAmelCase_) as globalvars_mocka:
                 lowercase__:							Tuple         =     mda(datasets.utils.py_utils.dumps(UpperCAmelCase_)).hexdigest()
                 self.assertGreater(globalvars_mocka.call_count					, 0)
          self.assertEqual(UpperCAmelCase_					, UpperCAmelCase_)







class 						_a  (		lowercase_       ):





   '''simple docstring'''






   def __lowercase							(       self)			->   int:




          '''simple docstring'''




          lowercase__:							List[Any]         =     Hasher.hash("hello")
          lowercase__:							Optional[int]         =     Hasher.hash("hello")
          lowercase__:							int         =     Hasher.hash("there")
          self.assertEqual(UpperCAmelCase_					, UpperCAmelCase_)
          self.assertNotEqual(UpperCAmelCase_					, UpperCAmelCase_)





   def __lowercase							(       self)			->   Any:




          '''simple docstring'''




          lowercase__:							str         =     Hasher.hash(Foo("hello"))
          lowercase__:							Tuple         =     Hasher.hash(Foo("hello"))
          lowercase__:							Union[str, Any]         =     Hasher.hash(Foo("there"))
          self.assertEqual(UpperCAmelCase_					, UpperCAmelCase_)
          self.assertNotEqual(UpperCAmelCase_					, UpperCAmelCase_)





   def __lowercase							(       self)			->   str:




          '''simple docstring'''




          lowercase__:							str         =     Hasher()
          for x in ["hello", Foo("hello")]:
                 hasher.update(UpperCAmelCase_)
          lowercase__:							Dict         =     hasher.hexdigest()
          lowercase__:							Any         =     Hasher()
          for x in ["hello", Foo("hello")]:
                 hasher.update(UpperCAmelCase_)
          lowercase__:							List[Any]         =     hasher.hexdigest()
          lowercase__:							Optional[int]         =     Hasher()
          for x in ["there", Foo("there")]:
                 hasher.update(UpperCAmelCase_)
          lowercase__:							Tuple         =     hasher.hexdigest()
          self.assertEqual(UpperCAmelCase_					, UpperCAmelCase_)
          self.assertNotEqual(UpperCAmelCase_					, UpperCAmelCase_)





   def __lowercase							(       self)			->   List[str]:




          '''simple docstring'''




          with self.assertRaises(pickle.PicklingError):
                 Hasher.hash(UnpicklableCallable(Foo("hello")))





   def __lowercase							(       self)			->   Optional[Any]:




          '''simple docstring'''




          lowercase__:							Optional[Any]         =     "abc"
          lowercase__:							Any         =     [string, string]  # two strings have the same ids
          lowercase__:							str         =     [string, string]
          lowercase__:							Optional[int]         =     json.loads(F"""[\"{string}\", \"{string}\"]""")  # two strings have different ids
          self.assertIs(obja[0]					, UpperCAmelCase_)
          self.assertIs(obja[0]					, obja[1])
          self.assertIs(obja[0]					, UpperCAmelCase_)
          self.assertIs(obja[0]					, obja[1])
          self.assertIsNot(obja[0]					, UpperCAmelCase_)
          self.assertIsNot(obja[0]					, obja[1])
          lowercase__:							List[Any]         =     Hasher.hash(UpperCAmelCase_)
          lowercase__:							str         =     Hasher.hash(UpperCAmelCase_)
          lowercase__:							Tuple         =     Hasher.hash(UpperCAmelCase_)
          self.assertEqual(UpperCAmelCase_					, UpperCAmelCase_)
          self.assertEqual(UpperCAmelCase_					, UpperCAmelCase_)





   @require_tiktoken
   def __lowercase							(       self)			->   str:




          '''simple docstring'''




          import tiktoken

          lowercase__:							Union[str, Any]         =     tiktoken.get_encoding("gpt2")
          lowercase__:							List[str]         =     mda(datasets.utils.py_utils.dumps(UpperCAmelCase_)).hexdigest()
          lowercase__:							Dict         =     tiktoken.get_encoding("r50k_base")
          lowercase__:							Dict         =     mda(datasets.utils.py_utils.dumps(UpperCAmelCase_)).hexdigest()
          lowercase__:							List[Any]         =     tiktoken.get_encoding("gpt2")
          lowercase__:							Optional[int]         =     mda(datasets.utils.py_utils.dumps(UpperCAmelCase_)).hexdigest()
          self.assertEqual(UpperCAmelCase_					, UpperCAmelCase_)
          self.assertNotEqual(UpperCAmelCase_					, UpperCAmelCase_)





   @require_torch
   def __lowercase							(       self)			->   List[Any]:




          '''simple docstring'''




          import torch

          lowercase__:							Tuple         =     torch.tensor([1.0])
          lowercase__:							Optional[int]         =     mda(datasets.utils.py_utils.dumps(UpperCAmelCase_)).hexdigest()
          lowercase__:							Dict         =     torch.tensor([2.0])
          lowercase__:							Union[str, Any]         =     mda(datasets.utils.py_utils.dumps(UpperCAmelCase_)).hexdigest()
          lowercase__:							Tuple         =     torch.tensor([1.0])
          lowercase__:							Any         =     mda(datasets.utils.py_utils.dumps(UpperCAmelCase_)).hexdigest()
          self.assertEqual(UpperCAmelCase_					, UpperCAmelCase_)
          self.assertNotEqual(UpperCAmelCase_					, UpperCAmelCase_)





   @require_spacy
   @require_spacy_model("en_core_web_sm")
   @require_spacy_model("fr_core_news_sm")
   @pytest.mark.integration
   def __lowercase							(       self)			->   Any:




          '''simple docstring'''




          import spacy

          lowercase__:							Tuple         =     spacy.load("en_core_web_sm")
          lowercase__:							Any         =     mda(datasets.utils.py_utils.dumps(UpperCAmelCase_)).hexdigest()
          lowercase__:							Any         =     spacy.load("fr_core_news_sm")
          lowercase__:							str         =     mda(datasets.utils.py_utils.dumps(UpperCAmelCase_)).hexdigest()
          lowercase__:							int         =     spacy.load("en_core_web_sm")
          lowercase__:							str         =     mda(datasets.utils.py_utils.dumps(UpperCAmelCase_)).hexdigest()
          self.assertEqual(UpperCAmelCase_					, UpperCAmelCase_)
          self.assertNotEqual(UpperCAmelCase_					, UpperCAmelCase_)







@pytest.mark.integration
def 							A(    snake_case_						):
       """simple docstring"""





       lowercase__:							Optional[Any]         =     tmp_path / "dir1"
       lowercase__:							Tuple         =     tmp_path / "dir2"
       dira.mkdir()
       dira.mkdir()
       lowercase__:							Union[str, Any]         =     "script.py"
       lowercase__:							Any         =     dedent(
           "\n    from datasets.fingerprint import Hasher\n    def foo():\n        pass\n    print(Hasher.hash(foo))\n    "						)
       lowercase__:							List[str]         =     dira / script_filename
       lowercase__:							int         =     dira / script_filename
       with script_patha.open("w"						) as f:
              f.write(snake_case_						)
       with script_patha.open("w"						) as f:
              f.write(snake_case_						)
       lowercase__:							Any         =     subprocess.check_output(["python", str(snake_case_						)]						)
       lowercase__:							Optional[Any]         =     subprocess.check_output(["python", str(snake_case_						)]						)
       assert fingerprinta == fingerprinta






def 							A(    ):
       """simple docstring"""





       lowercase__:							Optional[int]         =     {"a": [0, 1, 2]}
       lowercase__:							Dict         =     DatasetChild(InMemoryTable.from_pydict(snake_case_						)						)
       lowercase__:							List[Any]         =     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 							A(    ):
       """simple docstring"""





       lowercase__:							List[str]         =     {"a": [0, 1, 2]}







       class 						_a  (		datasets.Dataset       ):





          '''simple docstring'''






          @fingerprint_transform(inplace=UpperCAmelCase_)
          def __lowercase							(       self					, UpperCAmelCase_)			->   List[str]:




                 '''simple docstring'''




                 return DummyDatasetChild(self.data					, fingerprint=UpperCAmelCase_)







       lowercase__:							Tuple         =     DummyDatasetChild(InMemoryTable.from_pydict(snake_case_						)						).func()







       class 						_a  (		datasets.Dataset       ):





          '''simple docstring'''






          @fingerprint_transform(inplace=UpperCAmelCase_					, version="1.0.0")
          def __lowercase							(       self					, UpperCAmelCase_)			->   Optional[int]:




                 '''simple docstring'''




                 return DummyDatasetChild(self.data					, fingerprint=UpperCAmelCase_)







       lowercase__:							Optional[int]         =     DummyDatasetChild(InMemoryTable.from_pydict(snake_case_						)						).func()







       class 						_a  (		datasets.Dataset       ):





          '''simple docstring'''






          @fingerprint_transform(inplace=UpperCAmelCase_					, version="2.0.0")
          def __lowercase							(       self					, UpperCAmelCase_)			->   Any:




                 '''simple docstring'''




                 return DummyDatasetChild(self.data					, fingerprint=UpperCAmelCase_)







       lowercase__:							Optional[int]         =     DummyDatasetChild(InMemoryTable.from_pydict(snake_case_						)						).func()

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







def 							A(    ):
       """simple docstring"""





       lowercase__:							int         =     Hasher()
       hasher.update(lambda snake_case_						: x						)






