"""simple docstring"""




from typing import Dict, List, Optional, Union

import numpy as np

from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
    center_crop,
    convert_to_rgb,
    get_resize_output_image_size,
    normalize,
    rescale,
    resize,
    to_channel_dimension_format,
)
from ...image_utils import (
    OPENAI_CLIP_MEAN,
    OPENAI_CLIP_STD,
    ChannelDimension,
    ImageInput,
    PILImageResampling,
    make_list_of_images,
    to_numpy_array,
    valid_images,
)
from ...utils import TensorType, is_vision_available, logging


__lowerCamelCase									=	logging.get_logger(__name__)


if is_vision_available():
				import PIL
class      UpperCamelCase__(      lowercase_			):
						lowerCAmelCase__	:    Optional[int]    				=		['pixel_values']





						def __init__(							self		,__UpperCAmelCase = True		,__UpperCAmelCase = None		,__UpperCAmelCase = PILImageResampling.BICUBIC		,__UpperCAmelCase = True		,__UpperCAmelCase = None		,__UpperCAmelCase = True		,__UpperCAmelCase = 1 / 2_55		,__UpperCAmelCase = True		,__UpperCAmelCase = None		,__UpperCAmelCase = None		,__UpperCAmelCase = True		,**__UpperCAmelCase		,)       ->					None:
													super().__init__(**UpperCAmelCase_  )
													A__						  =				size if size is not None else {"shortest_edge": 2_24}
													A__						  =				get_size_dict(UpperCAmelCase_		,default_to_square=UpperCAmelCase_  )
													A__						  =				crop_size if crop_size is not None else {"height": 2_24, "width": 2_24}
													A__						  =				get_size_dict(UpperCAmelCase_  )

													A__						  =				do_resize
													A__						  =				size
													A__						  =				resample
													A__						  =				do_center_crop
													A__						  =				crop_size
													A__						  =				do_rescale
													A__						  =				rescale_factor
													A__						  =				do_normalize
													A__						  =				image_mean if image_mean is not None else OPENAI_CLIP_MEAN
													A__						  =				image_std if image_std is not None else OPENAI_CLIP_STD
													A__						  =				do_convert_rgb





						def 					snake_case__						(							self		,__UpperCAmelCase		,__UpperCAmelCase		,__UpperCAmelCase = PILImageResampling.BICUBIC		,__UpperCAmelCase = None		,**__UpperCAmelCase		,)       ->					np.ndarray:
													A__						  =				get_size_dict(UpperCAmelCase_		,default_to_square=UpperCAmelCase_  )
													A__						  =				get_resize_output_image_size(
													    UpperCAmelCase_		,size=(size['height'], size['width'])		,default_to_square=UpperCAmelCase_  )
													return resize(UpperCAmelCase_		,size=UpperCAmelCase_		,resample=UpperCAmelCase_		,data_format=UpperCAmelCase_		,**UpperCAmelCase_  )





						def 					snake_case__						(							self		,__UpperCAmelCase		,__UpperCAmelCase		,__UpperCAmelCase = None		,**__UpperCAmelCase		,)       ->					np.ndarray:
													A__						  =				get_size_dict(UpperCAmelCase_  )
													return center_crop(UpperCAmelCase_		,size=(size['height'], size['width'])		,data_format=UpperCAmelCase_		,**UpperCAmelCase_  )





						def 					snake_case__						(							self		,__UpperCAmelCase		,__UpperCAmelCase		,__UpperCAmelCase = None		,**__UpperCAmelCase		,)       ->					Optional[int]:
													return rescale(UpperCAmelCase_		,scale=UpperCAmelCase_		,data_format=UpperCAmelCase_		,**UpperCAmelCase_  )





						def 					snake_case__						(							self		,__UpperCAmelCase		,__UpperCAmelCase		,__UpperCAmelCase		,__UpperCAmelCase = None		,**__UpperCAmelCase		,)       ->					np.ndarray:
													return normalize(UpperCAmelCase_		,mean=UpperCAmelCase_		,std=UpperCAmelCase_		,data_format=UpperCAmelCase_		,**UpperCAmelCase_  )





						def 					snake_case__						(							self		,__UpperCAmelCase		,__UpperCAmelCase = None		,__UpperCAmelCase = None		,__UpperCAmelCase = None		,__UpperCAmelCase = None		,__UpperCAmelCase = None		,__UpperCAmelCase = None		,__UpperCAmelCase = None		,__UpperCAmelCase = None		,__UpperCAmelCase = None		,__UpperCAmelCase = None		,__UpperCAmelCase = None		,__UpperCAmelCase = None		,__UpperCAmelCase = ChannelDimension.FIRST		,**__UpperCAmelCase		,)       ->					PIL.Image.Image:
													A__						  =				do_resize if do_resize is not None else self.do_resize
													A__						  =				size if size is not None else self.size
													A__						  =				get_size_dict(UpperCAmelCase_		,default_to_square=UpperCAmelCase_  )
													A__						  =				resample if resample is not None else self.resample
													A__						  =				do_center_crop if do_center_crop is not None else self.do_center_crop
													A__						  =				crop_size if crop_size is not None else self.crop_size
													A__						  =				get_size_dict(UpperCAmelCase_  )
													A__						  =				do_rescale if do_rescale is not None else self.do_rescale
													A__						  =				rescale_factor if rescale_factor is not None else self.rescale_factor
													A__						  =				do_normalize if do_normalize is not None else self.do_normalize
													A__						  =				image_mean if image_mean is not None else self.image_mean
													A__						  =				image_std if image_std is not None else self.image_std
													A__						  =				do_convert_rgb if do_convert_rgb is not None else self.do_convert_rgb

													A__						  =				make_list_of_images(UpperCAmelCase_  )

													if not valid_images(UpperCAmelCase_  ):
																				raise ValueError(
																				    'Invalid image type. Must be of type PIL.Image.Image, numpy.ndarray, '
																				    'torch.Tensor, tf.Tensor or jax.ndarray.'  )

													if do_resize and size is None:
																				raise ValueError('Size must be specified if do_resize is True.'  )

													if do_center_crop and crop_size is None:
																				raise ValueError('Crop size must be specified if do_center_crop is True.'  )

													if do_rescale and rescale_factor is None:
																				raise ValueError('Rescale factor must be specified if do_rescale is True.'  )

													if do_normalize and (image_mean is None or image_std is None):
																				raise ValueError('Image mean and std must be specified if do_normalize is True.'  )

													# PIL RGBA images are converted to RGB
													if do_convert_rgb:
																				A__						  =				[convert_to_rgb(UpperCAmelCase_  ) for image in images]

													# All transformations expect numpy arrays.
													A__						  =				[to_numpy_array(UpperCAmelCase_  ) for image in images]

													if do_resize:
																				A__						  =				[self.resize(image=UpperCAmelCase_		,size=UpperCAmelCase_		,resample=UpperCAmelCase_  ) for image in images]

													if do_center_crop:
																				A__						  =				[self.center_crop(image=UpperCAmelCase_		,size=UpperCAmelCase_  ) for image in images]

													if do_rescale:
																				A__						  =				[self.rescale(image=UpperCAmelCase_		,scale=UpperCAmelCase_  ) for image in images]

													if do_normalize:
																				A__						  =				[self.normalize(image=UpperCAmelCase_		,mean=UpperCAmelCase_		,std=UpperCAmelCase_  ) for image in images]

													A__						  =				[to_channel_dimension_format(UpperCAmelCase_		,UpperCAmelCase_  ) for image in images]

													A__						  =				{"pixel_values": images}
													return BatchFeature(data=UpperCAmelCase_		,tensor_type=UpperCAmelCase_  )













"""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						)






