






import os
from collections import namedtuple

import pytest

from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict


__a      :       Optional[Any]				  =   namedtuple(
    "_TestCommandArgs",
    [
        "dataset",
        "name",
        "cache_dir",
        "data_dir",
        "all_configs",
        "save_infos",
        "ignore_verifications",
        "force_redownload",
        "clear_cache",
    ],
    defaults=[None, None, None, False, False, False, False, False],
)



def 			_SCREAMING_SNAKE_CASE						( __lowercase   :			str			,				__lowercase   :			Optional[int]    )						->      Any:





    """simple docstring"""

    return (abs(source - target    ) / target) < 0.01






@pytest.mark.integration
def 			_SCREAMING_SNAKE_CASE						( __lowercase   :			Optional[Any]    )						->      Optional[Any]:





    """simple docstring"""

    __A         =	_TestCommandArgs(dataset=lowerCAmelCase__			,				all_configs=lowerCAmelCase__			,				save_infos=lowerCAmelCase__    )
    __A         =	TestCommand(*lowerCAmelCase__    )
    test_command.run()
    __A         =	os.path.join(lowerCAmelCase__			,				"""README.md"""    )
    assert os.path.exists(lowerCAmelCase__    )
    __A         =	DatasetInfosDict.from_directory(lowerCAmelCase__    )
    __A         =	DatasetInfosDict(
        {
            """default""": DatasetInfo(
                features=Features(
                    {
                        """tokens""": Sequence(Value("""string"""    )    ),
                        """ner_tags""": Sequence(
                            ClassLabel(names=["""O""", """B-PER""", """I-PER""", """B-ORG""", """I-ORG""", """B-LOC""", """I-LOC"""]    )    ),
                        """langs""": Sequence(Value("""string"""    )    ),
                        """spans""": Sequence(Value("""string"""    )    ),
                    }    )			,				splits=[
                    {
                        """name""": """train""",
                        """num_bytes""": 2_3_5_1_5_6_3,
                        """num_examples""": 1_0_0_0_0,
                    },
                    {
                        """name""": """validation""",
                        """num_bytes""": 2_3_8_4_1_8,
                        """num_examples""": 1_0_0_0,
                    },
                ]			,				download_size=3_9_4_0_6_8_0			,				dataset_size=2_5_8_9_9_8_1			,				)
        }    )
    assert dataset_infos.keys() == expected_dataset_infos.keys()
    for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
        __A         =	getattr(dataset_infos["""default"""]			,				lowerCAmelCase__    ), getattr(expected_dataset_infos["""default"""]			,				lowerCAmelCase__    )
        if key == "num_bytes":
            assert is_apercent_close(lowerCAmelCase__			,				lowerCAmelCase__    )
        elif key == "splits":
            assert list(lowerCAmelCase__    ) == list(lowerCAmelCase__    )
            for split in result:
                assert result[split].name == expected[split].name
                assert result[split].num_examples == expected[split].num_examples
                assert is_apercent_close(result[split].num_bytes			,				expected[split].num_bytes    )
        else:
            result == expected












import random
import sys

import numpy as np
from matplotlib import pyplot as plt
from matplotlib.colors import ListedColormap

__a      :       List[Any]				  =   "Usage of script: script_name <size_of_canvas:int>"

__a      :       Dict				  =   [0] * 100 + [1] * 10
random.shuffle(choice)



def 			_SCREAMING_SNAKE_CASE						( __lowercase   :			int    )						->      list[list[bool]]:





    """simple docstring"""

    __A         =	[[False for i in range(__lowercase    )] for j in range(__lowercase    )]
    return canvas



def 			_SCREAMING_SNAKE_CASE						( __lowercase   :			list[list[bool]]    )						->      None:





    """simple docstring"""

    for i, row in enumerate(__lowercase    ):
        for j, _ in enumerate(__lowercase    ):
            __A         =	bool(random.getrandbits(1    )    )



def 			_SCREAMING_SNAKE_CASE						( __lowercase   :			list[list[bool]]    )						->      list[list[bool]]:





    """simple docstring"""

    __A         =	np.array(__lowercase    )
    __A         =	np.array(create_canvas(current_canvas.shape[0]    )    )
    for r, row in enumerate(__lowercase    ):
        for c, pt in enumerate(__lowercase    ):
            __A         =	__judge_point(
                __lowercase			,				current_canvas[r - 1 : r + 2, c - 1 : c + 2]    )

    __A         =	next_gen_canvas
    del next_gen_canvas  # cleaning memory as we move on.
    __A         =	current_canvas.tolist()
    return return_canvas



def 			_SCREAMING_SNAKE_CASE						( __lowercase   :			bool			,				__lowercase   :			list[list[bool]]    )						->      bool:





    """simple docstring"""

    __A         =	0
    __A         =	0
    # finding dead or alive neighbours count.
    for i in neighbours:
        for status in i:
            if status:
                alive += 1
            else:
                dead += 1

    # handling duplicate entry for focus pt.
    if pt:
        alive -= 1
    else:
        dead -= 1

    # running the rules of game here.
    __A         =	pt
    if pt:
        if alive < 2:
            __A         =	False
        elif alive == 2 or alive == 3:
            __A         =	True
        elif alive > 3:
            __A         =	False
    else:
        if alive == 3:
            __A         =	True

    return state


if __name__ == "__main__":
  if len(sys.argv) != 2:
    raise Exception(usage_doc)

  __a      :       str				  =   int(sys.argv[1])
  # main working structure of this module.
  __a      :       List[Any]				  =   create_canvas(canvas_size)
  seed(c)
  __a  ,__a      :       int				  =   plt.subplots()
  fig.show()
  __a      :       Union[str, Any]				  =   ListedColormap(["w", "k"])
  try:
    while True:
      __a      :       Dict				  =   run(c)
      ax.matshow(c, cmap=cmap)
      fig.canvas.draw()
      ax.cla()
  except KeyboardInterrupt:
    # do nothing.
    pass




