


import random
import sys

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

__UpperCamelCase    		=       'Usage of script: script_name <size_of_canvas:int>'

__UpperCamelCase    		=       [0] * 1_0_0 + [1] * 1_0
random.shuffle(choice)
def 			UpperCamelCase_(				_A   :int  )->		Union[str, Any]:
			UpperCamelCase__					=       [[False for i in range(SCREAMING_SNAKE_CASE__  )] for j in range(SCREAMING_SNAKE_CASE__  )]
			return canvas
def 			UpperCamelCase_(				_A   :list[list[bool]]  )->		Tuple:





			for i, row in enumerate(SCREAMING_SNAKE_CASE__  ):
						for j, _ in enumerate(SCREAMING_SNAKE_CASE__  ):
									UpperCamelCase__					=       bool(random.getrandbits(1  )  )
def 			UpperCamelCase_(				_A   :list[list[bool]]  )->		List[Any]:
			UpperCamelCase__					=       np.array(SCREAMING_SNAKE_CASE__  )
			UpperCamelCase__					=       np.array(create_canvas(current_canvas.shape[0]  )  )
			for r, row in enumerate(SCREAMING_SNAKE_CASE__  ):
						for c, pt in enumerate(SCREAMING_SNAKE_CASE__  ):
									UpperCamelCase__					=       __judge_point(
									    SCREAMING_SNAKE_CASE__				,     current_canvas[r - 1 : r + 2, c - 1 : c + 2]  )

			UpperCamelCase__					=       next_gen_canvas
			del next_gen_canvas  # cleaning memory as we move on.
			UpperCamelCase__					=       current_canvas.tolist()
			return return_canvas
def 			UpperCamelCase_(				_A   :bool				,     _A   :list[list[bool]]  )->		Optional[int]:
			UpperCamelCase__					=       0
			UpperCamelCase__					=       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.
			UpperCamelCase__					=       pt
			if pt:
						if alive < 2:
									UpperCamelCase__					=       False
						elif alive == 2 or alive == 3:
									UpperCamelCase__					=       True
						elif alive > 3:
									UpperCamelCase__					=       False
			else:
						if alive == 3:
									UpperCamelCase__					=       True

			return state


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

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






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_speech_available,
    is_torch_available,
)


__UpperCamelCase    		=       {
    'configuration_trocr': ['TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TrOCRConfig'],
    'processing_trocr': ['TrOCRProcessor'],
}


try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__UpperCamelCase    		=       [
						    'TROCR_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'TrOCRForCausalLM',
						    'TrOCRPreTrainedModel',
						]


if TYPE_CHECKING:
						from .configuration_trocr import TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP, TrOCRConfig
						from .processing_trocr import TrOCRProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_trocr import TROCR_PRETRAINED_MODEL_ARCHIVE_LIST, TrOCRForCausalLM, TrOCRPreTrainedModel

else:
						import sys

						__UpperCamelCase    		=       _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


