





'''simple docstring'''



from __future__ import annotations

from PIL import Image

# Define glider example
_SCREAMING_SNAKE_CASE					=    [
    [0, 1, 0, 0, 0, 0, 0, 0],
    [0, 0, 1, 0, 0, 0, 0, 0],
    [1, 1, 1, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0, 0],
]

# Define blinker example
_SCREAMING_SNAKE_CASE					=    [[0, 1, 0], [0, 1, 0], [0, 1, 0]]




def    _lowerCAmelCase						(				lowerCamelCase_			:  list[list[int]]				):
			__lowercase										=							[]
			for i in range(len(lowerCamelCase_				)				):
						__lowercase										=							[]
						for j in range(len(cells[i]				)				):
									# Get the number of live neighbours
									__lowercase										=							0
									if i > 0 and j > 0:
												neighbour_count += cells[i - 1][j - 1]
									if i > 0:
												neighbour_count += cells[i - 1][j]
									if i > 0 and j < len(cells[i]				) - 1:
												neighbour_count += cells[i - 1][j + 1]
									if j > 0:
												neighbour_count += cells[i][j - 1]
									if j < len(cells[i]				) - 1:
												neighbour_count += cells[i][j + 1]
									if i < len(lowerCamelCase_				) - 1 and j > 0:
												neighbour_count += cells[i + 1][j - 1]
									if i < len(lowerCamelCase_				) - 1:
												neighbour_count += cells[i + 1][j]
									if i < len(lowerCamelCase_				) - 1 and j < len(cells[i]				) - 1:
												neighbour_count += cells[i + 1][j + 1]

									# Rules of the game of life (excerpt from Wikipedia):
									# 1. Any live cell with two or three live neighbours survives.
									# 2. Any dead cell with three live neighbours becomes a live cell.
									# 3. All other live cells die in the next generation.
									#    Similarly, all other dead cells stay dead.
									__lowercase										=							cells[i][j] == 1
									if (
									    (alive and 2 <= neighbour_count <= 3)
									    or not alive
									    and neighbour_count == 3
									):
												next_generation_row.append(1				)
									else:
												next_generation_row.append(0				)

						next_generation.append(lowerCamelCase_				)
			return next_generation




def    _lowerCAmelCase						(				lowerCamelCase_			:  list[list[int]]		,       lowerCamelCase_			:  int				):
			__lowercase										=							[]
			for _ in range(lowerCamelCase_				):
						# Create output image
						__lowercase										=							Image.new('''RGB'''		,       (len(cells[0]				), len(lowerCamelCase_				))				)
						__lowercase										=							img.load()

						# Save cells to image
						for x in range(len(lowerCamelCase_				)				):
									for y in range(len(cells[0]				)				):
												__lowercase										=							2_5_5 - cells[y][x] * 2_5_5
												__lowercase										=							(colour, colour, colour)

        # Save image
						images.append(lowerCamelCase_				)
						__lowercase										=							new_generation(lowerCamelCase_				)
			return images


if __name__ == "__main__":
	_SCREAMING_SNAKE_CASE					=    generate_images(GLIDER, 1_6)
	images[0].save('''out.gif''', save_all=True, append_images=images[1:])












'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


_SCREAMING_SNAKE_CASE					=    {'''configuration_xglm''': ['''XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XGLMConfig''']}

try:
	if not is_sentencepiece_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_SCREAMING_SNAKE_CASE					=    ['''XGLMTokenizer''']

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_SCREAMING_SNAKE_CASE					=    ['''XGLMTokenizerFast''']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_SCREAMING_SNAKE_CASE					=    [
	    '''XGLM_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''XGLMForCausalLM''',
	    '''XGLMModel''',
	    '''XGLMPreTrainedModel''',
	]


try:
	if not is_flax_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_SCREAMING_SNAKE_CASE					=    [
	    '''FlaxXGLMForCausalLM''',
	    '''FlaxXGLMModel''',
	    '''FlaxXGLMPreTrainedModel''',
	]


try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_SCREAMING_SNAKE_CASE					=    [
	    '''TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''TFXGLMForCausalLM''',
	    '''TFXGLMModel''',
	    '''TFXGLMPreTrainedModel''',
	]


if TYPE_CHECKING:
	from .configuration_xglm import XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP, XGLMConfig

	try:
		if not is_sentencepiece_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_xglm import XGLMTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_xglm_fast import XGLMTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_xglm import XGLM_PRETRAINED_MODEL_ARCHIVE_LIST, XGLMForCausalLM, XGLMModel, XGLMPreTrainedModel

	try:
		if not is_flax_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_flax_xglm import FlaxXGLMForCausalLM, FlaxXGLMModel, FlaxXGLMPreTrainedModel

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_xglm import (
		    TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFXGLMForCausalLM,
		    TFXGLMModel,
		    TFXGLMPreTrainedModel,
		)


else:
	import sys

	_SCREAMING_SNAKE_CASE					=    _LazyModule(__name__, globals()['''__file__'''], _import_structure)





