






'''simple docstring'''
from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__magic_name__		:     Optional[Any]					=    logging.get_logger(__name__)

__magic_name__		:     str					=    {
    '''google/bigbird-roberta-base''': '''https://huggingface.co/google/bigbird-roberta-base/resolve/main/config.json''',
    '''google/bigbird-roberta-large''': '''https://huggingface.co/google/bigbird-roberta-large/resolve/main/config.json''',
    '''google/bigbird-base-trivia-itc''': '''https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/config.json''',
    # See all BigBird models at https://huggingface.co/models?filter=big_bird
}







class 	UpperCamelCase__					(     __SCREAMING_SNAKE_CASE			):

		"""simple docstring"""
		UpperCAmelCase__     			=						'big_bird'




		def __init__( self						:						Dict							,    __A						:						List[Any]=5_0_3_5_8							,    __A						:						List[Any]=7_6_8							,    __A						:						Optional[Any]=1_2							,    __A						:						Tuple=1_2							,    __A						:						Tuple=3_0_7_2							,    __A						:						List[str]="gelu_new"							,    __A						:						Optional[int]=0.1							,    __A						:						List[Any]=0.1							,    __A						:						Optional[int]=4_0_9_6							,    __A						:						List[Any]=2							,    __A						:						str=0.0_2							,    __A						:						Any=1e-12							,    __A						:						List[str]=True							,    __A						:						Optional[Any]=0							,    __A						:						int=1							,    __A						:						Tuple=2							,    __A						:						List[Any]=6_6							,    __A						:						int="block_sparse"							,    __A						:						Optional[int]=True							,    __A						:						Union[str, Any]=False							,    __A						:						Optional[Any]=6_4							,    __A						:						Optional[int]=3							,    __A						:						Any=None							,    **__A						:						Dict							,    ):







							"""simple docstring"""
							super().__init__(
							    pad_token_id=UpperCamelCase__							,    bos_token_id=UpperCamelCase__							,    eos_token_id=UpperCamelCase__							,    sep_token_id=UpperCamelCase__							,    **UpperCamelCase__							,    )

							_lowercase			= vocab_size
							_lowercase			= max_position_embeddings
							_lowercase			= hidden_size
							_lowercase			= num_hidden_layers
							_lowercase			= num_attention_heads
							_lowercase			= intermediate_size
							_lowercase			= hidden_act
							_lowercase			= hidden_dropout_prob
							_lowercase			= attention_probs_dropout_prob
							_lowercase			= initializer_range
							_lowercase			= type_vocab_size
							_lowercase			= layer_norm_eps
							_lowercase			= use_cache

							_lowercase			= rescale_embeddings
							_lowercase			= attention_type
							_lowercase			= use_bias
							_lowercase			= block_size
							_lowercase			= num_random_blocks
							_lowercase			= classifier_dropout







class 	UpperCamelCase__					(     __SCREAMING_SNAKE_CASE			):

		"""simple docstring"""




		@property
		def       snake_case     ( self						:						Optional[Any]    ):







							"""simple docstring"""







							if self.task == "multiple-choice":
												_lowercase			= {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
							else:
												_lowercase			= {0: '''batch''', 1: '''sequence'''}
							return OrderedDict(
							    [
							        ("input_ids", dynamic_axis),
							        ("attention_mask", dynamic_axis),
							    ]    )



'''simple docstring'''
from __future__ import annotations

from PIL import Image

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




def    _UpperCamelCase						(       SCREAMING_SNAKE_CASE__			)  ->							list[list[int]]:


		'''simple docstring'''


		snake_case  :       Optional[Any]     			=						[]
		for i in range(len(SCREAMING_SNAKE_CASE__			)			):
				snake_case  :       str     			=						[]
				for j in range(len(cells[i]			)			):
						# Get the number of live neighbours
						snake_case  :       Any     			=						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(SCREAMING_SNAKE_CASE__			) - 1 and j > 0:
								neighbour_count += cells[i + 1][j - 1]
						if i < len(SCREAMING_SNAKE_CASE__			) - 1:
								neighbour_count += cells[i + 1][j]
						if i < len(SCREAMING_SNAKE_CASE__			) - 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.
						snake_case  :       List[Any]     			=						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(SCREAMING_SNAKE_CASE__			)
		return next_generation




def    _UpperCamelCase						(       SCREAMING_SNAKE_CASE__ ,       SCREAMING_SNAKE_CASE__			)  ->							list[Image.Image]:


		'''simple docstring'''


		snake_case  :       Tuple     			=						[]
		for _ in range(SCREAMING_SNAKE_CASE__			):
				# Create output image
				snake_case  :       List[Any]     			=						Image.new('''RGB''' ,       (len(cells[0]			), len(SCREAMING_SNAKE_CASE__			))			)
				snake_case  :       Optional[Any]     			=						img.load()

				# Save cells to image
				for x in range(len(SCREAMING_SNAKE_CASE__			)			):
						for y in range(len(cells[0]			)			):
								snake_case  :       str     			=						255 - cells[y][x] * 255
								snake_case  :       List[str]     			=						(colour, colour, colour)

        # Save image
				images.append(SCREAMING_SNAKE_CASE__			)
				snake_case  :       Dict     			=						new_generation(SCREAMING_SNAKE_CASE__			)
		return images


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


