




'''simple docstring'''

from __future__ import annotations

from PIL import Image

# Define glider example
a  :				Optional[int]									=  [
    [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
a  :				List[Any]									=  [[0, 1, 0], [0, 1, 0], [0, 1, 0]]


def 		__magic_name__    (	__UpperCAmelCase	)		->					list[list[int]]:

					'''simple docstring'''

					snake_case_									=				[]
					for i in range(len(__UpperCAmelCase	)	):
										snake_case_									=				[]
										for j in range(len(cells[i]	)	):
															# Get the number of live neighbours
															snake_case_									=				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(__UpperCAmelCase	) - 1 and j > 0:
																				neighbour_count += cells[i + 1][j - 1]
															if i < len(__UpperCAmelCase	) - 1:
																				neighbour_count += cells[i + 1][j]
															if i < len(__UpperCAmelCase	) - 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_									=				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(__UpperCAmelCase	)
					return next_generation


def 		__magic_name__    (	__UpperCAmelCase,      __UpperCAmelCase	)		->					list[Image.Image]:

					'''simple docstring'''

					snake_case_									=				[]
					for _ in range(__UpperCAmelCase	):
										# Create output image
										snake_case_									=				Image.new('''RGB''',      (len(cells[0]	), len(__UpperCAmelCase	))	)
										snake_case_									=				img.load()

										# Save cells to image
										for x in range(len(__UpperCAmelCase	)	):
															for y in range(len(cells[0]	)	):
																				snake_case_									=				255 - cells[y][x] * 255
																				snake_case_									=				(colour, colour, colour)

        # Save image
										images.append(__UpperCAmelCase	)
										snake_case_									=				new_generation(__UpperCAmelCase	)
					return images


if __name__ == "__main__":
							a  :				Dict									=  generate_images(GLIDER, 16)
							images[0].save('out.gif', save_all=True, append_images=images[1:])





'''simple docstring'''



import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
      from .tokenization_xlnet import XLNetTokenizer
else:
      A__		:					Dict												=  None


A__		:					List[Any]												=  logging.get_logger(__name__)

A__		:					str												=  {"""vocab_file""": """spiece.model""", """tokenizer_file""": """tokenizer.json"""}

A__		:					Union[str, Any]												=  {
    """vocab_file""": {
        """xlnet-base-cased""": """https://huggingface.co/xlnet-base-cased/resolve/main/spiece.model""",
        """xlnet-large-cased""": """https://huggingface.co/xlnet-large-cased/resolve/main/spiece.model""",
    },
    """tokenizer_file""": {
        """xlnet-base-cased""": """https://huggingface.co/xlnet-base-cased/resolve/main/tokenizer.json""",
        """xlnet-large-cased""": """https://huggingface.co/xlnet-large-cased/resolve/main/tokenizer.json""",
    },
}

A__		:					Any												=  {
    """xlnet-base-cased""": None,
    """xlnet-large-cased""": None,
}

A__		:					Dict												=  """▁"""

# Segments (not really needed)
A__		:					List[str]												=  0
A__		:					List[Any]												=  1
A__		:					Union[str, Any]												=  2
A__		:					List[Any]												=  3
A__		:					str												=  4





class    UpperCAmelCase_  (_UpperCAmelCase  ):





    """simple docstring"""






    lowerCamelCase  :					str							     =			VOCAB_FILES_NAMES
    lowerCamelCase  :					Dict							     =			PRETRAINED_VOCAB_FILES_MAP
    lowerCamelCase  :					Tuple							     =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    lowerCamelCase  :					List[Any]							     =			'left'
    lowerCamelCase  :					Optional[Any]							     =			XLNetTokenizer







    def __init__(							self			,     SCREAMING_SNAKE_CASE_=None			,     SCREAMING_SNAKE_CASE_=None			,     SCREAMING_SNAKE_CASE_=False			,     SCREAMING_SNAKE_CASE_=True			,     SCREAMING_SNAKE_CASE_=False			,     SCREAMING_SNAKE_CASE_="<s>"			,     SCREAMING_SNAKE_CASE_="</s>"			,     SCREAMING_SNAKE_CASE_="<unk>"			,     SCREAMING_SNAKE_CASE_="<sep>"			,     SCREAMING_SNAKE_CASE_="<pad>"			,     SCREAMING_SNAKE_CASE_="<cls>"			,     SCREAMING_SNAKE_CASE_="<mask>"			,     SCREAMING_SNAKE_CASE_=["<eop>", "<eod>"]			,     **SCREAMING_SNAKE_CASE_			,     )				->     Union[str, Any]:
         # Mask token behave like a normal word, i.e. include the space before it
         __lowerCamelCase   :	str								=		AddedToken(SCREAMING_SNAKE_CASE_			,     lstrip=SCREAMING_SNAKE_CASE_			,     rstrip=SCREAMING_SNAKE_CASE_	) if isinstance(SCREAMING_SNAKE_CASE_			,     SCREAMING_SNAKE_CASE_	) else mask_token

         super().__init__(
             vocab_file=SCREAMING_SNAKE_CASE_			,     tokenizer_file=SCREAMING_SNAKE_CASE_			,     do_lower_case=SCREAMING_SNAKE_CASE_			,     remove_space=SCREAMING_SNAKE_CASE_			,     keep_accents=SCREAMING_SNAKE_CASE_			,     bos_token=SCREAMING_SNAKE_CASE_			,     eos_token=SCREAMING_SNAKE_CASE_			,     unk_token=SCREAMING_SNAKE_CASE_			,     sep_token=SCREAMING_SNAKE_CASE_			,     pad_token=SCREAMING_SNAKE_CASE_			,     cls_token=SCREAMING_SNAKE_CASE_			,     mask_token=SCREAMING_SNAKE_CASE_			,     additional_special_tokens=SCREAMING_SNAKE_CASE_			,     **SCREAMING_SNAKE_CASE_			,     )

         __lowerCamelCase   :	Union[str, Any]								=		3
         __lowerCamelCase   :	int								=		do_lower_case
         __lowerCamelCase   :	Optional[Any]								=		remove_space
         __lowerCamelCase   :	int								=		keep_accents
         __lowerCamelCase   :	Any								=		vocab_file
         __lowerCamelCase   :	Any								=		False if not self.vocab_file else True







    def       lowercase_				(							self			,     SCREAMING_SNAKE_CASE_			,     SCREAMING_SNAKE_CASE_ = None	)				->     List[int]:
         __lowerCamelCase   :	Optional[Any]								=		[self.sep_token_id]
         __lowerCamelCase   :	Any								=		[self.cls_token_id]
         if token_ids_a is None:
              return token_ids_a + sep + cls
         return token_ids_a + sep + token_ids_a + sep + cls







    def       lowercase_				(							self			,     SCREAMING_SNAKE_CASE_			,     SCREAMING_SNAKE_CASE_ = None	)				->     List[int]:
         __lowerCamelCase   :	int								=		[self.sep_token_id]
         __lowerCamelCase   :	Dict								=		[2]

         if token_ids_a is None:
              return len(token_ids_a + sep	) * [0] + cls_segment_id
         return len(token_ids_a + sep	) * [0] + len(token_ids_a + sep	) * [1] + cls_segment_id







    def       lowercase_				(							self			,     SCREAMING_SNAKE_CASE_			,     SCREAMING_SNAKE_CASE_ = None	)				->     Tuple[str]:
         if not self.can_save_slow_tokenizer:
              raise ValueError(
                  'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '
                  'tokenizer.'	)

         if not os.path.isdir(SCREAMING_SNAKE_CASE_	):
              logger.error(f'Vocabulary path ({save_directory}) should be a directory'	)
              return
         __lowerCamelCase   :	Tuple								=		os.path.join(
             SCREAMING_SNAKE_CASE_			,     (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']	)

         if os.path.abspath(self.vocab_file	) != os.path.abspath(SCREAMING_SNAKE_CASE_	):
              copyfile(self.vocab_file			,     SCREAMING_SNAKE_CASE_	)

         return (out_vocab_file,)






