

import tempfile
import unittest

from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from transformers.testing_utils import (
    is_torch_available,
    require_optimum,
    require_torch,
    slow,
)


if is_torch_available():
					import torch





@require_torch
@require_optimum
@slow
class 	snake_case_   (		unittest.TestCase					):







			'''simple docstring'''

			def 				snake_case__(     self :				Optional[Any]							)      ->Tuple:
									snake_case_   =	'''hf-internal-testing/tiny-random-t5'''
									snake_case_   =	AutoTokenizer.from_pretrained(_UpperCamelCase							)
									snake_case_   =	AutoModelForSeqaSeqLM.from_pretrained(_UpperCamelCase							)

									snake_case_   =	tokenizer('''This is me'''							,   return_tensors='''pt'''							)

									snake_case_   =	model.to_bettertransformer()

									self.assertTrue(any('''BetterTransformer''' in mod.__class__.__name__ for _, mod in model.named_modules()							)							)

									snake_case_   =	model.generate(**_UpperCamelCase							)

									snake_case_   =	model.reverse_bettertransformer()

									self.assertFalse(any('''BetterTransformer''' in mod.__class__.__name__ for _, mod in model.named_modules()							)							)

									with tempfile.TemporaryDirectory() as tmpdirname:
															model.save_pretrained(_UpperCamelCase							)

															snake_case_   =	AutoModelForSeqaSeqLM.from_pretrained(_UpperCamelCase							)

															self.assertFalse(
															    any('''BetterTransformer''' in mod.__class__.__name__ for _, mod in model_reloaded.named_modules()							)							)

															snake_case_   =	model_reloaded.generate(**_UpperCamelCase							)
															self.assertTrue(torch.allclose(_UpperCamelCase							,   _UpperCamelCase							)							)







			def 				snake_case__(     self :				List[Any]							)      ->str:
									snake_case_   =	'''hf-internal-testing/tiny-random-t5'''
									snake_case_   =	AutoModelForSeqaSeqLM.from_pretrained(_UpperCamelCase							)

									snake_case_   =	model.to_bettertransformer()

									with tempfile.TemporaryDirectory() as tmpdirname:
															with self.assertRaises(_UpperCamelCase							):
																					model.save_pretrained(_UpperCamelCase							)

															snake_case_   =	model.reverse_bettertransformer()
															model.save_pretrained(_UpperCamelCase							)


from __future__ import annotations


def   __SCREAMING_SNAKE_CASE					(SCREAMING_SNAKE_CASE__       ):
						snake_case_   =	len(SCREAMING_SNAKE_CASE__       )
						# We need to create solution object to save path.
						snake_case_   =	[[0 for _ in range(SCREAMING_SNAKE_CASE__       )] for _ in range(SCREAMING_SNAKE_CASE__       )]
						snake_case_   =	run_maze(SCREAMING_SNAKE_CASE__  ,		0  ,		0  ,		SCREAMING_SNAKE_CASE__       )
						if solved:
												print('''\n'''.join(str(SCREAMING_SNAKE_CASE__       ) for row in solutions       )       )
						else:
												print('''No solution exists!'''       )
						return solved


def   __SCREAMING_SNAKE_CASE					(SCREAMING_SNAKE_CASE__  ,		SCREAMING_SNAKE_CASE__  ,		SCREAMING_SNAKE_CASE__  ,		SCREAMING_SNAKE_CASE__       ):
						snake_case_   =	len(SCREAMING_SNAKE_CASE__       )
						# Final check point.
						if i == j == (size - 1):
												snake_case_   =	1
												return True

						snake_case_   =	(not i < 0) and (not j < 0)  # Check lower bounds
						snake_case_   =	(i < size) and (j < size)  # Check upper bounds

						if lower_flag and upper_flag:
												# check for already visited and block points.
												snake_case_   =	(not solutions[i][j]) and (not maze[i][j])
												if block_flag:
																		# check visited
																		snake_case_   =	1

																		# check for directions
																		if (
																		    run_maze(SCREAMING_SNAKE_CASE__  ,		i + 1  ,		SCREAMING_SNAKE_CASE__  ,		SCREAMING_SNAKE_CASE__       )
																		    or run_maze(SCREAMING_SNAKE_CASE__  ,		SCREAMING_SNAKE_CASE__  ,		j + 1  ,		SCREAMING_SNAKE_CASE__       )
																		    or run_maze(SCREAMING_SNAKE_CASE__  ,		i - 1  ,		SCREAMING_SNAKE_CASE__  ,		SCREAMING_SNAKE_CASE__       )
																		    or run_maze(SCREAMING_SNAKE_CASE__  ,		SCREAMING_SNAKE_CASE__  ,		j - 1  ,		SCREAMING_SNAKE_CASE__       )
																		):
																								return True

																		snake_case_   =	0
																		return False
						return False


if __name__ == "__main__":
					import doctest

					doctest.testmod()