

'''simple docstring'''






import unittest

from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow


if is_flax_available():
 import optax
 from flax.training.common_utils import onehot

 from transformers import AutoTokenizer, FlaxMTaForConditionalGeneration
 from transformers.models.ta.modeling_flax_ta import shift_tokens_right






@require_torch
@require_sentencepiece
@require_tokenizers
@require_flax
class 			lowercase_	(unittest.TestCase      ):




  """simple docstring"""




  @slow
  def 					SCREAMING_SNAKE_CASE      (      self   :     Any			):
   __lowercase							  = FlaxMTaForConditionalGeneration.from_pretrained('''google/mt5-small'''			)
   __lowercase							  = AutoTokenizer.from_pretrained('''google/mt5-small'''			)

   __lowercase							  = tokenizer('''Hello there'''					,return_tensors='''np'''			).input_ids
   __lowercase							  = tokenizer('''Hi I am'''					,return_tensors='''np'''			).input_ids

   __lowercase							  = shift_tokens_right(lowercase__					,model.config.pad_token_id					,model.config.decoder_start_token_id			)

   __lowercase							  = model(lowercase__					,decoder_input_ids=lowercase__			).logits
   __lowercase							  = optax.softmax_cross_entropy(lowercase__					,onehot(lowercase__					,logits.shape[-1]			)			).mean()

   __lowercase							  = -(labels.shape[-1] * loss.item())

   __lowercase							  = -8_4.9_1_2_7
   self.assertTrue(abs(mtf_score - EXPECTED_SCORE			) < 1e-4			)




'''simple docstring'''






from __future__ import annotations


def 		_A     (    A__      ):






 """simple docstring"""



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


def 		_A     (    A__     ,				A__     ,				A__     ,				A__      ):






 """simple docstring"""



 __lowercase							  = len(A__      )
 # Final check point.
 if i == j == (size - 1):
  __lowercase							  = 1
  return True

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

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

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

   __lowercase							  = 0
   return False
 return False


if __name__ == "__main__":
 import doctest

 doctest.testmod()

