"""simple docstring"""


from typing import Any




class  UpperCamelCase					:







       def __init__( self,							lowerCAmelCase__)      ->      str:
            snake_case_					       =					data
            snake_case_					       =					None




class  UpperCamelCase					:







       def __init__( self)      ->      Any:
            snake_case_					       =					None







       def 		a_						( self)      ->      Tuple:
            snake_case_					       =					self.head
            while temp is not None:
                 print(temp.data,							end=' ')
                 snake_case_					       =					temp.next
            print()







       def 		a_						( self,							lowerCAmelCase__)      ->      Any:
            snake_case_					       =					Node(lowerCAmelCase__)
            snake_case_					       =					self.head
            snake_case_					       =					new_node







       def 		a_						( self,							lowerCAmelCase__,							lowerCAmelCase__)      ->      Optional[int]:
            if node_data_a == node_data_a:
                 return
            else:
                 snake_case_					       =					self.head
                 while node_a is not None and node_a.data != node_data_a:
                      snake_case_					       =					node_a.next

                 snake_case_					       =					self.head
                 while node_a is not None and node_a.data != node_data_a:
                      snake_case_					       =					node_a.next

                 if node_a is None or node_a is None:
                      return

                 snake_case_       ,	snake_case_					       =					node_a.data, node_a.data


if __name__ == "__main__":
    __UpperCamelCase									=			LinkedList()
    for i in range(5, 0, -1):
        ll.push(i)

    ll.print_list()

    ll.swap_nodes(1, 4)
    print('''After swapping''')
    ll.print_list()






"""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 			A__   (  unittest.TestCase							):




	'''simple docstring'''





	@slow
	def 							_SCREAMING_SNAKE_CASE   (     self:		Union[str, Any])				->       str:

				"""simple docstring"""

				__lowerCAmelCase      :  Optional[Any]												=       FlaxMTaForConditionalGeneration.from_pretrained("google/mt5-small")
				__lowerCAmelCase      :  Optional[Any]												=       AutoTokenizer.from_pretrained("google/mt5-small")

				__lowerCAmelCase      :  Tuple												=       tokenizer("Hello there"       ,			return_tensors="np").input_ids
				__lowerCAmelCase      :  Dict												=       tokenizer("Hi I am"       ,			return_tensors="np").input_ids

				__lowerCAmelCase      :  str												=       shift_tokens_right(_SCREAMING_SNAKE_CASE       ,			model.config.pad_token_id       ,			model.config.decoder_start_token_id)

				__lowerCAmelCase      :  Optional[int]												=       model(_SCREAMING_SNAKE_CASE       ,			decoder_input_ids=_SCREAMING_SNAKE_CASE).logits
				__lowerCAmelCase      :  int												=       optax.softmax_cross_entropy(_SCREAMING_SNAKE_CASE       ,			onehot(_SCREAMING_SNAKE_CASE       ,			logits.shape[-1])).mean()

				__lowerCAmelCase      :  List[str]												=       -(labels.shape[-1] * loss.item())

				__lowerCAmelCase      :  str												=       -84.9127
				self.assertTrue(abs(mtf_score - EXPECTED_SCORE) < 1e-4)