




'''simple docstring'''





def SCREAMING_SNAKE_CASE       ( lowercase_		)     -> List[str]:



       """simple docstring"""

       if not head:
              return True
       # split the list to two parts
       A__				,							A__   				=					head.next, head
       while fast and fast.next:
              A__   				=					fast.next.next
              A__   				=					slow.next
       A__   				=					slow.next
       A__   				=					None  # Don't forget here! But forget still works!
       # reverse the second part
       A__   				=					None
       while second:
              A__   				=					second.next
              A__   				=					node
              A__   				=					second
              A__   				=					nxt
       # compare two parts
       # second part has the same or one less node
       while node:
              if node.val != head.val:
                     return False
              A__   				=					node.next
              A__   				=					head.next
       return True







def SCREAMING_SNAKE_CASE       ( lowercase_		)     -> str:



       """simple docstring"""

       if not head or not head.next:
              return True

       # 1. Get the midpoint (slow)
       A__   				=					A__   				=					A__   				=					head
       while fast and fast.next:
              A__				,							A__   				=					fast.next.next, slow.next

       # 2. Push the second half into the stack
       A__   				=					[slow.val]
       while slow.next:
              A__   				=					slow.next
              stack.append(slow.val		)

       # 3. Comparison
       while stack:
              if stack.pop() != cur.val:
                     return False
              A__   				=					cur.next

       return True







def SCREAMING_SNAKE_CASE       ( lowercase_		)     -> Optional[int]:



       """simple docstring"""

       if not head or not head.next:
              return True
       A__   				=					{}
       A__   				=					0
       while head:
              if head.val in d:
                     d[head.val].append(lowercase_		)
              else:
                     A__   				=					[pos]
              A__   				=					head.next
              pos += 1
       A__   				=					pos - 1
       A__   				=					0
       for v in d.values():
              if len(lowercase_		) % 2 != 0:
                     middle += 1
              else:
                     A__   				=					0
                     for i in range(0				,       len(lowercase_		)		):
                            if v[i] + v[len(lowercase_		) - 1 - step] != checksum:
                                   return False
                            step += 1
              if middle > 1:
                     return False
       return True








import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device


if is_torch_available():
  from transformers import AutoModelForSeqaSeqLM, AutoTokenizer


@require_torch
@require_sentencepiece
@require_tokenizers
class        UpperCamelCase_					(				unittest.TestCase  ):

    '''simple docstring'''






    @slow
    def  SCREAMING_SNAKE_CASE							(    self   :			Optional[Any])		->Any:





           '''simple docstring'''

           A__   				=					AutoModelForSeqaSeqLM.from_pretrained('''google/mt5-small'''      ,				return_dict=UpperCAmelCase__).to(UpperCAmelCase__)
           A__   				=					AutoTokenizer.from_pretrained('''google/mt5-small''')

           A__   				=					tokenizer('''Hello there'''      ,				return_tensors='''pt''').input_ids
           A__   				=					tokenizer('''Hi I am'''      ,				return_tensors='''pt''').input_ids

           A__   				=					model(input_ids.to(UpperCAmelCase__)      ,				labels=labels.to(UpperCAmelCase__)).loss
           A__   				=					-(labels.shape[-1] * loss.item())

           A__   				=					-84.9127
           self.assertTrue(abs(mtf_score - EXPECTED_SCORE) < 1e-4)


