


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










from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a__: List[Any]							   =						{
    'configuration_x_clip': [
        'XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'XCLIPConfig',
        'XCLIPTextConfig',
        'XCLIPVisionConfig',
    ],
    'processing_x_clip': ['XCLIPProcessor'],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       a__: Any							   =						[
           'XCLIP_PRETRAINED_MODEL_ARCHIVE_LIST',
           'XCLIPModel',
           'XCLIPPreTrainedModel',
           'XCLIPTextModel',
           'XCLIPVisionModel',
       ]

if TYPE_CHECKING:
       from .configuration_x_clip import (
           XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
           XCLIPConfig,
           XCLIPTextConfig,
           XCLIPVisionConfig,
       )
       from .processing_x_clip import XCLIPProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_x_clip import (
                  XCLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
                  XCLIPModel,
                  XCLIPPreTrainedModel,
                  XCLIPTextModel,
                  XCLIPVisionModel,
              )

else:
       import sys

       a__: Optional[Any]							   =						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





