code: def __new__(
      cls,
      values,
      offsets,
      *,
      lengths=None,
      **kwargs,
  ):
      ks = DispatchKeySet(DispatchKey.NestedTensor)
      ks = ks.add(DispatchKey.AutogradNestedTensor)
      r = torch.Tensor._make_wrapper_subclass(  # type: ignore[attr-defined]
          cls,
          (0,),
          (0,),
          0,
          torch.contiguous_format,
          values.dtype,
          torch.jagged,
          values.device,
          False,
          kwargs.get("requires_grad", False),
          "sizes",
          False,
          True,  # dispatch_layout
          ks,
      )
      return r
  
imports: from typing import Tuple
  import torch
  from torch._C import DispatchKey, DispatchKeySet
  from torch._prims_common import is_expandable_to
  from torch.fx.experimental.symbolic_shapes import has_free_symbols
  from torch.utils.weak import WeakTensorKeyDictionary
  from typing import *
label_desc: Use image node_id 1 for calling the NestedTensor obj's underlying member method code with example usage: obj.__new__(cls, values, offsets) and returns: r