code: def log_ndtr(a: TensorLikeType) -> TensorLikeType:
      # Note: M_SQRT1_2 is the value of 1 / √2
      M_SQRT1_2 = 0.707106781186547524400844362104849039
      t = a * M_SQRT1_2
      return torch.where(
          a < 1.0,
          torch.log(torch.special.erfcx(-t) / 2) - t * t,
          torch.log1p(-torch.erfc(t) / 2),
      )
  
imports: import math
  from typing import Optional, Union
  import torch
  import torch._prims
  import torch._prims_common
  import torch._refs
  from torch import Tensor
  from torch._decomp import register_decomposition
  from torch._prims_common import ELEMENTWISE_TYPE_PROMOTION_KIND, Number, NumberType, TensorLike, TensorLikeType
  from torch._prims_common.wrappers import elementwise_type_promotion_wrapper, out_wrapper
  from torch._refs import _make_alias, _make_elementwise_binary_reference, _make_elementwise_unary_reference
label_desc: Use image node_id 8 for calling a global function with example usage: log_ndtr(a) and returns: torch