code: def triplet_margin_loss(
      anchor: TensorLikeType,
      positive: TensorLikeType,
      negative: TensorLikeType,
      margin: float = 1.0,
      p: float = 2,
      eps: float = 1e-6,
      swap: bool = False,
      size_average: Optional[bool] = None,
      reduce: Optional[bool] = None,
      reduction: str = "mean",
  ) -> TensorLikeType:
      if size_average is not None or reduce is not None:
          # TODO: Raise exception instead of converting value.  This is only for
          # primTorch since it can drop support for deprecated arguments.
          # msg = "size_average and reduce args are deprecated, please use reduction argument."
          reduction = _get_string_reduction_arg(
              size_average=size_average, reduce=reduce
          )
  
      # torch.nn.functional.triplet_margin_with_distance_loss has no ref defined
      # since it's a pure Python implementation.  Use this helper instead.
      return _triplet_margin_with_distance_loss(
          anchor=anchor,
          positive=positive,
          negative=negative,
          distance_function=lambda x, y: torch.pairwise_distance(
              x, y, p, eps
          ),
          margin=margin,
          swap=swap,
          reduction=reduction,
      )
  
imports: import math
  from functools import wraps
  from typing import Callable, Optional, Union
  import torch
  import torch._prims
  import torch._prims_common
  import torch._refs
  from torch._decomp import register_decomposition
  from torch._prims_common import ELEMENTWISE_TYPE_PROMOTION_KIND, NumberType, ShapeType, TensorLike, TensorLikeType
  from torch._prims_common.wrappers import elementwise_type_promotion_wrapper, elementwise_unary_scalar_wrapper, out_wrapper
  from torch._refs import _make_inplace
label_desc: Use image node_id 33 for calling a global function with example usage: triplet_margin_loss(anchor, positive, negative, margin, p, eps, swap, size_average, reduce, reduction) and returns: _triplet_margin_with_distance_loss