code: def test_overflow(x: torch.Tensor):
      "Tests whether fp16 gradients have overflown."
      s = float(x.float().sum())
      return s == float("inf") or s == float("-inf") or s != s
  
imports: from __future__ import annotations
  from ..basics import *
  from .progress import *
  from torch.cuda.amp import GradScaler, autocast
  from torch.cuda.amp.grad_scaler import OptState
  from ..fp16_utils import convert_network, model_grads_to_master_grads, master_params_to_model_params
  from torch.nn.utils import parameters_to_vector
label_desc: Use image node_id 7 for calling a global function with example usage: test_overflow(x) and returns: unknown