code: def fp16_to_fp32(val):
      """Convert fp16 `val` to fp32"""
  
      def float_conversion(val):
          val_typecheck = val
          if isinstance(val_typecheck, (Parameter, Variable)):
              val_typecheck = val.data
          if isinstance(val_typecheck, HALF_TYPES):
              val = val.float()
          return val
  
      return conversion_helper(val, float_conversion)
  
imports: import torch
  from torch import nn
  from torch.autograd import Variable
  from torch.nn.parameter import Parameter
  from torch._utils import _flatten_dense_tensors, _unflatten_dense_tensors
  from common.loss_scaler import DynamicLossScaler, LossScaler
label_desc: Use image node_id 3 for calling a global function with example usage: fp16_to_fp32(val) and returns: conversion_helper, val