code: def _save_weight_qparams(
      destination,
      prefix,
      weight_qscheme,
      weight_dtype,
      weight_scale,
      weight_zero_point,
      weight_axis,
  ):
      destination[prefix + "weight_qscheme"] = weight_qscheme
      destination[prefix + "weight_dtype"] = weight_dtype
      if weight_qscheme is not None:
          destination[prefix + "weight_scale"] = weight_scale
          destination[prefix + "weight_zero_point"] = weight_zero_point
          if weight_qscheme == torch.per_channel_affine:
              destination[prefix + "weight_axis"] = weight_axis
  
file_path: pytorch/torch/ao/nn/quantized/reference/modules/utils.py
imports: import torch
  import typing
label_desc: Use image node_id 6 for calling a global function with example usage: _save_weight_qparams(destination, prefix, weight_qscheme, weight_dtype, weight_scale, weight_zero_point, weight_axis) without return types