code: def convert_weights(model: paddle.nn.Layer):
      """Convert applicable model parameters to fp16"""
  
      def _convert_weights_to_fp16(param):
          if isinstance(
              param,
              (paddle.nn.Conv1D, paddle.nn.Conv2D, paddle.nn.Linear),
          ):
              param.weight.data = param.weight.astype("float16")
              if param.bias is not None:
                  param.bias.data = param.bias.astype("float16")
          if isinstance(param, paddle.nn.MultiHeadAttention):
              for attr in [
                  *[f"{s}_proj_weight" for s in ["in", "q", "k", "v"]],
                  "in_proj_bias",
                  "bias_k",
                  "bias_v",
              ]:
                  tensor_l = getattr(param, attr)
                  if tensor_l is not None:
                      tensor_l.data = tensor_l.astype("float16")
          for name in ["text_projection", "proj"]:
              if hasattr(param, name):
                  attr = getattr(param, name)
                  if attr is not None:
                      attr.data = attr.astype("float16")
  
      model.apply(fn=_convert_weights_to_fp16)
  
imports: from collections import OrderedDict
  from typing import Tuple, Union
  import numpy
  import paddle
  from paddle.nn.initializer import Constant
  from paddle.vision.transforms import Compose, Resize, CenterCrop, ToTensor, Normalize
label_desc: Use image node_id 1 for calling a global function with example usage: convert_weights(model) without return types