code: def _fuse_conv_bn_weights(
      conv_w, conv_b, bn_rm, bn_rv, bn_eps, bn_w, bn_b
  ):
      """fuse weights and bias of conv and bn"""
      if conv_b is None:
          conv_b = paddle.zeros_like(bn_rm)
      if bn_w is None:
          bn_w = paddle.ones_like(bn_rm)
      if bn_b is None:
          bn_b = paddle.zeros_like(bn_rm)
      bn_var_rsqrt = paddle.rsqrt(bn_rv + bn_eps)
      conv_w = conv_w * (bn_w * bn_var_rsqrt).reshape(
          [-1] + [1] * (len(conv_w.shape) - 1)
      )
      conv_b = (conv_b - bn_rm) * bn_var_rsqrt * bn_w + bn_b
      return conv_w, conv_b
  
file_path: PaddleDetection/ppdet/utils/fuse_utils.py
imports: import copy
  import paddle
  import paddle.nn
label_desc: Use image node_id 7 for calling a global function with example usage: _fuse_conv_bn_weights(conv_w, conv_b, bn_rm, bn_rv, bn_eps, bn_w, bn_b) and returns: conv_w,  conv_b