code: def convert_to_deploy(self):
      if not hasattr(self, "conv1"):
          self.conv1 = nn.Conv2D(
              in_channels=self.ch_in,
              out_channels=self.ch_in,
              kernel_size=self.kernel_size,
              stride=self.stride,
              padding=self.padding,
              groups=self.ch_in,
              bias_attr=ParamAttr(
                  initializer=Constant(value=0.0), learning_rate=1.0
              ),
          )
      if not hasattr(self, "conv2"):
          self.conv2 = nn.Conv2D(
              in_channels=self.ch_in,
              out_channels=self.ch_out,
              kernel_size=1,
              stride=1,
              padding="SAME",
              groups=1,
              bias_attr=ParamAttr(
                  initializer=Constant(value=0.0), learning_rate=1.0
              ),
          )
  
      (
          conv1_kernel,
          conv1_bias,
          conv2_kernel,
          conv2_bias,
      ) = self.get_equivalent_kernel_bias()
      self.conv1.weight.set_value(conv1_kernel)
      self.conv1.bias.set_value(conv1_bias)
      self.conv2.weight.set_value(conv2_kernel)
      self.conv2.bias.set_value(conv2_bias)
      self.__delattr__("depth_conv")
      self.__delattr__("point_conv")
      self.__delattr__("rbr_1x1")
      if hasattr(self, "rbr_identity_st1"):
          self.__delattr__("rbr_identity_st1")
      if hasattr(self, "rbr_identity_st2"):
          self.__delattr__("rbr_identity_st2")
  
file_path: PaddleDetection/ppdet/modeling/backbones/mobileone.py
imports: import paddle
  import paddle.nn
  from paddle import ParamAttr
  from paddle.regularizer import L2Decay
  from paddle.nn.initializer import Normal, Constant
  from ppdet.modeling.ops import get_act_fn
  from ppdet.modeling.layers import ConvNormLayer
label_desc: Use image node_id 3 for calling the MobileOneBlock obj's underlying member method code with example usage: obj.convert_to_deploy() without return types