docstr: Modified from METRO network, see https://arxiv.org/abs/2012.09760
  
  Args:
      backbone (nn.Layer): backbone instance
docstr_tok: ["Modified","from","METRO","network",",","see","https",":","\/\/arxiv.org\/abs\/2012.09760","Args",":","backbone","(","nn.Layer",")",":","backbone","instance"]
code: def __init__(
      self,
      num_joints,
      backbone="HRNet",
      trans_encoder="",
      loss="Pose3DLoss",
  ):
      """
      Modified from METRO network, see https://arxiv.org/abs/2012.09760
  
      Args:
          backbone (nn.Layer): backbone instance
      """
      super(METRO_Body, self).__init__()
      self.num_joints = num_joints
      self.backbone = backbone
      self.loss = loss
      self.deploy = False
  
      self.trans_encoder = trans_encoder
      self.conv_learn_tokens = paddle.nn.Conv1D(49, num_joints + 10, 1)
      self.cam_param_fc = paddle.nn.Linear(3, 2)
  
file_path: PaddleDetection/ppdet/modeling/architectures/pose3d_metro.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from ppdet.core.workspace import register, create
  from .meta_arch import BaseArch
  from ..None import layers
label_desc: Use image node_id 1 to create a new METRO_Body object from inherited base classes: BaseArch with example: obj = METRO_Body(num_joints, backbone, trans_encoder, loss)