class_docstr: Decoder of Monodepth2 PoseNet
  
  Parameters
  ----------
  num_ch_enc : list
      The channels number of encoder.
  num_input_features: int
      The number of input sequences. 1 for depth encoder, larger than 1 for pose encoder.
      (Default: 2)
  num_frames_to_predict_for: int
      The number of output pose between frames; If None, it equals num_input_features - 1.
      (Default: 2)
  stride: int
      The stride number for Conv in pose decoder. (Default: 1)
code: def __init__(
      self,
      num_ch_enc,
      num_input_features,
      num_frames_to_predict_for=2,
      stride=1,
  ):
      super(PoseDecoder, self).__init__()
  
      self.num_ch_enc = num_ch_enc
      self.num_input_features = num_input_features
  
      if num_frames_to_predict_for is None:
          num_frames_to_predict_for = num_input_features - 1
      self.num_frames_to_predict_for = num_frames_to_predict_for
  
      self.convs = OrderedDict()
      self.convs[("squeeze")] = nn.Conv2D(
          in_channels=self.num_ch_enc[-1], channels=256, kernel_size=1
      )
      self.convs[("pose", 0)] = nn.Conv2D(
          in_channels=num_input_features * 256,
          channels=256,
          kernel_size=3,
          strides=stride,
          padding=1,
      )
      self.convs[("pose", 1)] = nn.Conv2D(
          in_channels=256,
          channels=256,
          kernel_size=3,
          strides=stride,
          padding=1,
      )
      self.convs[("pose", 2)] = nn.Conv2D(
          in_channels=256,
          channels=6 * num_frames_to_predict_for,
          kernel_size=1,
      )
  
      # register blocks
      for k in self.convs:
          self.register_child(self.convs[k])
      self.net = nn.HybridSequential()
      self.net.add(*list(self.convs.values()))
  
file_path: gluon-cv/gluoncv/model_zoo/monodepthv2/pose_decoder.py
imports: from __future__ import absolute_import, division, print_function
  from collections import OrderedDict
  import mxnet
  import mxnet.gluon.nn
label_desc: Use image node_id 1 to create a new PoseDecoder object from inherited base classes: nn with example: obj = PoseDecoder(num_ch_enc, num_input_features, num_frames_to_predict_for, stride)