class_docstr: PCB (Part-based Convolutional Baseline), see https://arxiv.org/abs/1711.09349,
  Pyramidal Person Re-IDentification, see https://arxiv.org/abs/1810.12193
  
  Args:
      input_ch (int): Number of channels of the input feature.
      num_stripes (int): Number of sub-parts.
      used_levels (tuple): Whether the level is used, 1 means used.
      num_classes (int): Number of classes for identities, default 751 in
          Market-1501 dataset.
      last_conv_stride (int): Stride of the last conv.
      last_conv_dilation (int): Dilation of the last conv.
      num_conv_out_channels (int): Number of channels of conv feature.
code: def forward(self, x):
      feat = self.base(x)
      assert feat.shape[2] % self.num_stripes == 0
      feat_list, logits_list = self.pyramid_forward(feat)
      feat_out = paddle.concat(feat_list, axis=-1)
      return feat_out
  
file_path: PaddleDetection/ppdet/modeling/reid/pyramidal_embedding.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 paddle.nn.initializer import Normal, Constant
  from paddle import ParamAttr
  from .resnet import ResNet50, ResNet101
  from ppdet.core.workspace import register
label_desc: Use image node_id 4 for calling the PCBPyramid obj's underlying member method code with example usage: obj.forward(x) and returns: feat_out