class_docstr: Clip bounding box to image edges.
  
  Parameters
  ----------
  axis : int
      The coordinate axis with length 4.
docstr: Clip box with shape inferred from image.
docstr_tok: ["Clip","box","with","shape","inferred","from","image","."]
code: def forward(self, is_train, req, in_data, out_data, aux):
      """Clip box with shape inferred from image."""
      x = in_data[0]
      shape_like = in_data[1]
      height, width = shape_like.shape[-2:]
      assert x.shape[self.axis] == 4
      xmin, ymin, xmax, ymax = x.split(axis=self.axis, num_outputs=4)
      xmin = xmin.clip(0, width - 1)
      ymin = ymin.clip(0, height - 1)
      xmax = xmax.clip(0, width - 1)
      ymax = ymax.clip(0, height - 1)
      out = mx.nd.concat(xmin, ymin, xmax, ymax, dim=self.axis)
      self.assign(out_data[0], req[0], out)
  
file_path: gluon-cv/gluoncv/model_zoo/rcnn/rpn/bbox_clip.py
imports: import mxnet
label_desc: Use image node_id 2 for calling the BBoxClipToImage obj's underlying member method code with example usage: obj.forward(is_train, req, in_data, out_data, aux) without return types