class_docstr: Test methods of RPN.
class_docstr_tok: ["Test","methods","of","RPN","."]
docstr: Test without augmentation.
  
  Args:
      x (tuple[Tensor]): Features from the upstream network, each is
          a 4D-tensor.
      img_metas (list[dict]): Meta info of each image.
  
  Returns:
      list[Tensor]: Proposals of each image.
docstr_tok: ["Test","without","augmentation",".","Args",":","x","(","tuple","[","Tensor","]",")",":","Features","from","the","upstream","network",",","each","is","a","4D-tensor",".","img_metas","(","list","[","dict","]",")",":","Meta","info","of","each","image",".","Returns",":","list","[","Tensor","]",":","Proposals","of","each","image","."]
code: def simple_test_rpn(self, x, img_metas):
      """Test without augmentation.
  
      Args:
          x (tuple[Tensor]): Features from the upstream network, each is
              a 4D-tensor.
          img_metas (list[dict]): Meta info of each image.
  
      Returns:
          list[Tensor]: Proposals of each image.
      """
      rpn_outs = self(x)
      proposal_list = self.get_bboxes(*rpn_outs, img_metas)
      return proposal_list
  
imports: import sys
  from mmdet.core import merge_aug_proposals
label_desc: Use image node_id 1 for calling the RPNTestMixin obj's underlying member method code with example usage: obj.simple_test_rpn(x, img_metas) and returns: proposal_list