parameters: (self, proposals, infos)
return_statement: return torch.cat(z_fts).requires_grad_()
docstring: normalized z coordinate in DeepLesion
docstring_summary: normalized z coordinate in DeepLesion
docstring_tokens: normalized z coordinate in DeepLesion
function: def get_z_ft(self, proposals, infos):
          """normalized z coordinate in DeepLesion"""
          z_fts = []
          for prop, info in zip(proposals, infos):
              z = torch.FloatTensor([info['z_coord']])
              z = z.repeat(len(prop), 1).cuda()
              z_fts.append(z)
          return torch.cat(z_fts).requires_grad_()
function_tokens: def get_z_ft ( self , proposals , infos ) : z_fts = [ ] for prop , info in zip ( proposals , infos ) : z = torch . FloatTensor ( [ info [ 'z_coord' ] ] ) z = z . repeat ( len ( prop ) , 1 ) . cuda ( ) z_fts . append ( z ) return torch . cat ( z_fts ) . requires_grad_ ( )