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Traceback (most recent call last):
File "./examples/slam_demo.py", line 200, in
run(args)
File "./examples/slam_demo.py", line 143, in run
slam_module.spin() # visualizer should be the main spin, but pytorch has a memory bug/leak if threaded...
File "/home/user/linzejun01/linzejun_mutiply_view01/NeRF-SLAM/./examples/../pipeline/pipeline_module.py", line 101, in spin
output = self.spin_once(input);
File "/home/user/linzejun01/linzejun_mutiply_view01/NeRF-SLAM/./examples/../slam/slam_module.py", line 11, in spin_once
output = self.slam(input)
File "/home/user/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "/home/user/linzejun01/linzejun_mutiply_view01/NeRF-SLAM/./examples/../slam/meta_slam.py", line 30, in forward
output = self._frontend(batch["data"], self.state, self.delta)
File "/home/user/linzejun01/linzejun_mutiply_view01/NeRF-SLAM/./examples/../slam/vio_slam.py", line 119, in _frontend
x0_visual, visual_factors, viz_out = self.visual_frontend(batch) # TODO: currently also calls BA, and global BA
File "/home/user/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "/home/user/linzejun01/linzejun_mutiply_view01/NeRF-SLAM/./examples/../slam/visual_frontends/visual_frontend.py", line 331, in forward
self.__initialize()
File "/home/user/linzejun01/linzejun_mutiply_view01/NeRF-SLAM/./examples/../slam/visual_frontends/visual_frontend.py", line 655, in __initialize
x0, rcm_factor = self.update(kf0=None, kf1=None, use_inactive=True)
File "/home/user/.local/lib/python3.8/site-packages/torch/amp/autocast_mode.py", line 14, in decorate_autocast
return func(*args, **kwargs)
File "/home/user/linzejun01/linzejun_mutiply_view01/NeRF-SLAM/./examples/../slam/visual_frontends/visual_frontend.py", line 444, in update
x0, rcm_factor = self.ba(gru_estimated_flow, gru_estimated_flow_weight, damping,
File "/home/user/linzejun01/linzejun_mutiply_view01/NeRF-SLAM/./examples/../slam/visual_frontends/visual_frontend.py", line 1143, in ba
linear_factor_graph.push_back(vision_factors)
TypeError: push_back(): incompatible function arguments. The following argument types are supported:
1. (self: gtsam.gtsam.GaussianFactorGraph, factor: gtsam.gtsam.GaussianFactor) -> None
2. (self: gtsam.gtsam.GaussianFactorGraph, conditional: gtsam::GaussianConditional) -> None
3. (self: gtsam.gtsam.GaussianFactorGraph, graph: gtsam.gtsam.GaussianFactorGraph) -> None
4. (self: gtsam.gtsam.GaussianFactorGraph, bayesNet: gtsam::GaussianBayesNet) -> None
5. (self: gtsam.gtsam.GaussianFactorGraph, bayesTree: gtsam::GaussianBayesTree) -> None
The text was updated successfully, but these errors were encountered:
Traceback (most recent call last):
File "./examples/slam_demo.py", line 200, in
run(args)
File "./examples/slam_demo.py", line 143, in run
slam_module.spin() # visualizer should be the main spin, but pytorch has a memory bug/leak if threaded...
File "/home/user/linzejun01/linzejun_mutiply_view01/NeRF-SLAM/./examples/../pipeline/pipeline_module.py", line 101, in spin
output = self.spin_once(input);
File "/home/user/linzejun01/linzejun_mutiply_view01/NeRF-SLAM/./examples/../slam/slam_module.py", line 11, in spin_once
output = self.slam(input)
File "/home/user/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "/home/user/linzejun01/linzejun_mutiply_view01/NeRF-SLAM/./examples/../slam/meta_slam.py", line 30, in forward
output = self._frontend(batch["data"], self.state, self.delta)
File "/home/user/linzejun01/linzejun_mutiply_view01/NeRF-SLAM/./examples/../slam/vio_slam.py", line 119, in _frontend
x0_visual, visual_factors, viz_out = self.visual_frontend(batch) # TODO: currently also calls BA, and global BA
File "/home/user/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "/home/user/linzejun01/linzejun_mutiply_view01/NeRF-SLAM/./examples/../slam/visual_frontends/visual_frontend.py", line 331, in forward
self.__initialize()
File "/home/user/linzejun01/linzejun_mutiply_view01/NeRF-SLAM/./examples/../slam/visual_frontends/visual_frontend.py", line 655, in __initialize
x0, rcm_factor = self.update(kf0=None, kf1=None, use_inactive=True)
File "/home/user/.local/lib/python3.8/site-packages/torch/amp/autocast_mode.py", line 14, in decorate_autocast
return func(*args, **kwargs)
File "/home/user/linzejun01/linzejun_mutiply_view01/NeRF-SLAM/./examples/../slam/visual_frontends/visual_frontend.py", line 444, in update
x0, rcm_factor = self.ba(gru_estimated_flow, gru_estimated_flow_weight, damping,
File "/home/user/linzejun01/linzejun_mutiply_view01/NeRF-SLAM/./examples/../slam/visual_frontends/visual_frontend.py", line 1143, in ba
linear_factor_graph.push_back(vision_factors)
TypeError: push_back(): incompatible function arguments. The following argument types are supported:
1. (self: gtsam.gtsam.GaussianFactorGraph, factor: gtsam.gtsam.GaussianFactor) -> None
2. (self: gtsam.gtsam.GaussianFactorGraph, conditional: gtsam::GaussianConditional) -> None
3. (self: gtsam.gtsam.GaussianFactorGraph, graph: gtsam.gtsam.GaussianFactorGraph) -> None
4. (self: gtsam.gtsam.GaussianFactorGraph, bayesNet: gtsam::GaussianBayesNet) -> None
5. (self: gtsam.gtsam.GaussianFactorGraph, bayesTree: gtsam::GaussianBayesTree) -> None
The text was updated successfully, but these errors were encountered: