LAV
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Using a pre-trained model
Hi there,
I would like to test the pre-trained model against pedestrian models that I have been developing. I see there is a weight folder but still not sure how to create an agent and load the weights. Can you guide me?
Thank you for your interest in our project.
Please follow the instructions here on how to directly run an agent with pre-trained model weights.
Please make sure to have installed git-lfs
before cloning the repo.
Thanks for the prompt reponse.
Hi @dotchen, when are you planning on releasing the Leaderboard weights for model evaluation? Thanks in advance.
I will try to find sometime to refactor and release it. Hopefully around June.
Hi @dotchen,
Are there any updates on the leaderboard weights?
Thank you for your interest in our project.
Please follow the instructions here on how to directly run an agent with pre-trained model weights. Please make sure to have installed
git-lfs
before cloning the repo.
Hi @dotchen I followed what said in the repo but still don't know what should I do with "wights" folder!? I run the project and it' output is like this:
Running the route ======[Agent] Wallclock_time = 2024-03-10 08:13:24.232159 / 0.0 / Sim_time = 0.05000000074505806 / 50.00000074505806x ======[Agent] Wallclock_time = 2024-03-10 08:13:25.015090 / 0.782931 / Sim_time = 0.10000000149011612 / 0.12756224908839695x
Stopping the route, the agent has crashed:
Not compiled with CUDA support
Traceback (most recent call last): File "/home/missakhbariun/LAV/leaderboard/leaderboard/scenarios/scenario_manager.py", line 152, in _tick_scenario ego_action = self._agent() File "/home/missakhbariun/LAV/leaderboard/leaderboard/autoagents/agent_wrapper.py", line 75, in call return self._agent() File "/home/missakhbariun/LAV/leaderboard/leaderboard/autoagents/autonomous_agent.py", line 115, in call control = self.run_step(input_data, timestamp) File "/home/missakhbariun/miniconda3/envs/LAV-env/lib/python3.7/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context return func(*args, **kwargs) File "/home/missakhbariun/LAV/team_code_v2/lav_agent.py", line 318, in run_step pred_bev = self.lidar_model([lidar_points], [len(lidar_points)]) File "/home/missakhbariun/miniconda3/envs/LAV-env/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl return forward_call(*input, **kwargs) File "/home/missakhbariun/LAV/team_code_v2/models/lidar.py", line 37, in forward features = self.point_pillar_net(lidars, num_points) File "/home/missakhbariun/miniconda3/envs/LAV-env/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl return forward_call(*input, **kwargs) File "/home/missakhbariun/LAV/team_code_v2/models/point_pillar.py", line 114, in forward features = self.point_net(decorated_points, inverse_indices) File "/home/missakhbariun/miniconda3/envs/LAV-env/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl return forward_call(*input, **kwargs) File "/home/missakhbariun/LAV/team_code_v2/models/point_pillar.py", line 33, in forward feat_max = scatter_max(feat, inverse_indices, dim=0)[0] File "/home/missakhbariun/miniconda3/envs/LAV-env/lib/python3.7/site-packages/torch_scatter/scatter.py", line 72, in scatter_max return torch.ops.torch_scatter.scatter_max(src, index, dim, out, dim_size) File "/home/missakhbariun/miniconda3/envs/LAV-env/lib/python3.7/site-packages/torch/_ops.py", line 442, in call return self._op(*args, **kwargs or {}) RuntimeError: Not compiled with CUDA support
During handling of the above exception, another exception occurred:
Traceback (most recent call last): File "/home/missakhbariun/LAV/leaderboard/leaderboard_evaluator.py", line 352, in _load_and_run_scenario self.manager.run_scenario() File "/home/missakhbariun/LAV/leaderboard/leaderboard/scenarios/scenario_manager.py", line 136, in run_scenario self._tick_scenario(timestamp) File "/home/missakhbariun/LAV/leaderboard/leaderboard/scenarios/scenario_manager.py", line 159, in _tick_scenario raise AgentError(e) leaderboard.autoagents.agent_wrapper.AgentError: Not compiled with CUDA support
Stopping the route
========= Results of RouteScenario_25 (repetition 0) ------ FAILURE =========
╒═════════════════════════════════╤═════════════════════╕ │ Start Time │ 2024-03-07 22:05:05 │ ├─────────────────────────────────┼─────────────────────┤ │ End Time │ 2024-03-07 22:05:07 │ ├─────────────────────────────────┼─────────────────────┤ │ Duration (System Time) │ 1.97s │ ├─────────────────────────────────┼─────────────────────┤ │ Duration (Game Time) │ 0.1s │ ├─────────────────────────────────┼─────────────────────┤ │ Ratio (System Time / Game Time) │ 0.051 │ ╘═════════════════════════════════╧═════════════════════╛
╒═══════════════════════╤═════════╤═════════╕ │ Criterion │ Result │ Value │ ├───────────────────────┼─────────┼─────────┤ │ RouteCompletionTest │ FAILURE │ 0.0 % │ ├───────────────────────┼─────────┼─────────┤ │ OutsideRouteLanesTest │ SUCCESS │ 0 % │ ├───────────────────────┼─────────┼─────────┤ │ CollisionTest │ SUCCESS │ 0 times │ ├───────────────────────┼─────────┼─────────┤ │ RunningRedLightTest │ SUCCESS │ 0 times │ ├───────────────────────┼─────────┼─────────┤ │ RunningStopTest │ SUCCESS │ 0 times │ ├───────────────────────┼─────────┼─────────┤ │ InRouteTest │ SUCCESS │ │ ├───────────────────────┼─────────┼─────────┤ │ AgentBlockedTest │ SUCCESS │ │ ├───────────────────────┼─────────┼─────────┤ │ Timeout │ SUCCESS │ │ ╘═══════════════════════╧═════════╧═════════╛
Registering the route statistics Registering the global statistics
It looks like it did not use the pretrained wights and models.
what should I do??? I would be so thankful if you guys help me, too.@varunjammula @adhocmaster @ricokoff @philkr