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Job 13291

Job ID13291
submission937
userDavid
user labelPytorch IL
challengeaido1_LF1_r3-v3
stepstep1-simulation
statusfailed
up to dateyes
evaluator368
date started
date completed
duration0:00:28
message
InvalidSubmission: T [...]
InvalidSubmission:
Traceback (most recent call last):
  File "/workspace/src/duckietown-challenges/src/duckietown_challenges/cie_concrete.py", line 486, in wrap_evaluator
    raise InvalidSubmission(out[SPECIAL_INVALID_SUBMISSION])
InvalidSubmission: Invalid solution:
Traceback (most recent call last):
  File "/notebooks/src/duckietown-challenges/src/duckietown_challenges/cie_concrete.py", line 590, in wrap_solution
    raise InvalidSubmission(msg)
InvalidSubmission: Uncaught exception in solution:
Traceback (most recent call last):
  File "/notebooks/src/duckietown-challenges/src/duckietown_challenges/cie_concrete.py", line 585, in wrap_solution
    solution.run(cis)
  File "solution.py", line 85, in run
    solve(params, cis)  # let's try to solve the challenge,
  File "solution.py", line 28, in solve
    model = PytorchTrainer().load().eval()
  File "/workspace/pytorch_model.py", line 33, in load
    self.model.load_state_dict(torch.load("trained_models/pytorch_convnet.pth"))
  File "/usr/local/lib/python2.7/dist-packages/torch/serialization.py", line 358, in load
    return _load(f, map_location, pickle_module)
  File "/usr/local/lib/python2.7/dist-packages/torch/serialization.py", line 542, in _load
    result = unpickler.load()
  File "/usr/local/lib/python2.7/dist-packages/torch/serialization.py", line 508, in persistent_load
    data_type(size), location)
  File "/usr/local/lib/python2.7/dist-packages/torch/serialization.py", line 104, in default_restore_location
    result = fn(storage, location)
  File "/usr/local/lib/python2.7/dist-packages/torch/serialization.py", line 75, in _cuda_deserialize
    raise RuntimeError('Attempting to deserialize object on a CUDA '
RuntimeError: Attempting to deserialize object on a CUDA device but torch.cuda.is_available() is False. If you are running on a CPU-only machine, please use torch.load with map_location='cpu' to map your storages to the CPU.


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