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stepankonev / waymo-motion-prediction-challenge-2022-multipath-plus-plus

Solution for Waymo Motion Prediction Challenge 2022. Our implementation of MultiPath++
https://arxiv.org/abs/2206.10041
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Result for single model #17

Open fanghgit opened 2 years ago

fanghgit commented 2 years ago

Thanks for much for sharing your code, the softmap score on the Waymo leaderboard is amazing. I tried to reproduce the result, but got only 0.372 for a single model, I guess the performance gap comes from model ensembling. Can you please share the best softmap (or map) score you got for a single model? Many thanks in advance.

ares89 commented 2 years ago

@fanghgit hi, would you like to share your trained model ?

SevenTailCat commented 1 year ago

Hi, have you meet the infinitive problem?(it means that the loss or the covariance_matrices will be infinite and will assert torch.isfinite(covariance_matrices).all() If it is possible, could you share the solution? I've tried some ways like changing the lr and the clip_grabnorm parameters...

icefall7 commented 1 year ago

@fanghgit could you share your env setup? still getting issues with prerendering. like tensorflow.python.framework.errors_impl.InvalidArgumentError: Key: roadgraph_samples/xyz. Can't parse serialized Example. [Op:ParseExampleV2]

GT-111 commented 1 year ago

@fanghgit could you share your env setup? still getting issues with prerendering. like tensorflow.python.framework.errors_impl.InvalidArgumentError: Key: roadgraph_samples/xyz. Can't parse serialized Example. [Op:ParseExampleV2]

This is probably because you are using Waymo Motion Dataset 1.2, try to modify here in feature_description.py image