Gsp dev #149
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Gsp dev #149
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* Add human ll loss with random actions [placeholder]. * Change clip coef * Typo * Integrate the actual human data into pipeline. * Back at 194 K FPS. Save data to disk, only load small batch to gpu when needed. * Ignore human data. * Revert small unrelated change. * Remove print statement * Return the continuous actions for sanity checks. * Log the weighted loss objectives instead. * Always compute human log prob for systematic analysis. * Bug fix: do not use human entropy. * Small fixes * Experimental settings. * Simplify expert data generation logic. * Small improvement * Store amount of human data used in checkpoints (each seq is 3 seconds of human data). * Cleanup/
* WIP guidance reward * remove irrelevant const * heading fix * minor refactor * fix normalize function defn * removed master weight * guidance reward sweeps
…#112) * start on obs space cfg * rmv magic numbers * Pass ini -> drive env. * Working on fuse linear * Integrate 700k SPS kernel. * Dirty * Profile fix * linear max kernel * Add linearmax kernels * LinearMax with layernorm: 600/700K SPS, score of 0.85 in < 5 min. * Use 1000 maps * Best run gets score of .95 in 25 minutes. * Advantage weighting exps * Sweep setup. * Increase steps. * Remove exploration logging. * Delete Triton kernel. * Best score is 0.98 with 600K FPS. 800 K FPS with 128 road points. * Better hparams * Replace default learning rate and ent_coef. * Minor * start on obs space cfg * rmv magic numbers * Pass ini -> drive env. * Working on fuse linear * Integrate 700k SPS kernel. * Dirty * Profile fix * linear max kernel * Add linearmax kernels * LinearMax with layernorm: 600/700K SPS, score of 0.85 in < 5 min. * Best run gets score of .95 in 25 minutes. * Advantage weighting exps * Sweep setup. * Increase steps. * Remove exploration logging. * Delete Triton kernel. * Best score is 0.98 with 600K FPS. 800 K FPS with 128 road points. * Better hparams * Clean up. * Minor * Update profiling script. * Adapt drive c network. * Temp settings * minor * Set max agents to 32 * Add linear -> relu -> max kernel. * Score is .98 after 70 minutes. * Minor --------- Co-authored-by: Joseph Suarez <jsuarez@puffer.ai>
…rent dataset (#151) * Support train/test split with datasets. * Switch defaults. * Minor. * Typo. * More robust way of parsing the path.
* Load the sprites inside eval-gif() * Color consistency. * pedestrians and cyclists 3d models * Minor. --------- Co-authored-by: Spencer Cheng <spenccheng@gmail.com>
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