tests/data/aloha_sim_insertion_human/replay_buffer/action.memmap

version https://git-lfs.github.com/spec/v1
oid sha256:d789deddb081a9f4b626342391de8f48949d38fb5fdead87b5c0737b46c0877a
size 2800
Add Aloha env and ACT policy WIP Aloha env tests pass Rendering works (fps look fast tho? TODO action bounding is too wide [-1,1]) Update README Copy past from act repo Remove download.py add a WIP for Simxarm Remove download.py add a WIP for Simxarm Add act yaml (TODO: try train.py) Training can runs (TODO: eval) Add tasks without end_effector that are compatible with dataset, Eval can run (TODO: training and pretrained model) Add AbstractEnv, Refactor AlohaEnv, Add rendering_hook in env, Minor modifications, (TODO: Refactor Pusht and Simxarm) poetry lock fix bug in compute_stats for action normalization fix more bugs in normalization fix training fix import PushtEnv inheriates AbstractEnv, Improve factory Normalization Add _make_env to EnvAbstract Add call_rendering_hooks to pusht env SimxarmEnv inherites from AbstractEnv (NOT TESTED) Add aloha tests artifacts + update pusht stats fix image normalization: before env was in [0,1] but dataset in [0,255], and now both in [0,255] Small fix on simxarm Add next to obs Add top camera to Aloha env (TODO: make it compatible with set of cameras) Add top camera to Aloha env (TODO: make it compatible with set of cameras) 2024-03-08 09:47:39 +00:00			`version https://git-lfs.github.com/spec/v1`
			`oid sha256:d789deddb081a9f4b626342391de8f48949d38fb5fdead87b5c0737b46c0877a`
			`size 2800`