9d002032d1
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)
26 lines
390 B
YAML
26 lines
390 B
YAML
# @package _global_
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eval_episodes: 50
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eval_freq: 7500
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save_freq: 75000
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log_freq: 250
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# TODO: same as simxarm, need to adjust
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offline_steps: 25000
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online_steps: 25000
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fps: 50
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env:
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name: aloha
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task: sim_insertion_human
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from_pixels: True
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pixels_only: False
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image_size: [3, 480, 640]
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action_repeat: 1
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episode_length: 400
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fps: ${fps}
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policy:
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state_dim: 14
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action_dim: 14
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