Upload 3 files

eval_scene.py

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+"""
+Evaluate the original LeWM model on OGBench Scene.
+
+Example:
+MUJOCO_GL=egl python eval_scene.py \
+  policy=/data_nvme/user/zliu681/le-wm-main/lewm_cache/ogbench_scene/lewm_scene/lewm_scene_epoch_10 \
+  solver.device=auto \
+  eval.num_eval=50 \
+  eval.save_video=True
+"""
+
+import faulthandler
+import sys
+
+from eval import run
+
+
+def _has_config_name(argv: list[str]) -> bool:
+    return any(arg == "--config-name" or arg.startswith("--config-name=") for arg in argv)
+
+
+if __name__ == "__main__":
+    faulthandler.enable(all_threads=True)
+    if not _has_config_name(sys.argv):
+        sys.argv.insert(1, "--config-name=scene")
+    run()

train_hyperbolic_scene.py

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+"""
+Train the HyperbolicJEPA variant on OGBench Scene.
+
+Example:
+MUJOCO_GL=egl python train_hyperbolic_scene.py \
+  trainer.accelerator=gpu \
+  trainer.devices=1 \
+  trainer.max_epochs=10 \
+  loader.batch_size=128 \
+  subdir=ogbench_scene/hyperbolic_scene \
+  wandb.enabled=False
+
+If your local cache uses a different dataset layout, override the dataset name:
+  data.dataset.name=/path/to/visual-scene-play-v0.h5
+"""
+
+import faulthandler
+
+import hydra
+
+try:
+    from torch.distributed.elastic.multiprocessing.errors import record
+except Exception:
+    def record(fn):
+        return fn
+
+from train_hyperbolic import run_hyperbolic_training
+
+
+@hydra.main(
+    version_base=None,
+    config_path="./config/train",
+    config_name="lewm_hyperbolic_scene",
+)
+def run(cfg):
+    run_hyperbolic_training(cfg)
+
+
+@record
+def _main():
+    faulthandler.enable(all_threads=True)
+    run()
+
+
+if __name__ == "__main__":
+    _main()

train_scene.py

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+"""
+Train the original LeWM model on OGBench Scene.
+
+Example:
+MUJOCO_GL=egl python train_scene.py \
+  trainer.accelerator=gpu \
+  trainer.devices=1 \
+  trainer.max_epochs=10 \
+  loader.batch_size=128 \
+  subdir=ogbench_scene/lewm_scene \
+  wandb.enabled=False
+
+If your local cache uses a different dataset layout, override the dataset name:
+  data.dataset.name=/path/to/visual-scene-play-v0.h5
+"""
+
+import faulthandler
+
+import hydra
+
+try:
+    from torch.distributed.elastic.multiprocessing.errors import record
+except Exception:
+    def record(fn):
+        return fn
+
+from train import run_training
+
+
+@hydra.main(
+    version_base=None,
+    config_path="./config/train",
+    config_name="lewm_scene",
+)
+def run(cfg):
+    run_training(cfg)
+
+
+@record
+def _main():
+    faulthandler.enable(all_threads=True)
+    run()
+
+
+if __name__ == "__main__":
+    _main()