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fix bug in example 2 #361

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Aug 15, 2024
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fix bug in example 2 #361

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fix bug in example 2
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@alexander-soare
alexander-soare committed Aug 14, 2024
commit cfb8e04f5d8f0c8123a14591b213da533c0b3308
15 changes: 8 additions & 7 deletions examples/2_evaluate_pretrained_policy.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,6 +18,14 @@
output_directory = Path("outputs/eval/example_pusht_diffusion")
output_directory.mkdir(parents=True, exist_ok=True)

# Download the diffusion policy for pusht environment
pretrained_policy_path = Path(snapshot_download("lerobot/diffusion_pusht"))
# OR uncomment the following to evaluate a policy from the local outputs/train folder.
# pretrained_policy_path = Path("outputs/train/example_pusht_diffusion")

policy = DiffusionPolicy.from_pretrained(pretrained_policy_path)
policy.eval()

# Check if GPU is available
if torch.cuda.is_available():
device = torch.device("cuda")
Expand All @@ -28,13 +36,6 @@
# Decrease the number of reverse-diffusion steps (trades off a bit of quality for 10x speed)
policy.diffusion.num_inference_steps = 10

# Download the diffusion policy for pusht environment
pretrained_policy_path = Path(snapshot_download("lerobot/diffusion_pusht"))
# OR uncomment the following to evaluate a policy from the local outputs/train folder.
# pretrained_policy_path = Path("outputs/train/example_pusht_diffusion")

policy = DiffusionPolicy.from_pretrained(pretrained_policy_path)
policy.eval()
policy.to(device)

# Initialize evaluation environment to render two observation types:
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