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simple eval

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Pepijn
2025-08-31 13:40:13 +02:00
parent b0a5b88c21
commit 7da15ba069
2 changed files with 4 additions and 7 deletions
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src/lerobot/policies/rlearn/configuration_rlearn.py
-3
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@@ -56,9 +56,6 @@ class RLearNConfig(PreTrainedConfig):
# Sequence length, amount of past frames including current one to use in the temporal model # Sequence length, amount of past frames including current one to use in the temporal model
max_seq_len: int = 16 max_seq_len: int = 16
# Head
use_tanh_head: bool = False # when True, bound outputs in [-1, 1]
# Training # Training
learning_rate: float = 1e-3 learning_rate: float = 1e-3
weight_decay: float = 0.01 weight_decay: float = 0.01
src/lerobot/policies/rlearn/modeling_rlearn.py
+4 -4
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@@ -255,10 +255,10 @@ class RLearNPolicy(PreTrainedPolicy):
frames = extract_visual_sequence(batch, target_seq_len=self.config.max_seq_len) frames = extract_visual_sequence(batch, target_seq_len=self.config.max_seq_len)
B, T, C, H, W = frames.shape B, T, C, H, W = frames.shape
# Apply stride (no dropout during eval) # CRITICAL FIX: Do NOT apply stride during evaluation
idx = torch.arange(0, T, self.stride, device=frames.device) # During evaluation, we want to process all frames in the sliding window
frames = frames[:, idx] # Stride should only be used during training to reduce computational cost
T_eff = frames.shape[1] T_eff = T # Use all frames during evaluation
# Get language commands # Get language commands
commands = batch.get(OBS_LANGUAGE, None) commands = batch.get(OBS_LANGUAGE, None)