From f84affec23c3315fe1b1a1d61e0156cacb62a5ad Mon Sep 17 00:00:00 2001 From: Pepijn Date: Sun, 31 Aug 2025 14:00:19 +0200 Subject: [PATCH] simple eval --- src/lerobot/policies/rlearn/eval_script.py | 10 ++++++++++ 1 file changed, 10 insertions(+) diff --git a/src/lerobot/policies/rlearn/eval_script.py b/src/lerobot/policies/rlearn/eval_script.py index 30fa38312..d2cf58392 100644 --- a/src/lerobot/policies/rlearn/eval_script.py +++ b/src/lerobot/policies/rlearn/eval_script.py @@ -188,6 +188,16 @@ def predict_rewards_sliding(model, frames, language, max_seq_len=16, batch_size= # Model returns (B, L) predictions for each temporal position values = model.predict_rewards(batch) # torch.Tensor (B, L) + # DEBUG: Print model outputs to understand what's happening + if s == 0: # Only print for first batch to avoid spam + print(f"\n=== DEBUG EVALUATION ===") + print(f"Model output shape: {values.shape}") + print(f"Model output range: [{values.min():.6f}, {values.max():.6f}]") + print(f"Model output mean: {values.mean():.6f}") + print(f"First few frame positions: {batch_positions[:5]}") + print(f"Model outputs for first sample (all positions): {values[0].cpu().numpy()}") + print("========================") + if values.dim() == 2: # Extract the prediction corresponding to each frame's position in its window batch_preds = []