fix codex BLOCKERs: global fixed layout invariance, min_steps off-by-one, integers EOS alias, rerun guard, eval prereg-literal codes + dual-checkpoint honesty; +7 regression tests

1 files changed, 6 insertions, 1 deletions

diff --git a/src/model_api.py b/src/model_api.py
index 66c2ace..31ffe31 100644
--- a/src/model_api.py
+++ b/src/model_api.py
@@ -3,6 +3,7 @@ import torch
 import torch.nn as nn
 
 from src.config import Config
+from src.data import pad_inputs
 
 
 class PrimeModel(nn.Module):
@@ -27,7 +28,11 @@ def build_model(cfg: Config) -> PrimeModel:
 
 @torch.no_grad()
 def greedy_decode(model: PrimeModel, x: torch.Tensor, cfg: Config, max_len: int | None = None) -> torch.Tensor:
-    """Autoregressive greedy decode of output digits. Returns (B, max_len) tokens (BOS stripped)."""
+    """Autoregressive greedy decode of output digits. Returns (B, max_len) tokens (BOS stripped).
+
+    Inputs are LEFT-padded to the global layout so positions match training exactly
+    (batch/singleton invariance — codex BLOCKER fix)."""
+    x = pad_inputs(x, cfg)
     max_len = max_len or cfg.max_out_len
     B = x.shape[0]
     y_in = torch.full((B, 1), cfg.eos_id, dtype=torch.long, device=x.device)