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modeling_beacon.py

@@ -243,7 +243,8 @@ class Memory(torch.nn.Module):
                     # use the minimal possible length for this sequence (the smallest fold ratio)
                     beacon_ratio = beacon_ratio[minimum_length_index]
                 else:
-                    raise ValueError(f"Failed to find valid fold window and size for sequence length {sequence_length}, as the maximum theoretical length is {max(max_lengths)}. Please use higher beacon condensing ratios.")
+                    beacon_ratio = max(beacon_ratio)
+                    logger.warning(f"Failed to find valid fold window and size for sequence length {sequence_length}, as the maximum theoretical length is {max(max_lengths)}. Fall back to use the maximum one: {beacon_ratio}.")
                 self._ratio = beacon_ratio
             else:
                 beacon_ratio = self._ratio