Fix quantization issues

toolkit/util/convrot_quant.py

@@ -1319,6 +1319,19 @@ class ConvRotInt8Quantizer(OstrisQuantizer):
                     f"(needs in divisible by 16, out by 8, and a power-of-4 block >= 16)"
                 )
             return False
+        if d < 128 and module.out_features % 16 != 0:
+            # cublasLt has no int8 kernel for K < 128 with N % 16 != 0
+            # (torch._int_mm raises CUBLAS_STATUS_NOT_SUPPORTED), e.g.
+            # omnigen2's 64 -> 2520 x_embedder
+            key = (d, module.out_features)
+            if key not in _skip_warned:
+                _skip_warned.add(key)
+                print_acc(
+                    f"ConvRot: skipping linears with in_features={d}, "
+                    f"out_features={module.out_features} (int8 gemm needs out "
+                    f"divisible by 16 when in < 128)"
+                )
+            return False
         return True
 
     def quantize_(self, module: torch.nn.Linear, weight_fp32: torch.Tensor) -> None: