cast properly

bitsandbytes/autograd/_functions.py

@@ -231,7 +231,7 @@ class MatMul8bitLt(torch.autograd.Function):
 
         # Cast A to fp16
         if A.dtype != torch.float16:
-            warnings.warn(f"MatMul8bitLt: input matrix will be cast from {A.dtype} to float16")
+            warnings.warn(f"MatMul8bitLt: inputs will be cast from {A.dtype} to float16 during quantization")
 
         # 1. Quantize A
         if len(A.shape) == 3:

tests/test_autograd.py

@@ -372,8 +372,10 @@ def test_matmullt(
             n = out_bnb.numel()
             err = torch.abs(out_bnb - out_torch).mean().item()
             # print(f'abs error {err:.4f}')
+            out_error_rate = 0.0175 if dtype == torch.float16 else 0.02
+
             idx = torch.isclose(out_bnb, out_torch, atol=0.01, rtol=0.1)
-            assert (idx == 0).sum().item() <= n * 0.0175
+            assert (idx == 0).sum().item() <= n * out_error_rate
             idx = torch.isclose(out_bnb, out_torch, atol=0.035, rtol=0.2)
             assert (idx == 0).sum().item() <= n * 0.001