debug

bitsandbytes/autograd/_functions.py

@@ -370,8 +370,6 @@ class MatMul8bitLt(torch.autograd.Function):
             if state.threshold > 0.0 and subA is not None:
                 grad_B[:, idx] += torch.matmul(grad_output.t(), subA)
 
-            raise NotImplementedError("!!")
-
         if req_gradA:
             if state.CBt is not None:
                 C32grad, Sgrad = F.transform(Cgrad, "col32")

bitsandbytes/nn/modules.py

@@ -237,7 +237,9 @@ class Linear8bitLt(nn.Linear):
         if threshold > 0.0 and not has_fp16_weights:
             self.state.use_pool = True
 
-        self.weight = Int8Params(self.weight.data, has_fp16_weights=has_fp16_weights)
+        self.weight = Int8Params(
+            self.weight.data, has_fp16_weights=has_fp16_weights, requires_grad=has_fp16_weights
+        )
 
     def init_8bit_state(self):
         self.state.CB = self.weight.CB