run backward

tests/test_modules.py

@@ -554,11 +554,22 @@ def test_linear8bitlt_no_fp16_weights(threshold, memory_efficient_backward):
             assert mlp.fc1.state.idx is not None
         if threshold > 0:
             assert mlp.fc2.state.idx is not None
+
     assert mlp.fc1.weight.dtype == torch.int8
     assert mlp.fc2.weight.dtype == torch.int8
     assert mlp.fc1.weight.device.type == "cuda"
     assert mlp.fc2.weight.device.type == "cuda"
 
+    if memory_efficient_backward:
+        b1 = torch.randn(16, 8, 32, device="cuda", requires_grad=True, dtype=torch.half)
+        o1 = mlp(b1)
+        assert o1.dtype == torch.float16
+        assert o1.requires_grad
+        grad_proj = torch.randn_like(o1)
+
+        (o1 * grad_proj).sum().backward()
+
+
 
 
 def test_linear8bitlt_fp32_bias():