recognize group_size ==0/None as channelwise quant

quantize.py

@@ -583,6 +583,8 @@ def create_quantized_state_dict(self):
             if isinstance(mod, torch.nn.Linear):
                 assert not mod.bias
                 in_features = mod.in_features
+                if group_size is None or group_size == 0:
+                    group_size = in_features
                 # print("in features:", in_features, " out features:", out_features)
                 # assert out_features % 8 == 0, "require out_features % 8 == 0"
                 # print(f"linear: {fqn}, in={in_features}, out={out_features}")