blackkker opened a new issue, #12882: URL: https://github.com/apache/tvm/issues/12882
When importing a quantized model, i found that the qnn op has not registered the **TOpPattern** attribute. Can I set them all to kOpaque first? Then, more discussion are needed to decide the **TOpPattern** attr of the qnn op. ### Expected behavior Build normally. ### Actual behavior `Check failed: (idx < data_.size() && data_[idx].second != 0) is false: Attribute TOpPattern has not been registered for qnn.concatenate` `Check failed: (idx < data_.size() && data_[idx].second != 0) is false: Attribute TOpPattern has not been registered for qnn.dense` `Check failed: (idx < data_.size() && data_[idx].second != 0) is false: Attribute TOpPattern has not been registered for qnn.requantize` ### Environment Any environment details, such as: Operating System, TVM version, etc pytorch(1.12.0) tvm version: [9ce95a9](https://github.com/apache/tvm/tree/9ce95a9abe3db43b4a4187111c9e2ad0d6bf3dbd) ### Steps to reproduce Download [bug.zip](https://github.com/apache/tvm/files/9631099/bug.zip) Run python check.py ``` import tvm from tvm import relay import torch model_name = "googlenet_quant_torchscript.pt" pytorch_model = torch.jit.load(model_name).float().eval() input_name = "x" shape_list = [(input_name, (1, 3, 224, 224))] mod, params = relay.frontend.from_pytorch(pytorch_model, shape_list) target = tvm.target.Target("llvm", host="llvm") dev = tvm.cpu(0) with tvm.transform.PassContext(opt_level=0): lib = relay.build(mod, target=target, params=params) ``` Preferably a minimal script to cause the issue to occur. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
