I want to test the function "CombineParallelConv2D", so I use the GoogLenet. The below is my code. import numpy as np
import tvm from tvm import relay from tvm.autotvm.graph_tuner import DPTuner from tvm.contrib import graph_runtime import torch import torchvision from torchvision import models googlenet = models.googlenet(pretrained=True) model = googlenet.eval() model.dropout = torch.nn.Dropout(p = 0) input_shape = [1, 3, 224, 299] input_data = torch.randn(input_shape) scripted_model = torch.jit.trace(model, input_data).eval() input_name = 'img' shape_list = [(input_name, input_shape)] mod, params = relay.frontend.from_pytorch(scripted_model, shape_list) seq = tvm.transform.Sequential( [ relay.transform.FoldConstant(), relay.transform.EliminateCommonSubexpr(), relay.transform.FuseOps(), relay.transform.CombineParallelConv2D(3), ] ) mod1 = seq(mod) And my error is : "Check failed: (idx < data_.size() && data_[idx].second != 0) is false: Attribute TOpPattern has not been registered for nn.batch_norm" --- [Visit Topic](https://discuss.tvm.apache.org/t/question-about-the-googlenet-relay/11799/1) to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click here](https://discuss.tvm.apache.org/email/unsubscribe/44f51947d017ae55f4ae5d764642d9581890c790c3d937dda37a2068b4f61745).