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"





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