Method SetUp

src/opr/test/dnn/convolution.cpp:2529–2550

    MockConvolutionForward& mock_conv() { return *mock_conv_ptr; }

    void SetUp() override {
        constexpr uint32_t ih = 10, ic = 16, oc = 32, ph = 0, sh = 1, fh = 2, iw = ih;
        comp_node = CompNode::load("cpux");
        graph = ComputingGraph::make();
        graph->options().graph_opt.weight_preprocess = is_weight_preprocess();
        TensorShape x_shape{1, ic, ih, iw}, w_shape{oc, ic, fh, fh};
        x_host = std::make_shared<HostTensorND>(comp_node, x_shape);
        auto x = opr::Host2DeviceCopy::make(*graph, x_host);
        auto w = opr::ImmutableTensor::make(*graph, {comp_node, w_shape});
        Param param;
        param.pad_h = param.pad_w = ph;
        param.stride_h = param.stride_w = sh;
        param.format = Param::Format::NCHW;
        y = opr::ConvolutionForward::make(x, w, param);
        auto& opr = y.node()->owner_opr()->cast_final<opr::ConvolutionForward>();
        auto mock = std::make_unique<MockConvolutionForward>(
                opr.megdnn_opr(),
                ::testing::UnitTest::GetInstance()->current_test_info()->name());
        mock_conv_ptr = mock.get();
        ConvolutionTestingPeer{&opr}.set_megdnn_opr(std::move(mock));
        func = graph->compile({make_callback_copy(y, y_host)});
    }

    void run() { func->execute().wait(); }