Method run

test/op/SoftmaxTest.cpp:253–286

public:
    virtual ~SoftmaxInt8Test() = default;
    virtual bool run(int precision) {
        // testcase 1
        {
            std::vector<int> dimensions = {2, 2, 3, 4};
            auto input = _Input(dimensions, NCHW);
            input->setName("input_tensor");
            // set input data
            float inputData[] = {7.2129,5.9265,3.7045,3.1111,4.5548,7.5229,4.2968,7.9198,4.2842,9.7357,8.6082,
                                  4.2730,3.2067,9.5121,4.6973,7.1634,8.2003,6.7548,4.6160,9.3058,3.0313,7.5376,7.6309,3.8655,
                                  5.4967,5.6967,8.1985,5.9047,7.1774,6.6393,5.9027,3.9387,6.5073,4.4462,4.7199,3.6948,7.4889,
                                  9.5616,5.1855,3.1104,3.7267,5.2157,9.8103,9.8155,6.3442,8.2376,3.6553,5.3901};

            const float quantScales[] = {0.102, 0.00784};
            const float zeroPoints[]  = {1., 2.};
            input->writeScaleMap(quantScales[0], zeroPoints[0]);
            auto inputPtr          = input->writeMap<float>();
            memcpy(inputPtr, inputData, 48 * sizeof(float));
            input->unMap();
            VARP output;
            for (int axis = 0; axis < dimensions.size(); ++axis) {
                output = _Softmax(input, axis);
                output->writeScaleMap(quantScales[1], zeroPoints[1]);
                auto gotOutput                          = output->readMap<float>();

                
                bool result = checkProbAndOrder((float*)gotOutput, outputs[axis], orders[axis], 48, dimensions, axis);
                if (!result) {
                    MNN_PRINT("when axis = %d, SoftmaxInt8 case1 failed!\n", axis);
                    return false;
                }
            }
        }
        return true;
    }
};
MNNTestSuiteRegister(SoftmaxTest, "op/softmax");
MNNTestSuiteRegister(SoftmaxInt8Test, "op/softmaxInt8");