chore: import upstream snapshot with attribution

test/grad/ScaleGradTest.cpp

@@ -0,0 +1,54 @@
+//
+//  ScaleGradTest.cpp
+//  MNNTests
+//
+//  Created by MNN on 2022/08/11.
+//  Copyright © 2018, Alibaba Group Holding Limited
+//
+
+#include <MNN/expr/Expr.hpp>
+#include <MNN/expr/ExprCreator.hpp>
+#include "MNNTestSuite.h"
+#include "TestUtils.h"
+#include "../tools/train/source/grad/OpGrad.hpp"
+
+using namespace MNN;
+using namespace MNN::Express;
+
+class ScaleGradTest : public MNNTestCase {
+public:
+    char name[20] = "Scale";
+    virtual ~ScaleGradTest() = default;
+
+    virtual bool run(int precision) {
+        const int len = 4;
+        auto input = _Input({1, len, 1, 1}, NCHW);
+        const float inpudata[] = {-1.0, -2.0, 0.0, 4.0};
+        auto inputPtr          = input->writeMap<float>();
+        memcpy(inputPtr, inpudata, len * sizeof(float));
+
+        std::vector<float> scale = {0.1, 0.2, 0.3, 0.4};
+        std::vector<float> bias = {1, 2, 3, 4};
+        auto output = _Scale(input, len, std::move(scale), std::move(bias));
+        auto opExpr = output->expr().first;
+
+        auto grad = OpGrad::get(opExpr->get()->type());
+        float outputDiff[len] = {0.1, -0.2, -0.3, 0.4};
+        auto inputGrad = grad->onGrad(opExpr, {_Const(outputDiff, {1, len, 1, 1})});
+
+        const std::vector<float> expectedOutput = {0.01, -0.04, -0.09, 0.16};
+        auto gotOutput = inputGrad[0]->readMap<float>();
+
+        for (int i = 0; i < len; ++i) {
+            auto diff = ::fabsf(gotOutput[i] - expectedOutput[i]);
+            if (diff > 0.0001) {
+                MNN_ERROR("%s grad test failed, expected: %f, but got: %f!\n", name, expectedOutput[i], gotOutput[i]);
+                return false;
+            }
+        }
+
+        return true;
+    }
+};
+
+MNNTestSuiteRegister(ScaleGradTest, "grad/scale");