chore: import upstream snapshot with attribution

2026-07-13 13:33:03 +08:00
commit 5b57521aa1
8226 changed files with 3425766 additions and 0 deletions
@@ -0,0 +1,80 @@
+//
+//  ReLU6GradTest.cpp
+//  MNNTests
+//
+//  Created by MNN on 2022/07/12.
+//  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 ReLU6GradTest : public MNNTestCase {
+public:
+    char name[20] = "ReLU6";
+    virtual ~ReLU6GradTest() = default;
+
+    virtual bool run(int precision) {
+        {
+            const int len = 4;
+            auto input = _Input({len}, NCHW);
+            const float inpudata[] = {-1.0, -2.0, 3.0, 6.0};
+            auto inputPtr          = input->writeMap<float>();
+            memcpy(inputPtr, inpudata, len * sizeof(float));
+
+            auto output = _Relu6(input);
+            auto opExpr = output->expr().first;
+
+            auto grad = OpGrad::get(opExpr->get()->type());
+            float outputDiff[] = {0.1, -0.2, -0.3, 0.4};
+            auto inputGrad = grad->onGrad(opExpr, {_Const(outputDiff, {len})});
+
+            const std::vector<float> expectedOutput = {0.0f, 0.0f, -0.3f, 0.0f};
+            auto gotOutput = inputGrad[0]->readMap<float>();
+
+            for (int i = 0; i < len; ++i) {
+                auto diff = ::fabsf(gotOutput[i] - expectedOutput[i]);
+                if (diff > 0.000001) {
+                    MNN_ERROR("%s grad test failed, expected: %f, but got: %f!\n", name, expectedOutput[i], gotOutput[i]);
+                    return false;
+                }
+            }
+        }
+        {
+            float minValue = -3.0f;
+            float maxValue = 1.0f;
+            const int len = 4;
+            auto input = _Input({len}, NCHW);
+            const float inpudata[] = {-1.0f, -2.0f, 3.0f, 6.0f};
+            auto inputPtr          = input->writeMap<float>();
+            memcpy(inputPtr, inpudata, len * sizeof(float));
+
+            auto output = _Relu6(input, minValue, maxValue);
+            auto opExpr = output->expr().first;
+
+            auto grad = OpGrad::get(opExpr->get()->type());
+            float outputDiff[] = {0.1f, -0.2f, -0.3f, 0.4f};
+            auto inputGrad = grad->onGrad(opExpr, {_Const(outputDiff, {len})});
+
+            const std::vector<float> expectedOutput = {0.1f, -0.2f, 0.0f, 0.0f};
+            auto gotOutput = inputGrad[0]->readMap<float>();
+
+            for (int i = 0; i < len; ++i) {
+                auto diff = ::fabsf(gotOutput[i] - expectedOutput[i]);
+                if (diff > 0.000001) {
+                    MNN_ERROR("%f-%f, %s grad test failed, expected: %f, but got: %f!\n", minValue, maxValue, name, expectedOutput[i], gotOutput[i]);
+                    return false;
+                }
+            }
+        }
+        return true;
+    }
+};
+
+MNNTestSuiteRegister(ReLU6GradTest, "grad/relu6");