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 +1,67 @@
+//
+//  InnerProductTest.cpp
+//  MNNTests
+//
+//  Created by MNN on 2020/07/16.
+//  Copyright © 2018, Alibaba Group Holding Limited
+//
+
+#include <MNN/expr/Expr.hpp>
+#include <MNN/expr/ExprCreator.hpp>
+#include <string>
+#include <vector>
+#include "MNNTestSuite.h"
+#include "TestUtils.h"
+using namespace MNN::Express;
+class InnerProductTest : public MNNTestCase {
+public:
+    virtual ~InnerProductTest() = default;
+    virtual bool run(int precision) {
+        int batch         = 1;
+        int outputChannel = 2;
+        auto input        = _Input({batch, 4 * 2 * 3}, NCHW, halide_type_of<float>());
+
+        std::vector<float> inputData = {// inputChannel 0
+                                        1.0, 2.0, 3.0, 4.0, 5.0, 6.0,
+                                        // inputChannel 1
+                                        1.1, 2.1, 3.1, 4.1, 5.1, 6.1,
+                                        // inputChannel 2
+                                        1.2, 2.2, 3.2, 4.2, 5.2, 6.2,
+                                        // inputChannel 3
+                                        1.3, 2.3, 3.3, 4.3, 5.3, 6.3};
+
+        std::vector<float> weightData = {/* outputChannel 0*/
+                                         // inputChannel 0
+                                         1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
+                                         // inputChannel 1
+                                         1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
+                                         // inputChannel 2
+                                         1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
+                                         // inputChannel 3
+                                         1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
+
+                                         /* outputChannel 1*/
+                                         // inputChannel 0
+                                         4.3, 1.3, 6.3, 0.0, -2.3, 3.3,
+                                         // inputChannel 1
+                                         -4.0, 5.0, 6.0, 1.0, 2.0, 3.0,
+                                         // inputChannel 2
+                                         4.1, 5.1, 6.1, 1.1, 2.1, 3.1,
+                                         // inputChannel 3
+                                         4.2, 5.2, -6.2, 1.2, 2.2, 0.2};
+        std::vector<float> biasData = {1.0, 0.0};
+        std::vector<float> outputData = {88.6, 176.86};
+
+        INTS outputShape = {batch, outputChannel};
+        ::memcpy(input->writeMap<float>(), inputData.data(), inputData.size() * sizeof(float));
+        auto output = _InnerProduct(std::move(weightData), std::move(biasData), input, outputShape);
+        auto outPtr = output->readMap<float>();
+
+        if (!checkVectorByRelativeError<float>(outPtr, outputData.data(), outputData.size(), 0.005)) {
+            MNN_ERROR("InnerProductTest test failed!\n");
+            return false;
+        }
+        return true;
+    }
+};
+MNNTestSuiteRegister(InnerProductTest, "op/InnerProduct");