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 +1,97 @@
+//
+//  Convolution3D.cpp
+//  MNNConverter
+//
+//  Created by MNN on 2019/01/31.
+//  Copyright © 2018, Alibaba Group Holding Limited
+//
+
+#include <cstdint>
+#include <vector>
+#include "OpConverter.hpp"
+#include "logkit.h"
+using namespace std;
+
+class Convolution3DConverter : public OpConverter {
+public:
+    Convolution3DConverter() {
+    }
+
+    virtual ~Convolution3DConverter() {
+    }
+
+    virtual MNN::OpType opType() {
+        return MNN::OpType_Convolution3D;
+    }
+
+    virtual MNN::OpParameter type() {
+        return MNN::OpParameter_Convolution3D;
+    }
+
+    virtual void run(MNN::OpT* dstOp, const caffe::LayerParameter& parameters, const caffe::LayerParameter& weight) {
+        auto convolution3D = new MNN::Convolution3DT;
+        DCHECK(weight.blobs_size() >= 1) << "Convolution3D weight blob ERROR! ==> " << parameters.name();
+        dstOp->main.value = convolution3D;
+
+        convolution3D->common = std::unique_ptr<MNN::Convolution3DCommonT>(new MNN::Convolution3DCommonT);
+        auto& common          = convolution3D->common;
+
+        common->padMode = MNN::PadMode_CAFFE;
+        common->relu = common->relu6 = false;
+
+        auto& convProto = parameters.convolution3d_param();
+        { // group must be equal to 1
+            const int group = convProto.has_group() ? convProto.group() : 1;
+            DCHECK(group == 1) << "Convolution3D not support group convolution";
+        }
+
+        { // kernel_size, kernel_depth
+            const int kernel_depth = convProto.kernel_depth();
+            const int kernel_size  = convProto.kernel_size();
+            common->kernels        = std::vector<int32_t>({kernel_depth, kernel_size, kernel_size});
+        }
+        { // stride, temporal_stride
+            const int stride          = convProto.stride();
+            const int temporal_stride = convProto.temporal_stride();
+            common->strides           = std::vector<int32_t>({temporal_stride, stride, stride});
+        }
+        { // pad, temporal_pad
+            const int pad          = convProto.pad();
+            const int temporal_pad = convProto.temporal_pad();
+            common->pads           = std::vector<int32_t>({temporal_pad, pad, pad});
+        }
+        common->dilates = std::vector<int32_t>({1, 1, 1});
+
+        { // set kernel weight data
+            auto& weightBlob = weight.blobs(0);
+            DCHECK(weightBlob.shape().dim_size() == 5) << "Conv3D Weight Dimension ERROR!";
+            common->outputCount = convProto.num_output();
+            DCHECK(weightBlob.has_shape()) << "Caffemodel ERROR!";
+            common->inputCount = weightBlob.shape().dim(1);
+
+            int size = 1;
+            for (int i = 0; i < weightBlob.shape().dim_size(); ++i) {
+                size *= weightBlob.shape().dim(i);
+            }
+            std::vector<float> weightData;
+            weightData.resize(size);
+            for (int i = 0; i < size; ++i) {
+                weightData[i] = weightBlob.data(i);
+            }
+            convolution3D->weight = weightData;
+        }
+
+        { // set bias data
+            std::vector<float> biasData(convProto.num_output(), 0.0f);
+            if (convProto.bias_term() && weight.blobs_size() >= 2) {
+                for (int i = 0; i < biasData.size(); ++i) {
+                    biasData[i] = weight.blobs(1).data(i);
+                }
+            }
+            convolution3D->bias = biasData;
+        }
+    }
+};
+
+// https://github.com/facebook/C3D/blob/master/C3D-v1.1/src/caffe/proto/caffe.proto
+static OpConverterRegister<Convolution3DConverter> a("Convolution3D");