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
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+//
+//  ShapeConvTranspose3D.cpp
+//  MNN
+//
+//  Created by MNN on 2019/01/10.
+//  Copyright © 2018, Alibaba Group Holding Limited
+//
+
+#include <math.h>
+#include "shape/SizeComputer.hpp"
+#include "core/Macro.h"
+#include "core/TensorUtils.hpp"
+namespace MNN {
+class ConvTranspose3DSizeComputer : public SizeComputer {
+public:
+    virtual bool onComputeSize(const MNN::Op* op, const std::vector<Tensor*>& inputs,
+                               const std::vector<Tensor*>& outputs) const override {
+//            MNN_ASSERT(1 == inputs.size());
+        MNN_ASSERT(1 == outputs.size());
+
+        auto layer        = op->main_as_Convolution3D()->common();
+        auto input = inputs[0];
+        int dimensions = input->dimensions();
+        int convolutinDim = dimensions - 2;
+
+        auto& outputBuffer         = outputs[0]->buffer();
+        outputBuffer.dimensions    = input->buffer().dimensions;
+        outputBuffer.dim[0].extent = input->buffer().dim[0].extent;
+        outputBuffer.dim[1].extent = layer->outputCount();
+
+        for (int i = 0; i < convolutinDim; ++i) {
+            const int inputLength = input->length(i + 2), stride = (*layer->strides())[i];
+            if (inputLength <= 0) {
+                return false;
+            }
+            int outputLength;
+            if (layer->padMode() == PadMode_SAME) {
+                outputLength =inputLength * stride;
+            } else {
+                int padL = 0;
+                int padR = 0;
+                int kernel = layer->kernels()->data()[i];
+                int dialate = 1;
+                if (nullptr != layer->pads()) {
+                    padL = layer->pads()->data()[i];
+                    if (layer->pads()->size() == 6) {
+                        padR = layer->pads()->data()[i + 3];
+                    } else {
+                        padR = padL;
+                    }
+                }
+                if (nullptr != layer->dilates()) {
+                    dialate = layer->dilates()->data()[i];
+                }
+                const int dialatedKernel = (kernel - 1) * dialate + 1;
+//                    outputLength = (inputLength + 2 * pad - dialatedKernel) / stride + 1;
+                outputLength = (inputLength - 1) * stride + dialatedKernel - padR - padL;
+                if (layer->outPads() != nullptr) {
+                    outputLength = outputLength + layer->outPads()->data()[i];
+                }
+            }
+            outputBuffer.dim[i + 2].extent = outputLength;
+        }
+
+        outputBuffer.type = input->getType();
+
+        TensorUtils::getDescribe(outputs[0])->dimensionFormat = TensorUtils::getDescribe(inputs[0])->dimensionFormat;
+        return true;
+    }
+};
+
+REGISTER_SHAPE(ConvTranspose3DSizeComputer, OpType_ConvTranspose3D);
+} // namespace MNN