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 +1,82 @@
+//
+//  ShapeResize.cpp
+//  MNN
+//
+//  Created by MNN on 2019/01/10.
+//  Copyright © 2018, Alibaba Group Holding Limited
+//
+
+#include "shape/SizeComputer.hpp"
+#include "core/Macro.h"
+
+namespace MNN {
+// Size Computer
+class ResizeComputer : public SizeComputer {
+    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());
+
+        // copy dims
+        auto resize  = op->main_as_Resize();
+        auto &input  = inputs[0]->buffer();
+        auto &output = outputs[0]->buffer();
+        TensorUtils::copyShape(inputs[0], outputs[0], true);
+
+        // set dims
+        output.dim[3].extent = input.dim[3].extent * resize->xScale();
+        output.dim[2].extent = input.dim[2].extent * resize->yScale();
+        output.type = inputs[0]->getType();
+
+        return true;
+    }
+    virtual float onComputeFlops(const MNN::Op *op, const std::vector<Tensor *> &inputs,
+                                 const std::vector<Tensor *> &outputs) const override {
+        return (float)outputs[0]->elementSize() / 1024.0f / 1024.0f * 4;
+    }
+};
+
+class ImageProcessComputer : public SizeComputer {
+    virtual bool onComputeSize(const MNN::Op *op, const std::vector<Tensor *> &inputs,
+                               const std::vector<Tensor *> &outputs) const override {
+        MNN_ASSERT(1 == inputs.size() || inputs.size() == 3);
+        MNN_ASSERT(1 == outputs.size());
+        if (inputs.size() == 3) {
+            auto &output = outputs[0]->buffer();
+            output.dimensions = 1;
+            output.dim[0].extent = 1;
+            return true;
+        }
+
+        // copy dims
+        auto &input  = inputs[0]->buffer();
+        auto &output = outputs[0]->buffer();
+        TensorUtils::copyShape(inputs[0], outputs[0], true);
+
+        // set dims
+        auto process  = op->main_as_ImageProcessParam();
+        int c = process->shape()->Get(1);
+        int h = process->shape()->Get(2);
+        int w = process->shape()->Get(3);
+        if (MNN_DATA_FORMAT_NHWC == TensorUtils::getDescribe(inputs[0])->dimensionFormat) {
+            output.dim[1].extent = h;
+            output.dim[2].extent = w;
+            output.dim[3].extent = c;
+        } else {
+            output.dim[1].extent = c;
+            output.dim[2].extent = h;
+            output.dim[3].extent = w;
+        }
+        // set dtype
+        outputs[0]->setType(process->outputType());
+        return true;
+    }
+    virtual float onComputeFlops(const MNN::Op *op, const std::vector<Tensor *> &inputs,
+                                 const std::vector<Tensor *> &outputs) const override {
+        return (float)outputs[0]->elementSize() / 1024.0f / 1024.0f * 4;
+    }
+};
+
+REGISTER_SHAPE(ResizeComputer, OpType_Resize);
+REGISTER_SHAPE(ImageProcessComputer, OpType_ImageProcess);
+} // namespace MNN