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 +1,61 @@
+//
+//  ShapeBatchToSpaceND.cpp
+//  MNN
+//
+//  Created by MNN on 2019/01/10.
+//  Copyright © 2018, Alibaba Group Holding Limited
+//
+
+#include "shape/SizeComputer.hpp"
+namespace MNN {
+class BatchToSpaceNDSizeComputer : public SizeComputer {
+public:
+    virtual bool onComputeSize(const MNN::Op* op, const std::vector<Tensor*>& inputs,
+                               const std::vector<Tensor*>& outputs) const override {
+        MNN_ASSERT(outputs.size() == 1);
+        MNN_ASSERT(inputs.size() == 1 || inputs.size() == 3);
+        auto input  = inputs[0];
+        auto output = outputs[0];
+
+        int blockSize = 0;
+        const int *blockData, *paddingData;
+        if (inputs.size() == 3) {
+            blockSize = inputs[1]->length(0);
+            blockData = inputs[1]->host<int32_t>();
+            paddingData = inputs[2]->host<int32_t>();
+        } else {
+            auto paramter         = op->main_as_SpaceBatch();
+            const auto blockShape = paramter->blockShape();
+            const auto paddings    = paramter->padding();
+            blockSize = blockShape->dims()->data()[0];
+            blockData = blockShape->int32s()->data();
+            paddingData = paddings->int32s()->data();
+        }
+        int batch                 = input->batch();
+        for (int i = 0; i < blockSize; ++i) {
+            batch /= blockData[i];
+        }
+        output->setLength(0, batch);
+        output->buffer().dimensions = input->buffer().dimensions;
+        auto format = TensorUtils::getDescribe(input)->dimensionFormat;
+        output->buffer().type = input->getType();
+        TensorUtils::getDescribe(output)->dimensionFormat = format;
+        if (MNN_DATA_FORMAT_NHWC != format) {
+            output->setLength(1, input->length(1));
+            for (int i = 0; i < blockSize; ++i) {
+                int paddedLength = input->length(2+i) * blockData[i] - paddingData[2 * i] - paddingData[2 * i+1];
+                output->setLength(i+2, paddedLength);
+            }
+        } else {
+            output->setLength(1 + blockSize, input->length(1 + blockSize));
+            for (int i = 0; i < blockSize; ++i) {
+                int paddedLength = input->length(1+i) * blockData[i] - paddingData[2 * i] - paddingData[2 * i+1];
+                output->setLength(i+1, paddedLength);
+            }
+        }
+        return true;
+    }
+};
+
+REGISTER_SHAPE_INPUTS(BatchToSpaceNDSizeComputer, OpType_BatchToSpaceND, std::vector<int>({1, 2}));
+} // namespace MNN