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 +1,63 @@
+//
+//  ShapeQuantizedMaxPool.cpp
+//  MNN
+//
+//  Created by MNN on 2019/01/10.
+//  Copyright © 2018, Alibaba Group Holding Limited
+//
+#include "shape/SizeComputer.hpp"
+#ifdef MNN_SUPPORT_DEPRECATED_OP
+#include <math.h>
+#include "core/Macro.h"
+
+namespace MNN {
+class QuantizedMaxPoolComputer : public SizeComputer {
+    virtual bool onComputeSize(const MNN::Op* op, const std::vector<Tensor*>& inputs,
+                               const std::vector<Tensor*>& outputs) const override {
+        auto layer = op->main_as_QuantizedMaxPool();
+
+        MNN_ASSERT(layer->strideX() == layer->strideY());
+
+        int kernel_width  = layer->kernelX();
+        int kernel_height = layer->kernelY();
+
+        int output_width  = 1;
+        int output_height = 1;
+
+        auto input = inputs[0];
+
+        if (layer->padType() == PoolPadType_SAME) {                                   // Tensorflow padding mode SAME
+            output_width  = ceil((float)input->width() / (float)layer->strideX());  // NHWC for tensorflow
+            output_height = ceil((float)input->height() / (float)layer->strideY()); // the default layout is NCHW
+        } else if (layer->padType() == PoolPadType_VALID) {                           // Tensorflow padding mode VALID
+            output_width  = ceil((float)(input->width() - kernel_width + 1) / (float)layer->strideX());
+            output_height = ceil((float)(input->height() - kernel_height + 1) / (float)layer->strideY());
+        } else {
+            MNN_ASSERT(false); // unsupported type
+        }
+
+        if (output_width <= 0 || output_height <= 0) {
+            return false;
+        }
+
+        // max pool use nhwc
+        auto& outputBuffer         = outputs[0]->buffer();
+        outputBuffer.dimensions    = input->buffer().dimensions;
+        outputBuffer.dim[0].extent = input->buffer().dim[0].extent;
+
+        outputBuffer.dim[1].extent = output_height;
+        outputBuffer.dim[2].extent = output_width;
+        outputBuffer.dim[3].extent = input->buffer().dim[3].extent;
+        outputs[0]->setType(DataType_DT_UINT8);
+        TensorUtils::getDescribe(outputs[0])->dimensionFormat = TensorUtils::getDescribe(inputs[0])->dimensionFormat;
+
+        return true;
+    }
+};
+
+} // namespace MNN
+#endif
+
+namespace MNN {
+REGISTER_SHAPE_OLD(QuantizedMaxPoolComputer, OpType_QuantizedMaxPool);
+};