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 +1,67 @@
+//
+//  CPUMatrixBandPart.cpp
+//  MNN
+//
+//  Created by MNN on 2019/09/17.
+//  Copyright © 2018, Alibaba Group Holding Limited
+//
+
+#include "backend/cpu/CPUMatrixBandPart.hpp"
+#include "backend/cpu/compute/ConvOpt.h"
+#include "core/TensorUtils.hpp"
+#include "core/Macro.h"
+namespace MNN {
+ErrorCode CPUMatrixBandPart::onResize(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) {
+    MNN_ASSERT(3 == inputs.size());
+    auto dimensions = inputs[0]->dimensions();
+    auto height     = inputs[0]->length(dimensions - 2);
+    auto width      = inputs[0]->length(dimensions - 1);
+    mMask.reset(Tensor::createDevice<float>({1, height*width}, Tensor::CAFFE_C4));
+    auto res                                               = backend()->onAcquireBuffer(mMask.get(), Backend::DYNAMIC);
+    if (!res) {
+        return OUT_OF_MEMORY;
+    }
+    backend()->onReleaseBuffer(mMask.get(), Backend::DYNAMIC);
+    return NO_ERROR;
+}
+ErrorCode CPUMatrixBandPart::onExecute(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs) {
+    // Generate Mask
+    auto lower   = inputs[1]->host<int32_t>()[0];
+    auto upper   = inputs[2]->host<int32_t>()[0];
+    auto maskPtr = mMask->host<float>();
+    auto dimensions = inputs[0]->dimensions();
+    auto height     = inputs[0]->length(dimensions - 2);
+    auto width      = inputs[0]->length(dimensions - 1);
+
+    for (int y = 0; y < height; ++y) {
+        auto maskY = maskPtr + y * width;
+        for (int x = 0; x < width; ++x) {
+            bool valid = (lower < 0 || (y - x) <= lower) && (upper < 0 || (x - y) <= upper);
+            maskY[x]   = valid ? 1.0f : 0.0f;
+        }
+    }
+
+    // Run Mul
+    auto outputPtr = outputs[0]->host<float>();
+    auto inputPtr  = inputs[0]->host<float>();
+    int outside    = 1;
+    for (int i = 0; i < inputs[0]->dimensions() - 2; ++i) {
+        outside *= inputs[0]->length(i);
+    }
+    auto inside = height * width;
+    for (int i = 0; i < outside; ++i) {
+        MNNMatrixProdCommon(outputPtr + i * inside, inputPtr + i * inside, maskPtr, inside, 0, 0, 0, 1);
+    }
+    return NO_ERROR;
+}
+
+class CPUMatrixBandPartCreator : public CPUBackend::Creator {
+public:
+    virtual Execution *onCreate(const std::vector<Tensor *> &inputs, const std::vector<Tensor *> &outputs,
+                                const MNN::Op *op, Backend *backend) const override {
+        return new CPUMatrixBandPart(backend);
+    }
+};
+
+REGISTER_CPU_OP_CREATOR(CPUMatrixBandPartCreator, OpType_MatrixBandPart);
+} // namespace MNN