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 +1,70 @@
+//
+//  ShapeRange.cpp
+//  MNN
+//
+//  Created by MNN on 2019/01/10.
+//  Copyright © 2018, Alibaba Group Holding Limited
+//
+
+#include "shape/SizeComputer.hpp"
+#include "core/Macro.h"
+#include "math.h"
+
+namespace MNN {
+
+template <typename T>
+static int computeSize(const MNN::Op* op, const std::vector<Tensor*>& inputs, const std::vector<Tensor*>& outputs) {
+    Tensor* start_in = inputs[0];
+    Tensor* limit_in = inputs[1];
+    Tensor* delta_in = inputs[2];
+
+    MNN_ASSERT((1 == start_in->buffer().dimensions) || (0 == start_in->buffer().dimensions));
+    MNN_ASSERT((1 == limit_in->buffer().dimensions) || (0 == limit_in->buffer().dimensions));
+    MNN_ASSERT((1 == delta_in->buffer().dimensions) || (0 == delta_in->buffer().dimensions));
+
+    const float start = (float)start_in->host<T>()[0];
+    const float limit = (float)limit_in->host<T>()[0];
+    const float delta = (float)delta_in->host<T>()[0];
+
+    MNN_ASSERT(0 != delta);
+    if (delta > 0) {
+        if (limit < start) {
+            return 0;
+        }
+    } else {
+        if (limit > start) {
+            return 0;
+        }
+    }
+
+    int32_t size = ceilf(fabsf((limit - start) / delta));
+    return (int)size;
+}
+
+class RangeComputer : public SizeComputer {
+    virtual bool onComputeSize(const MNN::Op* op, const std::vector<Tensor*>& inputs,
+                               const std::vector<Tensor*>& outputs) const override {
+        MNN_ASSERT(inputs.size() == 3);
+        int output_size = 0;
+        switch (inputs[0]->getType().code) {
+            case halide_type_int:
+                output_size = computeSize<int32_t>(op, inputs, outputs);
+                outputs[0]->setType(MNN::DataType_DT_INT32);
+                break;
+            case halide_type_float:
+                output_size = computeSize<float>(op, inputs, outputs);
+                outputs[0]->setType(MNN::DataType_DT_FLOAT);
+                break;
+            default:
+                MNN_ASSERT(false); // unsupported type
+        }
+        outputs[0]->buffer().dimensions    = 1;
+        outputs[0]->buffer().dim[0].extent = output_size;
+        TensorUtils::getDescribe(outputs[0])->dimensionFormat = TensorUtils::getDescribe(inputs[0])->dimensionFormat;
+
+        return true;
+    }
+};
+
+REGISTER_SHAPE_INPUTS(RangeComputer, OpType_Range, (std::vector<int>{0, 1, 2}));
+} // namespace MNN