forked from kscience/kmath
57 lines
1.2 KiB
C++
57 lines
1.2 KiB
C++
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#include <torch/torch.h>
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#include "ctorch.h"
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namespace ctorch
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{
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template <typename Dtype>
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inline c10::ScalarType dtype()
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{
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return torch::kFloat64;
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}
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template <>
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inline c10::ScalarType dtype<float>()
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{
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return torch::kFloat32;
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}
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template <>
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inline c10::ScalarType dtype<long>()
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{
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return torch::kInt64;
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}
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template <>
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inline c10::ScalarType dtype<int>()
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{
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return torch::kInt32;
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}
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inline torch::Tensor &cast(TorchTensorHandle tensor_handle)
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{
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return *static_cast<torch::Tensor *>(tensor_handle);
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}
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template <typename Dtype>
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inline torch::Tensor copy_from_blob(Dtype *data, int *shape, int dim)
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{
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auto shape_vec = std::vector<int64_t>(dim);
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shape_vec.assign(shape, shape + dim);
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return torch::from_blob(data, shape_vec, dtype<Dtype>()).clone();
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}
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template <typename IntArray>
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inline int *to_dynamic_ints(IntArray arr)
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{
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size_t n = arr.size();
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int *res = (int *)malloc(sizeof(int) * n);
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for (size_t i = 0; i < n; i++)
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{
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res[i] = arr[i];
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}
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return res;
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}
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} // namespace ctorch
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