jorisvandenbossche commented on code in PR #42118:
URL: https://github.com/apache/arrow/pull/42118#discussion_r1638074823
##########
cpp/src/arrow/c/dlpack.cc:
##########
@@ -130,4 +131,67 @@ Result<DLDevice> ExportDevice(const
std::shared_ptr<Array>& arr) {
}
}
+struct TensorManagerCtx {
+ std::shared_ptr<Tensor> t;
+ std::vector<int64_t> shape;
+ std::vector<int64_t> strides;
+ DLManagedTensor tensor;
+};
+
+Result<DLManagedTensor*> ExportTensor(const std::shared_ptr<Tensor>& t) {
+ // Define the DLDataType struct
+ const DataType& type = *t->type();
+ ARROW_ASSIGN_OR_RAISE(DLDataType dlpack_type, GetDLDataType(type));
+
+ // Define DLDevice struct
+ ARROW_ASSIGN_OR_RAISE(DLDevice device, ExportDevice(t))
+
+ // Create ManagerCtx that will serve as the owner of the DLManagedTensor
+ std::unique_ptr<TensorManagerCtx> ctx(new TensorManagerCtx);
+
+ // Define the data pointer to the DLTensor
+ // If tensor is of length 0, data pointer should be NULL
+ if (t->size() == 0) {
+ ctx->tensor.dl_tensor.data = NULL;
+ } else {
+ ctx->tensor.dl_tensor.data = t->raw_mutable_data();
+ }
+
+ ctx->tensor.dl_tensor.device = device;
+ ctx->tensor.dl_tensor.ndim = t->ndim();
+ ctx->tensor.dl_tensor.dtype = dlpack_type;
+
+ std::vector<int64_t>* shape_arr = &ctx->shape;
+ std::vector<int64_t>* strides_arr = &ctx->strides;
+ shape_arr->resize(t->ndim());
+ strides_arr->resize(t->ndim());
+ for (int i = 0; i < t->ndim(); i++) {
+ (*shape_arr)[i] = t->shape().data()[i];
+ (*strides_arr)[i] = t->strides().data()[i] / t->type()->byte_width();
+ }
+ ctx->tensor.dl_tensor.shape = shape_arr->data();
+ ctx->tensor.dl_tensor.strides = strides_arr->data();
+ ctx->tensor.dl_tensor.byte_offset = 0;
+
+ ctx->t = std::move(t);
+ ctx->tensor.manager_ctx = ctx.get();
+ ctx->tensor.deleter = [](struct DLManagedTensor* self) {
+ delete reinterpret_cast<ManagerCtx*>(self->manager_ctx);
Review Comment:
```suggestion
delete reinterpret_cast<TensorManagerCtx*>(self->manager_ctx);
```
That might fix the memory leak?
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