samskalicky commented on a change in pull request #17569: Adding sparse support
to MXTensor for custom operators
URL: https://github.com/apache/incubator-mxnet/pull/17569#discussion_r387408282
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File path: src/c_api/c_api.cc
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@@ -114,13 +114,19 @@ void CustomFComputeDispatcher(const std::string op_name,
const std::vector<OpReqType>& req,
const std::vector<NDArray>& outputs) {
std::vector<void*> in_data, out_data;
- std::vector<const int64_t *> in_shapes, out_shapes;
+ std::vector<const int64_t*> in_shapes, out_shapes;
std::vector<int> in_dims, out_dims;
std::vector<int> in_types, out_types;
std::vector<size_t> in_verIDs, out_verIDs;
std::vector<const char*> in_dev_type, out_dev_type;
std::vector<int> in_dev_id, out_dev_id;
+ // Extra data for sparse inputs.
+ std::vector<void*> in_indices;
+ std::vector<void*> in_indptr;
+ std::vector<int64_t> in_indices_shapes;
+ std::vector<int64_t> in_indptr_shapes;
Review comment:
lets just initialize these vectors to inputs.size(). Then it'll be easier to
index into them with the same index as the tensor input
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