[mlir][sparse] Rename the public SparseTensorStorage::asCOO to toCOO
Trying to reduce confusion by having the name of the public method match that of the private method for handling the recursion. Also adding some comments to SparseTensorStorage::fromCOO to help clarify what the recursive calls are doing in the dense case. Reviewed By: aartbik Differential Revision: https://reviews.llvm.org/D108954
This commit is contained in:
parent
befb384484
commit
b04b757a8e
|
@ -217,7 +217,7 @@ public:
|
|||
|
||||
/// Returns this sparse tensor storage scheme as a new memory-resident
|
||||
/// sparse tensor in coordinate scheme with the given dimension order.
|
||||
SparseTensor<V> *asCOO(uint64_t *perm) {
|
||||
SparseTensor<V> *toCOO(uint64_t *perm) {
|
||||
// Restore original order of the dimension sizes and allocate coordinate
|
||||
// scheme with desired new ordering specified in perm.
|
||||
uint64_t size = getRank();
|
||||
|
@ -272,6 +272,9 @@ private:
|
|||
if (sparsity[d] == kCompressed) {
|
||||
indices[d].push_back(idx);
|
||||
} else {
|
||||
// For dense storage we must fill in all the zero values between
|
||||
// the previous element (when last we ran this for-loop) and the
|
||||
// current element.
|
||||
for (; full < idx; full++)
|
||||
fromCOO(tensor, sparsity, 0, 0, d + 1); // pass empty
|
||||
full++;
|
||||
|
@ -284,6 +287,8 @@ private:
|
|||
if (sparsity[d] == kCompressed) {
|
||||
pointers[d].push_back(indices[d].size());
|
||||
} else {
|
||||
// For dense storage we must fill in all the zero values after
|
||||
// the last element.
|
||||
for (uint64_t sz = tensor->getSizes()[d]; full < sz; full++)
|
||||
fromCOO(tensor, sparsity, 0, 0, d + 1); // pass empty
|
||||
}
|
||||
|
@ -495,7 +500,7 @@ char *getTensorFilename(uint64_t id) {
|
|||
else if (action == 2) \
|
||||
return SparseTensor<V>::newSparseTensor(asize, sizes, perm); \
|
||||
else \
|
||||
return static_cast<SparseTensorStorage<P, I, V> *>(ptr)->asCOO(perm); \
|
||||
return static_cast<SparseTensorStorage<P, I, V> *>(ptr)->toCOO(perm); \
|
||||
return SparseTensorStorage<P, I, V>::newSparseTensor(tensor, sparsity, \
|
||||
perm); \
|
||||
}
|
||||
|
|
Loading…
Reference in a new issue