[Grouped Matmul] Fix PyTorch memory leak when tensors are not contiguous #290
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
For example, if
other[i]
was transposed, a new tensor is created in the loop offor (size_t i = 0; i < num_matrices; ++i) {
.The
data_ptr
of the tensor newly created will be used by a kernel following, but this tensor itself may get released before the kernel launch.