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[BUG]: DLPack tensors may be released before async launch work is finished #88
Description
Version
current main checkout (0477a34 locally); this code path appears to date back to the initial public import as well
CUDA Toolkit Version
not pinned yet; this came from source review rather than a runtime repro on a specific toolkit version
Which installation method(s) does this occur on?
Source
Describe the bug
I think the generic DLPack launch path is releasing consumed DLManagedTensor objects too early.
In cext/tile_kernel.cpp, arrayrepr_dlpack_common() renames the capsule to "used_dltensor" and then immediately calls tensor->deleter(tensor). That happens while kernel arguments are still being prepared, before prepare_launch() returns, and before cuLaunchKernelEx() is called.
For generic __dlpack__ objects, arrayrepr_dlpack() also calls __dlpack__(stream=-1), so the producer is explicitly being told not to synchronize.
My understanding of the DLPack ownership/lifetime contract is that once the consumer takes ownership of the capsule, it should keep the managed tensor alive until the consumer is actually done with it. Releasing it during argument parsing looks wrong on its own, and in the async CUDA launch path it seems like it could become a stale-pointer / premature-release problem for producers that rely on the deleter to hold the export alive until consumer work has safely passed.
What made me look twice is that there is already a comment in the code saying this is "technically an incorrect implementation" and suggesting an event-based deferred release after launch.
The control flow I am looking at is:
arrayrepr_dlpack()calls__dlpack__(stream=-1)arrayrepr_dlpack_common()reads the pointer, renames the capsule, and immediately calls the deleter- the actual kernel enqueue happens later in
launch()viacuLaunchKernelEx()
Minimum reproducible example
I do not have a clean runtime repro yet. I found this during code review because the control flow itself looks off:
1. producer returns a DLPack capsule
2. cuTile reads the exported pointer
3. cuTile immediately calls the DLPack deleter
4. the CUDA kernel launch happens afterwards, asynchronously
The repro shape I would expect to fail is a producer whose deleter drops the last owner or returns memory to a pool before the launched kernel has actually finished using the pointer.
Relevant log output
none yet
Full env printout
not available yet
Other/Misc.
Code pointers on current main:
cext/tile_kernel.cpp:arrayrepr_dlpack_common()cext/tile_kernel.cpp:arrayrepr_dlpack()cext/tile_kernel.cpp:launch()
If I am reading the intent correctly, it seems like the managed tensor probably needs to stay alive until launch work on the relevant stream is safely past the point where the producer can release it, rather than being deleted during argument extraction.
Happy to help with a repro if that would be useful.
Activity
haijieg commentedon Jun 1, 2026
@fallintoplace, as the comment in the code said, we currently have assumed that
__dlpack__return a view to simplify the deletion logic. Do you have a use case where__dlpack__returns copy?fallintoplace commentedon Jun 1, 2026
Thanks, that makes sense for the common PyTorch view case. My concern is mainly with the generic dlpack path: a copy-returning producer would be one repro, but even a view producer could use the DLManagedTensor deleter to release producer-side lifetime state. So calling the deleter before the async launch work has completed still seems too early.
haijieg commentedon Jun 1, 2026
I don't disagree with you, but I'm curious about if there an actual use case that hits the generic path. A copy-returning producer would be very inefficient, since every time calling
__dlpack__means creating a new copy. A view producer deleting producer-side lifetime state also seems very unlikely, as it would mean that "freeing the dlpack tensor would invalidate the original tensor".