Carried blocker fix for PR #1734 on this integration stack, per pr1734.md
finding F1 (reproduced on GB200/torch 2.12): with
@torch.compile(mode="reduce-overhead") on _stitch_tiles, the stitched canvas
is a CUDA-graph static buffer, and the collect-then-torch.cat consumers -
_decode (via _decode_chunks), _encode, _encode_pixels, encode_keyframe - hold
each chunk/clip result across the next _stitch_tiles replay, which overwrites
the pooled storage. First tiled decode() with >=2 temporal chunks (any real
video) and tiled encode() of >17 frames raised:
RuntimeError: Error: accessing tensor output of CUDAGraphs that has been
overwritten by a subsequent run. ... line ..., in _stitch_tiles:
return torch.cat(result_rows, dim=-2)
Fix: .clone() the stitch output at the two eager call sites (_encode_clip
tiled return, _decode_clip tiled return) so no cudagraph-owned storage
escapes the tile driver; the clone is read before the next replay, so it is
race-free by construction. The streaming _decode_to_pixels path was already
safe (full copy-out per chunk before the next decode) and stays correct at
one extra D2D copy per chunk (~tens of microseconds vs the decode compute).
This follows the option (a) recommendation in the review; reduce-overhead is
retained on _stitch_tiles/_project_decoder_tile.
Tests:
- test_decode_clip_emits_tiled_stage_ranges updated: the tile driver now
returns a caller-owned copy (is-not + equal), pinning the ownership
contract at the mock level.
- New CUDA regression gate (the review's must-add test):
test_tiled_decode_and_encode_survive_cudagraph_buffer_reuse_on_cuda - real
tiled decode() (2 temporal chunks, 2x2 spatial tiles) and encode()/
encode_pixels() (2 clips) with _stitch_tiles unmocked, asserting bitwise
repeat-consistency plus value parity against the fully eager tile helpers
(via _torchdynamo_orig_callable). Red on the unfixed merge (cudagraph
overwrite RuntimeError on the first decode), green with this fix.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
