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fix(nixl): replay strided views on inference #3113

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Merged
S1ro1 merged 2 commits into from
Jul 23, 2026
Merged

fix(nixl): replay strided views on inference #3113

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d7a4adb
fix(nixl): replay strided views on inference
S1ro1 Jul 22, 2026
c95589c
Merge branch 'main' into fix/nixl-replay-strided-views
S1ro1 Jul 23, 2026
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9 changes: 5 additions & 4 deletions src/prime_rl/trainer/rl/broadcast/nixl/graph.py
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Original file line number Diff line number Diff line change
Expand Up @@ -92,9 +92,10 @@ def is_view_of(value: torch.Tensor, root: torch.Tensor) -> bool:
def plan_tensor_replay(shape: tuple[int, ...], dtype: torch.dtype, ops: OperationChain) -> TensorReplayPlan:
"""Resolve a directly transferable source view and local replay suffix.

The prefix must remain a same-dtype view of the trainer root and can
therefore be addressed by RDMA. The first materializing or dtype-changing
operation and everything after it is replayed on the receive arena.
The prefix must remain a contiguous, same-dtype view of the trainer root
and can therefore be transferred in large RDMA runs. The first strided,
materializing, or dtype-changing operation and everything after it is
replayed on the receive arena.
"""
root = torch.empty(shape, dtype=dtype, device="meta")
prefix_len = 0
Expand All @@ -105,7 +106,7 @@ def plan_tensor_replay(shape: tuple[int, ...], dtype: torch.dtype, ops: Operatio
if candidate_len < len(ops) and ops[candidate_len].name == "tuple_getitem":
continue
candidate = apply_chain(root, ops[:candidate_len])
if candidate.dtype != dtype or not is_view_of(candidate, root):
if candidate.dtype != dtype or not is_view_of(candidate, root) or not candidate.is_contiguous():
break
prefix_len = candidate_len
source_view = candidate
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