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Add contiguous subgraph transformation threshold (#162192)

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Pull Request resolved: https://github.com/pytorch/pytorch/pull/162192
Approved by: https://github.com/coconutruben
This commit is contained in:
Gabriel Ferns
2025-09-06 02:48:00 +00:00
committed by PyTorch MergeBot
parent c3ceca2995
commit 20629b1619
2 changed files with 6 additions and 3 deletions
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6
torch/_inductor/utils.py
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@ -1842,7 +1842,7 @@ def use_contiguous(m: _IntLike, n: _IntLike, k: _IntLike) -> bool:
Check if we should use the contiguous subgraph transform.
This transform makes the second matrix contiguous before the matmul.
"""
decompose_k_threshold = config.triton.decompose_k_threshold
contiguous_threshold = config.rocm.contiguous_threshold
# Similar conditions to decompose_k but for contiguous transform
from torch._inductor.virtualized import V
@ -1851,8 +1851,8 @@ def use_contiguous(m: _IntLike, n: _IntLike, k: _IntLike) -> bool:
bool(torch.version.hip) # Only relevant on AMD
and V.graph.sizevars.statically_known_true(
sympy.And(
sympy.Ge(k, decompose_k_threshold * m),
sympy.Ge(k, decompose_k_threshold * n),
sympy.Ge(k, contiguous_threshold * m),
sympy.Ge(k, contiguous_threshold * n),
)
)
and not V.graph.aot_mode