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[common] Generalized MXFP8 gated kernels w.r.t. input tensor dimensions #1449
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ptrendx
merged 17 commits into
NVIDIA:release_v2.0
from
Oleg-Goncharov:pr_mxfp8_gated_scales_fix
Feb 5, 2025
Merged
[common] Generalized MXFP8 gated kernels w.r.t. input tensor dimensions #1449
ptrendx
merged 17 commits into
NVIDIA:release_v2.0
from
Oleg-Goncharov:pr_mxfp8_gated_scales_fix
Feb 5, 2025
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Signed-off-by: Oleg Goncharov <ogoncharov@nvidia.com>
for more information, see https://pre-commit.ci
timmoon10
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Feb 1, 2025
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LGTM, pending testing. Started pipeline 23308831.
timmoon10
reviewed
Feb 1, 2025
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>
for more information, see https://pre-commit.ci
ptrendx
approved these changes
Feb 2, 2025
Signed-off-by: Oleg Goncharov <ogoncharov@nvidia.com>
Signed-off-by: Oleg Goncharov <ogoncharov@nvidia.com>
for more information, see https://pre-commit.ci
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>
for more information, see https://pre-commit.ci
Signed-off-by: Oleg Goncharov <ogoncharov@nvidia.com>
Signed-off-by: Oleg Goncharov <ogoncharov@nvidia.com>
for more information, see https://pre-commit.ci
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>
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Description
This PR lifts the restrictions on the shape of the input tensor for gated MXFP8 fused kernels. Similar to PR#1437, it allows an arbitrary number of rows (or the product of all tensor dimensions except the last of high-dimensional tensors).
The number of columns (or the dimensionality of the last dimension of high-dimensional tensors) must be a multiple of 32.
Type of change
Changes
isFullTile
requirement in thequantize_gated
function.gate-
part of the gated output tensor.[128,4]
for row-wise and[4,128]
for column-wise scaling.exp2f_rcp
function in the testing suites, so it returns1.0
if thebiased_exp==0
to avoidNaN
in theamax=0
scenario.NVTE_CHECK
in theCheckScaleTensorShape
of thetransformer_engine.cpp
to suppress errors generated for the tensor shapes that are now supported.gate-
part of the input/output tensors.Checklist: