remove transpose addmm weights hack #358
Closed
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
facebook-github-bot
added
the
CLA Signed
|
This pull request was exported from Phabricator. Differential Revision: D49129704 |
|
This pull request was exported from Phabricator. Differential Revision: D49129704 |
mcr229
force-pushed
the
export-D49129704
branch
from
2c68280 to
a48a8bb
Compare
|
This pull request was exported from Phabricator. Differential Revision: D49129704 |
mcr229
force-pushed
the
export-D49129704
branch
from
a48a8bb to
c0fc7b3
Compare
|
This pull request was exported from Phabricator. Differential Revision: D49129704 |
mcr229
force-pushed
the
export-D49129704
branch
from
c0fc7b3 to
975e03f
Compare
|
This pull request was exported from Phabricator. Differential Revision: D49129704 |
mcr229
force-pushed
the
export-D49129704
branch
from
975e03f to
0338e22
Compare
|
This pull request was exported from Phabricator. Differential Revision: D49129704 |
mcr229
force-pushed
the
export-D49129704
branch
from
0338e22 to
2db4474
Compare
Differential Revision: D49068312 fbshipit-source-id: 6709b38f3be9da89f51db78740e9533e220a4a04
Differential Revision: D49301134 fbshipit-source-id: ccd56ffbef578989d2b3436adc0fe1e92a0431ce
Summary: Pull Request resolved: pytorch/executorch#358 ### Background A common pattern we when encountering addmm is that weights are permuted before given to addmm. This is because generally for torch.nn.Linear, the input shape and weight shape are given as such: ``` input: (*, in_features) weight: (out_features,in_features) ``` while the input shape and weight shape of addmm are the following: ``` input1 (input): (*, in_features) input2 (weight): (in_features, out_features) ``` so when decomposing nn.Linear to addmm, the weights go through a permute node to comply with addmm's shapes ### XNNPACK Status XNNPACK can handle both the transpose and normal weight shape, however it requires a flag for whether or not the weights are transposed. So an easy optimization is to skip the permute node and use the flag. ### Change and Motivation Currently, we have hardcoded some of this optimization logic directly into serialization. I believe that serialization should not be aware of these optimizations, which is why I am removing this logic from within serialization. Instead this logic should be performed completely by the addmm --> linear pass which recomposes permute + addmm into a singular linear. We should no longer rely on serialization logic to perform this logic (Right now its errorneous and causing a bug). Reviewed By: kirklandsign Differential Revision: D49129704 fbshipit-source-id: 9c41a2b4433c62b06e703b98ed8e0442275c3501
|
This pull request was exported from Phabricator. Differential Revision: D49129704 |
mcr229
force-pushed
the
export-D49129704
branch
from
2db4474 to
411273d
Compare
|
This pull request has been merged in 2b7eb62. |
Gasoonjia
pushed a commit
that referenced
this pull request
Jul 30, 2024
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Summary:
Background
A common pattern we when encountering addmm is that weights are permuted before given to addmm. This is because generally for torch.nn.Linear, the input shape and weight shape are given as such:
while the input shape and weight shape of addmm are the following:
so when decomposing nn.Linear to addmm, the weights go through a permute node to comply with addmm's shapes
XNNPACK Status
XNNPACK can handle both the transpose and normal weight shape, however it requires a flag for whether or not the weights are transposed. So an easy optimization is to skip the permute node and use the flag.
Change and Motivation
Currently, we have hardcoded some of this optimization logic directly into serialization. I believe that serialization should not be aware of these optimizations, which is why I am removing this logic from within serialization. Instead this logic should be performed completely by the addmm --> linear pass which recomposes permute + addmm into a singular linear. We should no longer rely on serialization logic to perform this logic (Right now its errorneous and causing a bug).
Reviewed By: kirklandsign
Differential Revision: D49129704