-
Notifications
You must be signed in to change notification settings - Fork 429
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
remove unused tensors from VK model's graph #4427
Conversation
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/4427
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit c09fe87 with merge base 889e5cb (): This comment was automatically generated by Dr. CI and updates every 15 minutes. |
This pull request was exported from Phabricator. Differential Revision: D60257047 |
Summary: Pull Request resolved: pytorch#4427 We implemented [operators fusion](pytorch#3769) (`conv+bn`) which fused `conv` and `bn`'s weights and biases, but the old parameters are not deleted. Hence we saw that VK model's size is nearly twice large as CPU's. As regards mobilenet_v2, before this diff CPU vs VK: 14M vs 22M. After this diff, both of them have 14M. Reviewed By: SS-JIA Differential Revision: D60257047
c5d02e3
to
9a5455d
Compare
This pull request was exported from Phabricator. Differential Revision: D60257047 |
1 similar comment
This pull request was exported from Phabricator. Differential Revision: D60257047 |
Summary: Pull Request resolved: pytorch#4427 We implemented [operators fusion](pytorch#3769) (`conv+bn`) which fused `conv` and `bn`'s weights and biases, but the old parameters are not deleted. Hence we saw that VK model's size is nearly twice large as CPU's. As regards mobilenet_v2, before this diff CPU vs VK: 14M vs 22M. After this diff, both of them have 14M. Reviewed By: SS-JIA Differential Revision: D60257047
9a5455d
to
0855797
Compare
Summary: Pull Request resolved: pytorch#4427 We implemented [operators fusion](pytorch#3769) (`conv+bn`) which fused `conv` and `bn`'s weights and biases, but the old parameters are not deleted. Hence we saw that VK model's size is nearly twice large as CPU's. As regards mobilenet_v2, before this diff CPU vs VK: 14M vs 22M. After this diff, both of them have 14M. Reviewed By: SS-JIA Differential Revision: D60257047
0855797
to
ca060d6
Compare
This pull request was exported from Phabricator. Differential Revision: D60257047 |
Summary: Pull Request resolved: pytorch#4427 We implemented [operators fusion](pytorch#3769) (`conv+bn`) which fused `conv` and `bn`'s weights and biases, but the old parameters are not deleted. Hence we saw that VK model's size is nearly twice large as CPU's. As regards mobilenet_v2, before this diff CPU vs VK: 14M vs 22M. After this diff, both of them have 14M. Reviewed By: SS-JIA Differential Revision: D60257047
ca060d6
to
c09fe87
Compare
This pull request was exported from Phabricator. Differential Revision: D60257047 |
This pull request has been merged in faeeca8. |
Summary:
We implemented operators fusion (
conv+bn
) which fusedconv
andbn
's weights and biases, but the old parameters are not deleted. Hence we saw that VK model's size is nearly twice large as CPU's.As regards mobilenet_v2, before this diff CPU vs VK: 14M vs 22M. After this diff, both of them have 14M.
Differential Revision: D60257047