Skip to content

Adding mixed quantization support #14134

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.

Sign up for GitHub

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

Jump to bottom
Open
wants to merge 2 commits into
base: main
Choose a base branch
from
Open

Adding mixed quantization support #14134

wants to merge 2 commits into from

Conversation

mgiordy
Copy link

@mgiordy mgiordy commented Sep 9, 2025

Summary:

Context

This Diff adds support for mixed quantization operators in Executorch. Now weights and biases can be quantized, while inputs and activations are kept in floating point.

In this diff

  1. Op nodes are returned from each pattern matching
  2. Dequantize nodes are bypassed if not needed in the final graph.

Differential Revision: D81519735

@pytorch-bot PyTorch Bot
Copy link

pytorch-bot bot commented Sep 9, 2025 •
edited
Loading

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/14134

Note: Links to docs will display an error until the docs builds have been completed.

✅ No Failures

As of commit 2ffaef2 with merge base 86e61bf (image):
💚 Looks good so far! There are no failures yet. 💚

This comment was automatically generated by Dr. CI and updates every 15 minutes.

@meta-cla meta-cla bot added the CLA Signed This label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed. label Sep 9, 2025
@facebook-github-bot
Copy link
Contributor

This pull request was exported from Phabricator. Differential Revision: D81519735

@github-actions GitHub Actions
Copy link

github-actions bot commented Sep 9, 2025

This PR needs a release notes: label

If your change should be included in the release notes (i.e. would users of this library care about this change?), please use a label starting with release notes:. This helps us keep track and include your important work in the next release notes.

To add a label, you can comment to pytorchbot, for example
@pytorchbot label "release notes: none"

For more information, see
https://github.com/pytorch/pytorch/wiki/PyTorch-AutoLabel-Bot#why-categorize-for-release-notes-and-how-does-it-work.

mgiordy pushed a commit to mgiordy/executorch that referenced this pull request Sep 10, 2025
@facebook-github-bot
Adding mixed quantization support (pytorch#14134)
789bf47 
Summary:

# Context
This Diff adds support for mixed quantization operators in Executorch. Now weights and biases can be quantized, while inputs and activations are kept in floating point.

# In this diff
1. Op nodes are returned from each pattern matching
2. Dequantize nodes are bypassed if not needed in the final graph.

Differential Revision: D81519735
@facebook-github-bot
Adding mixed quantization support (pytorch#14134)
20e4ab8 
Summary:
Pull Request resolved: pytorch#14134

# Context
This Diff adds support for mixed quantization operators in Executorch. Now weights and biases can be quantized, while inputs and activations are kept in floating point.

# In this diff
1. Op nodes are returned from each pattern matching
2. Dequantize nodes are bypassed if not needed in the final graph.

Differential Revision: D81519735
@facebook-github-bot
Copy link
Contributor

This pull request was exported from Phabricator. Differential Revision: D81519735

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Reviewers
No reviews
Assignees
No one assigned
Labels
CLA Signed This label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed. fb-exported
Projects
None yet
Milestone
No milestone
Development

Successfully merging this pull request may close these issues.
2 participants
@mgiordy @facebook-github-bot