Skip to content

Conversation

@pytorchbot
Copy link
Collaborator

This PR was created by the merge bot to help merge the original PR into the main branch.
ghstack PR number: #17106 by @SS-JIA
^ Please use this as the source of truth for the PR details, comments, and reviews
ghstack PR base: https://github.com/pytorch/executorch/tree/gh/SS-JIA/399/base
ghstack PR head: https://github.com/pytorch/executorch/tree/gh/SS-JIA/399/head
Merge bot PR base: https://github.com/pytorch/executorch/tree/gh/SS-JIA/405/orig
Merge bot PR head: https://github.com/pytorch/executorch/tree/gh/SS-JIA/399/orig
Differential Revision: D92061370
@diff-train-skip-merge

…perators

Pull Request resolved: #17106

Implemented quantize_per_tensor and dequantize_per_tensor GLSL shaders and C++
dispatch logic to support the new single-dimension packed INT8 layouts
(kPackedInt8_4W, kPackedInt8_4C, kPackedInt8_4H). These operators enable
conversion between floating-point tensors and packed int8 representations with
per-tensor scale and zero-point parameters.

The implementation includes:

- GLSL shaders: quantize_per_tensor and dequantize_per_tensor with support for
  both texture->buffer and buffer->buffer data flows, including
  GL_EXT_debug_printf statements for debugging
- QuantizeDequantize.cpp: Added dispatch functions for the new layouts and
  registered etvk.q_dq_8bit_per_tensor.default operator
- Test infrastructure: Created q_dq_8bit_per_tensor test binary with DEBUG_MODE
  support and reference CPU implementation for validation

The shaders implement the quantization formula

```
Q = clamp(round(x/scale) + zp, -128, 127)
```

and dequantization formula

```
x' = (Q - zp) \* scale
```

with proper int8 packing/unpacking using little-endian byte ordering and sign
extension.


ghstack-source-id: 338638544
@exported-using-ghexport

Differential Revision: [D92061370](https://our.internmc.facebook.com/intern/diff/D92061370/)
@pytorch-bot
Copy link

pytorch-bot bot commented Feb 5, 2026

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/17261

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

❌ 1 New Failure, 76 Pending, 1 Unrelated Failure

As of commit 1781382 with merge base 1cffd23 (image):

NEW FAILURE - The following job has failed:

FLAKY - The following job failed but was likely due to flakiness present on trunk:

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 Feb 5, 2026
@SS-JIA SS-JIA merged commit 694f9b8 into gh/SS-JIA/405/orig Feb 5, 2026
159 of 173 checks passed
@SS-JIA SS-JIA deleted the gh/SS-JIA/399/orig branch February 5, 2026 23:57
SS-JIA pushed a commit that referenced this pull request Feb 6, 2026
…perators (#17261)

Implemented quantize_per_tensor and dequantize_per_tensor GLSL shaders
and C++ dispatch logic to support the new single-dimension packed INT8 layouts
(kPackedInt8_4W, kPackedInt8_4C, kPackedInt8_4H). These operators enable
conversion between floating-point tensors and packed int8 representations with
per-tensor scale and zero-point parameters.

The implementation includes:
- GLSL shaders: quantize_per_tensor and dequantize_per_tensor with support for
  both texture->buffer and buffer->buffer data flows, including GL_EXT_debug_printf
  statements for debugging
- QuantizeDequantize.cpp: Added dispatch functions for the new layouts and
  registered etvk.q_dq_8bit_per_tensor.default operator
- Test infrastructure: Created q_dq_8bit_per_tensor test binary with DEBUG_MODE
  support and reference CPU implementation for validation

The shaders implement the quantization formula Q = clamp(round(x/scale) + zp, -128, 127)
and dequantization formula x' = (Q - zp) * scale, with proper int8 packing/unpacking
using little-endian byte ordering and sign extension.

Differential Revision: [D92061370](https://our.internmc.facebook.com/intern/diff/D92061370/)

[ghstack-poisoned]
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Labels

CLA Signed This label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed.

Projects

None yet

Development

Successfully merging this pull request may close these issues.

2 participants