pytorch / pytorch/executorch

compile error"Vulkan backend does not support quantization at the moment"

Open
#7,132 3 comments 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

module: vulkan triaged
Dominant language
Python
Stars
5k
Forks
1.2k
Avg merge
2d 10h
Merged PRs (30d)
581

Description

🐛 Describe the bug

when I compile the pte file from llama-7b-chat as indicated by "https://pytorch.org/executorch/stable/build-run-vulkan.html", I find that the generated ptr file size is too big to run on the edge devices. So I tried to use quantization to the Vulkan bankend. the command is as follows:
python -m examples.models.llama2.export_llama --disable_dynamic_shape --vulkan -kv --use_sdpa_with_kv_cache --checkpoint ~/Llama-2-7b-chat/consolidated.00.pth --params ~/Llama-2-7b-chat/params.json -d fp32 -X -qmode 8da4w --group_size 128 --max_seq_length 1024
then it was generated the error as follows:
Vulkan backend does not support quantization at the moment
I tried to generate the pte file at executor v0.4.0
Conld you help me fix the issue?
Thank you in advanced

Versions

executorvh v0.4.0

cc @SS-JIA @manuelcandales

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start with the examples.models.llama2.export_llama entry point and the Vulkan build instructions linked in the report. Reproduce the command with executor v0.4.0 and trace where the explicit quantization rejection occurs. Done means the quantized Llama export completes for Vulkan and produces a PTE suitable for the reported edge-device use case.

Written by the indexing model from the issue text.

Assessment

Tech stack
python, pytorch
Domain
embedded-iot, machine-learning
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
35/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.