Error in quantize vicuna-7b model from fp16 to int8

[JackWeiw]

Describe the issue

use shape_inference.quant_pre_process to preprocess will result in error even if i set skip_optimization=True

after that, i use quantize_dynamic, it successfully quantize the model to int8, but it fails to load it back

To reproduce

Urgency

Urgent, paper diliver deadline is coming !

Platform

Linux

OS Version

ubuntu22.04

ONNX Runtime Installation

Released Package

ONNX Runtime Version or Commit ID

1.17

ONNX Runtime API

Python

Architecture

X64

Execution Provider

CUDA

Execution Provider Library Version

CUDA11.8

[xadupre]

Did you try to see if it works with onnxruntime==1.18?

[JackWeiw]

Did you try to see if it works with onnxruntime==1.18?

I switch to onnxruntime==1.18, there it still return the same error when i try to pre-process

if i simply use quantize_dynamic, it works fine, but it fails to check_model

I set op_version as default(14) when export from PyTorch, my torch version is torch2.3-cu11.8.
Do you have any insights?

[xadupre]

Are you using the latest onnx package?

[JackWeiw]

Are you using the latest onnx package?

I have updated onnx to 1.16.1, onnxruntime to 1.18.0, than it succeed in quantization

howerver, when i tried to run it in onnxruntime, it report

[github-actions]

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