Skip to content

BerneS-1849361/onnx-mlir-init-test

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

8 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

onnx-mlir-init-test

Links to get input images and postprocessed image

  1. Unet
  2. Alexnet
  3. resnet
  4. mobilenet-net

Steps to generate and run bin

  1. follow instructions from onnx-mlir-docker to setup onnx-mlir-docker
  2. create parent folder automation in path containerId:/workdir/
  3. create folder with name onnx-mlir_files, llvm-IR_files/raw etc etc (check ref-for-docker-folder-structure for list of all folders`
  4. use torchhub links to get proper input for all models.
  5. Update <model>.main.cpp -> static float img_data[] = {<input data as 1D array>} [line 16] and shape[] [line 18]
  6. if required use Netron to get input and output dimensions. Update img_data and input img dimension
  7. run cd auto_scripts
  8. run ./get_bin_abs.sh <filename> to copy files from local to docker and generate llvm IR, asm and then exec bin
  9. to regenerate only bin run ./get_bin_abs.sh <filename> bin
  10. this cmd will generate filename.output.txt file containing model output as 1D array.

TO-DO Use output array and get post processed image / data for all 4 models and comapre them.

Ref for docker folder structure

image

run ./delete_all_files_con.sh to delete all generated files from docker container and run ./delete_all_files_host.sh to delete all generated files from local

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • LLVM 67.7%
  • MLIR 32.3%