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10 minutes to run stable diffusion from scratch on Windows

Downloading stable diffusion and related environment online can be very time-consuming. This note is intended to address this issue for quick testing on new device. If you want to test the latest resources (e.g. latest diffuser, onnxruntime etc.), it will not be a good reference.

  1. Download all files

    File Name Details
    Olive_SD1.5.zip onnx fp16 models for sd v1.5
    sdDML1.5.tar.gz packed conda enviroment including onxxruntime directml 1.15
    test_ml.py a python scirpt to run sd model by using DirectML as backend
    latents_fp16.npy latents data to get the same output image each time
    Anaconda3-2019.10-Windows-x86_64.exe anaconda app

  2. Click Anaconda3***.exe to install conda environment

  3. Unzip sdDML1.5.tar.gz

  4. Open anaconda prompt command and go to folder sdDML1.5

  5. Run the commands below
    .\Scripts\activate.bat

    .\ Scripts \conda-unpack.exe

    conda list

    Then, you can double check some key packages used for stable diffusion as below

    diffusers                 0.16.1                   pypi_0    pypi
olive-ai                  0.2.1                    pypi_0    pypi
onnx                      1.13.1                   pypi_0    pypi
onnxruntime-directml      1.15.0                   pypi_0    psypi

  6. Go to the folder where has test_dml.py, and run the script
    python test_dml.py

    Note, please point out the path where sd model is located in the command before testing.

usage: test_dml.py [-h] [--model_dir MODEL_DIR] [--latents_path LATENTS_PATH] [--prompt PROMPT]
                   [--num_images NUM_IMAGES] [--batch_size BATCH_SIZE] [--num_inference_steps NUM_INFERENCE_STEPS]
                   [--dynamic_dims] [--enable_profiling] [--enable_intermediate_model]

optional arguments:
  -h, --help            show this help message and exit
  --model_dir MODEL_DIR
                        folder of stable diffusion
  --latents_path LATENTS_PATH
                        file of latents
  --prompt PROMPT       prompt
  --num_images NUM_IMAGES
                        Number of images to generate
  --batch_size BATCH_SIZE
                        Number of images to generate per batch
  --num_inference_steps NUM_INFERENCE_STEPS
                        Number of steps in diffusion process
  --dynamic_dims        Disable static shape optimization
  --enable_profiling    To save onnx profiling file
  --enable_intermediate_model
                        To save intermediate graph optimized by onnxruntime

  1. local env table

    env Name Details
    sdov openvino 2022.3
    onnxov openvino 2023.0