sd-pokemon-generator/dvc.yaml at main · RCdeWit/sd-pokemon-generator · GitHub

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stages:
  set_up_diffusers:
    cmd: |
      git clone --depth 1 --branch v0.14.0 https://github.com/huggingface/diffusers.git diffusers
      pip3.10 install -r "diffusers/examples/dreambooth/requirements.txt"
      accelerate config default
    outs:
    - diffusers:
        cache: false
  scrape_pokemon_images:
    cmd: python3 src/scrape_pokemon_images.py --params params.yaml
    deps:
    - src/scrape_pokemon_images.py
    outs:
    - data/external/pokemon
  download_pokemon_stats:
    cmd: kaggle datasets download -d brdata/complete-pokemon-dataset-gen-iiv -f Pokedex_Cleaned.csv -p data/external/
    outs:
    - data/external/Pokedex_Cleaned.csv
  resize_pokemon_images:
    cmd: python3 src/resize_pokemon_images.py --params params.yaml
    deps:
    - src/resize_pokemon_images.py
    - data/external/pokemon
    - data/external/Pokedex_Cleaned.csv
    outs:
    - data/processed/pokemon
    params:
    - base
    - data_etl
  train_lora:
    cmd: >
      accelerate launch --mps "diffusers/examples/dreambooth/train_dreambooth_lora.py"
      --pretrained_model_name_or_path=${train_lora.base_model}
      --instance_data_dir=${data_etl.train_data_path}
      --output_dir=${train_lora.lora_path}
      --instance_prompt='a pkmnlora pokemon'
      --resolution=512
      --train_batch_size=1
      --gradient_accumulation_steps=1
      --checkpointing_steps=500
      --learning_rate=${train_lora.learning_rate}
      --lr_scheduler='cosine'
      --lr_warmup_steps=0
      --max_train_steps=${train_lora.max_train_steps}
      --seed=${train_lora.seed}
    deps:
    - diffusers
    - data/processed/pokemon
    outs:
    - models/pkmnlora
    params:
    - data_etl
    - train_lora
  generate_text_to_image:
    cmd: python3 src/generate_text_to_image.py --params params.yaml
    outs:
    - outputs
    deps:
    - src/generate_text_to_image.py
    - models/pkmnlora
    params:
    - train_lora
    - generate_text_to_image