pretrained

[06Liz]

const.py文件中，import os from pathlib import Path

Use environment variables to auto-detect whether we are running an a Compute Canada cluster:

Thanks to https://github.com/DM-Berger/unet-learn/blob/master/src/train/load.py for this trick.

COMPUTECANADA = False TMP = os.environ.get("SLURM_TMPDIR")

if TMP: COMPUTECANADA = True

if COMPUTECANADA: INPUT_FOLDER = Path(str(TMP)).resolve() / "work" / "inputs" MASK_FOLDER = Path(str(TMP)).resolve() / "work" / "inputs" / "masks" PRETRAINED_MODEL_FOLDER = Path(str(TMP)).resolve() / "work" / "trained_models" PRETRAINED_MODEL_DDPM_PATH = ( Path(str(TMP)).resolve() / "work" / "trained_models" / "ddpm" ) PRETRAINED_MODEL_VAE_PATH = ( Path(str(TMP)).resolve() / "work" / "trained_models" / "vae" ) PRETRAINED_MODEL_DECODER_PATH = ( Path(str(TMP)).resolve() / "work" / "trained_models" / "decoder" ) PRETRAINED_MODEL_VGG_PATH = ( Path(str(TMP)).resolve() / "work" / "trained_models" / "vgg16.pt" ) OUTPUT_FOLDER = Path(str(TMP)).resolve() / "work" / "outputs" else: INPUT_FOLDER = Path(file).resolve().parent.parent.parent / "data" / "IXI" MASK_FOLDER = Path(file).resolve().parent.parent / "masks" OASIS_FOLDER = Path(file).resolve().parent.parent.parent / "data" / "OASIS" PRETRAINED_MODEL_FOLDER = ( Path(file).resolve().parent.parent.parent / "data" / "trained_models" )这些预训练的模型都在哪里啊，数据在哪啊？