pretrained #10
Description
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？