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import torch | |
from PIL import Image | |
from pathlib import Path | |
from omegaconf import OmegaConf | |
from scripts.demo.streamlit_helpers import ( | |
load_model_from_config, | |
get_sampler, | |
get_batch, | |
do_sample, | |
) | |
def load_config_and_model(ckpt: Path): | |
if (ckpt.parent.parent / "configs").exists(): | |
config_path = list((ckpt.parent.parent / "configs").glob("*-project.yaml"))[0] | |
else: | |
config_path = list( | |
(ckpt.parent.parent.parent / "configs").glob("*-project.yaml") | |
)[0] | |
config = OmegaConf.load(config_path) | |
model, msg = load_model_from_config(config, ckpt) | |
return config, model | |
def load_sampler(sampler_cfg): | |
return get_sampler(**sampler_cfg) | |
def load_batch(): | |
pass | |
class DiffusionEngine: | |
def __init__(self, cfg) -> None: | |
self.cfg = cfg | |
def sample(self): | |
pass | |