in config: "target": module type, vqvae_zc.Decoder/vqvae_diffusion.Decoder/vqvae_diffusion.Decoder2 "ckpt": path of checkpoint "ckpt_prefix": prefix to remove in ckpt state dict "device": device "params": dict of params
(config)
| 15 | from .vqvae_zc import VQVAE |
| 16 | |
| 17 | def new_module(config): |
| 18 | ''' |
| 19 | in config: |
| 20 | "target": module type, vqvae_zc.Decoder/vqvae_diffusion.Decoder/vqvae_diffusion.Decoder2 |
| 21 | "ckpt": path of checkpoint |
| 22 | "ckpt_prefix": prefix to remove in ckpt state dict |
| 23 | "device": device |
| 24 | "params": dict of params |
| 25 | ''' |
| 26 | if not "target" in config: |
| 27 | raise KeyError("Expected key `target` to instantiate.") |
| 28 | module, cls = config.get("target").rsplit(".", 1) |
| 29 | model = getattr(importlib.import_module(module, package=__package__), cls)(**config.get("params", dict())) |
| 30 | |
| 31 | device = config.get("device", "cpu") |
| 32 | model = model.to(device) |
| 33 | model.eval() |
| 34 | |
| 35 | if "ckpt" in config: |
| 36 | ckpt = torch.load(config.get("ckpt"), map_location='cpu') |
| 37 | prefix = config.get("ckpt_prefix", None) |
| 38 | if "state_dict" in ckpt: |
| 39 | ckpt = ckpt["state_dict"] |
| 40 | if prefix is not None: |
| 41 | ckpt = {k[len(prefix) + 1:]: v for k, v in ckpt.items() if k.startswith(prefix)} |
| 42 | model.load_state_dict(ckpt, strict=False) |
| 43 | del ckpt |
| 44 | return model |
| 45 | |
| 46 | def load_decoder_default(device=0, path="pretrained/vqvae/l1+ms-ssim+revd_percep.pt"): |
| 47 | # exp: load currently best decoder |