Spaces:
Running
Running
File size: 2,060 Bytes
c4c7cee |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 |
import sys
import os
from models.networks.mlp import GeoAdaLNMLP
from huggingface_hub import PyTorchModelHubMixin
import torch
import argparse
models_overrides = {
"YFCC100M_geoadalnmlp_r3_small_sigmoid_flow_riemann_10M_10M": "YFCC100M_geoadalnmlp_r3_small_sigmoid_flow_riemann",
"iNaturalist_geoadalnmlp_r3_small_sigmoid_flow_riemann_-7_3": "iNaturalist_geoadalnmlp_r3_small_sigmoid_flow_riemann",
"osv_5m_geoadalnmlp_r3_small_sigmoid_flow_riemann_-7_3": "osv_5m_geoadalnmlp_r3_small_sigmoid_flow_riemann",
}
class Plonk(
GeoAdaLNMLP,
PyTorchModelHubMixin,
repo_url="https://github.com/nicolas-dufour/plonk",
tags=["plonk", "geolocalization", "diffusion"],
license="mit",
):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
def upload_model(checkpoint_dir, repo_name):
import hydra
from omegaconf import OmegaConf
hydra.initialize(version_base=None, config_path=f"../configs")
cfg = hydra.compose(
config_name="config",
overrides=[
f"exp={models_overrides[checkpoint_dir]}",
],
)
network_config = cfg.model.network
serialized_network_config = OmegaConf.to_container(network_config, resolve=True)
print(serialized_network_config)
del serialized_network_config["_target_"]
model = Plonk(**serialized_network_config)
ckpt = torch.load(f"checkpoints/{checkpoint_dir}/last.ckpt")
ckpt_state_dict = ckpt["state_dict"]
ckpt_state_dict = {k: v for k, v in ckpt_state_dict.items() if "ema_network" in k}
ckpt_state_dict = {
k.replace("ema_network.", ""): v for k, v in ckpt_state_dict.items()
}
model.load_state_dict(ckpt_state_dict)
model.push_to_hub(repo_name, commit_message="Fixed ckpt keys")
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--checkpoint_dir", type=str, required=True)
parser.add_argument("--repo_name", type=str, required=True)
args = parser.parse_args()
upload_model(args.checkpoint_dir, args.repo_name)
|