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Running
on
Zero
Running
on
Zero
File size: 1,768 Bytes
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import os
import torch
from omegaconf import OmegaConf
from ldm.util import instantiate_from_config
def get_state_dict(d):
return d.get('state_dict', d)
def load_state_dict(ckpt_path, location='cpu'):
_, extension = os.path.splitext(ckpt_path)
if extension.lower() == ".safetensors":
import safetensors.torch
state_dict = safetensors.torch.load_file(ckpt_path, device=location)
else:
state_dict = get_state_dict(torch.load(ckpt_path, map_location=torch.device(location)))
state_dict = get_state_dict(state_dict)
print(f'Loaded state_dict from [{ckpt_path}]')
return state_dict
def load_ckpt(model, state_dict, strict=True, input_channel_copy_indices=None):
input_channel_key = "local_adapter.feature_extractor.pre_extractor.0.weight"
model_state_dict = model.state_dict()
if input_channel_key in model_state_dict and input_channel_key in state_dict:
model_shape = model_state_dict[input_channel_key].shape
shape = state_dict[input_channel_key].shape
if model_shape != shape:
if input_channel_copy_indices is None:
state_dict[input_channel_key] = state_dict[input_channel_key][:, :model_shape[1], :, :]
else:
cout, cin, h, w = model_shape
weight = state_dict[input_channel_key].view(cout, -1, cin//3, h, w)
weight = weight[:, input_channel_copy_indices].view(cout, cin, h, w)
state_dict[input_channel_key] = weight
model.load_state_dict(state_dict, strict=strict)
def create_model(config_path):
config = OmegaConf.load(config_path)
model = instantiate_from_config(config.model).cpu()
print(f'Loaded model config from [{config_path}]')
return model
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