def load_model(dirname, device, weights=None, half=False):
"""
Load a model from disk
"""
if not os.path.isdir(dirname) and os.path.isdir(
os.path.join(__dir__, "models", dirname)):
dirname = os.path.join(__dir__, "models", dirname)
if not weights: # take the latest checkpoint
weight_files = glob(os.path.join(dirname, "weights_*.tar"))
if not weight_files:
raise FileNotFoundError("no model weights found in '%s'" % dirname)
weights = max(
[int(re.sub(".*_([0-9]+).tar", "\\1", w)) for w in weight_files])
device = torch.device(device)
config = os.path.join(dirname, 'config.toml')
weights = os.path.join(dirname, 'weights_%s.tar' % weights)
model = Model(toml.load(config))
model.to(device)
state_dict = torch.load(weights, map_location=device)
new_state_dict = OrderedDict()
for k, v in state_dict.items():
name = k.replace('module.', '')
new_state_dict[name] = v
model.load_state_dict(new_state_dict)
if half: model = model.half()
model.eval()
return model
def load_model(dirname, device, weights=None):
"""
Load a model from disk
"""
if not weights: # take the latest checkpoint
weight_files = glob(os.path.join(dirname, "weights_*.tar"))
weights = max(
[int(re.sub(".*_([0-9]+).tar", "\\1", w)) for w in weight_files])
device = torch.device(device)
config = os.path.join(dirname, 'config.toml')
weights = os.path.join(dirname, 'weights_%s.tar' % weights)
model = Model(toml.load(config))
model.to(device)
model.load_state_dict(torch.load(weights, map_location=device))
model.eval()
return model
