def save(self, path):
path = os.path.expanduser(path)
os.makedirs(path, exist_ok=True)
try:
with open(os.path.join(path, "best_configure.json"), 'w') as f:
json.dump(self.tune_cfg, f)
logger.info("save config file of quantized model to path %s" %
path)
except IOError as e:
logger.error("Unable to save configure file and weights. %s" % e)
def save(self, root=None):
if not root:
root = cfg.default_workspace
root = os.path.abspath(os.path.expanduser(root))
os.makedirs(root, exist_ok=True)
try:
with open(os.path.join(root, "best_configure.json"), 'w') as f:
json.dump(self.tune_cfg, f)
logger.info("Save config file of quantized model at %s" % root)
except IOError as e:
logger.error("Unable to save configure file and weights. %s" % e)
def save(self, path):
path = os.path.expanduser(path)
os.makedirs(path, exist_ok=True)
try:
with open(os.path.join(path, "best_configure.yaml"), 'w') as f:
yaml.dump(self.tune_cfg, f, default_flow_style=False)
torch.save(self._model.state_dict(),
os.path.join(path, "best_model_weights.pt"))
logger.info(
"save config file and weights of quantized model to path %s" %
path)
except IOError as e:
logger.error("Unable to save configure file and weights. %s" % e)
def save(self, root=None):
if not root:
root = cfg.default_workspace
root = os.path.abspath(os.path.expanduser(root))
os.makedirs(root, exist_ok=True)
try:
with open(os.path.join(root, "best_configure.yaml"), 'w') as f:
yaml.dump(self.tune_cfg, f, default_flow_style=False)
torch.save(self._model.state_dict(),
os.path.join(root, "best_model_weights.pt"))
logger.info(
"Save config file and weights of quantized model at %s" % root)
except IOError as e:
logger.error("Unable to save configure file and weights. %s" % e)