def train_online(self, *args, **kwargs):
results = super().train_online(*args, **kwargs)
if results is not None:
results = save_weights_to_buffer(results)
return results
def __init__(self, model):
buf = save_weights_to_buffer(model)
self.cls, self.args, state = list(model.__reduce__())
self.state = ray.put(buf)
def train(self, *args, **kwargs):
results = super().train(*args, **kwargs)
if results is not None:
model, *stats = results
results = (save_weights_to_buffer(model), *stats)
return results
def __init__(self, model: ECD):
buf = save_weights_to_buffer(model)
self.cls = type(model)
self.args = model.get_args()
self.state = ray.put(buf)