in optimum/quanto/tensor/weights/qbytes.py [0:0]
def load_from_state_dict(state_dict, prefix, qtype, axis, size, stride, activation_qtype, missing_keys):
inner_tensors_dict = {}
missing = False
for name in ["_data", "_scale"]:
if prefix + name not in state_dict:
missing_keys.append(prefix + name)
missing = True
else:
inner_tensors_dict[name] = state_dict.pop(prefix + name)
if missing: # could not deserialize because of missing keys
return None
meta = {
"qtype": qtype.name,
"axis": str(axis),
"size": str(list(size)),
"stride": str(list(stride)),
"activation_qtype": "none" if activation_qtype is None else activation_qtype.name,
}
return WeightQBytesTensor.__tensor_unflatten__(inner_tensors_dict, meta, None, None)