Pickle.load do dispositivo GPU para CPU
#if you are using pickle load on a cpu device, from a gpu device
#you will need to override the pickle load functionality like this:
#note: if loading directly in torch, just add map_location='cpu' in load()
class CPU_Unpickler(pickle.Unpickler):
def find_class(self, module, name):
if module == 'torch.storage' and name == '_load_from_bytes':
return lambda b: torch.load(io.BytesIO(b), map_location='cpu')
else: return super().find_class(module, name)
#contents = pickle.load(f) becomes...
contents = CPU_Unpickler(f).load()
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