I’m trying to implement
dynamic_decode with pytorch 0.3. Due to uncertain recursive times, I would like to run the model in parallel and then gather the outputs like that.
def f(model, input, queue): queue.put(model(input)) for i in range(3): p[i] = Process(f, args=(model, input[i], queue[i]) ... # run the processes... for q in queue: output[i] = q.get()
Variable has no attribute
It seems to be a feature brought by version 0.4 but I still wonder if there is any correct way to do that with 0.3.1. As a comparison, tensorflow uses a
while_loop which supports multi workers.