Does Pytorch-Lightning have a multiprocessing (or Joblib) module?

Question

I have been googling around but can't seem to find if there is a multiprocessing module available in Pytorch-Lightning, just like how Pytorch has a torch.multiprocessing module.

Does anyone know if Pytorch-Lightning has this (or a Joblib similar) module? I am looking for a Pytorch-Lightning module which allows me to parallelize over multiple GPUs

Many thanks in advance.

Edit: To be more specific, I am looking for a multiprocessing module in Pytorch-Lightning which allows me to parallelize over multiple GPUs on non-neural network computations, such as:

import numpy as np
import torch
from torch.multiprocessing import Pool

X = np.array([[1, 3, 2, 3], [2, 3, 5, 6], [1, 2, 3, 4]])
X = torch.DoubleTensor(X)

def X_power_func(j):
    X_power = X.cuda()**j
    return X_power

if __name__ == '__main__':
  with Pool(processes = 2) as p:   # Parallelizing over 2 GPUs
    results = p.map(X_power_func, range(4))

results

Answer 1

Yes, basically all you have to do is to provideTrainer with appropriate argument gpus=N and specify backend:

# train on 8 GPUs (same machine (ie: node))
trainer = Trainer(gpus=8, distributed_backend='ddp')

# train on 32 GPUs (4 nodes)
trainer = Trainer(gpus=8, distributed_backend='ddp', num_nodes=4)

You can read more about it in multi-GPU training documentation .

EDIT:

What you were actually looking for is distributed module instead of multiprocessing , torch.distributed.DistributedDataParallel is usually recommended for parallelizing over multiple GPUs.