import torch
from math import sqrt
-from torch.multiprocessing import Pool, cpu_count
+from torch import multiprocessing
from torch import Tensor
from torch.autograd import Variable
for b in range(0, self.nb_batches):
mp_args.append( [ problem_number, batch_size, seeds[b] ])
- # self.data = []
- # for b in range(0, self.nb_batches):
- # self.data.append(generate_one_batch(mp_args[b]))
+ self.data = []
+ for b in range(0, self.nb_batches):
+ self.data.append(generate_one_batch(mp_args[b]))
+
+ # Weird thing going on with the multi-processing, waiting for more info
- self.data = Pool(cpu_count()).map(generate_one_batch, mp_args)
+ # pool = multiprocessing.Pool(multiprocessing.cpu_count())
+ # self.data = pool.map(generate_one_batch, mp_args)
acc = 0.0
acc_sq = 0.0