import svrt
+# FIXME
+import resource
+
######################################################################
def generate_one_batch(s):
for b in range(0, self.nb_batches):
target = torch.LongTensor(self.batch_size).bernoulli_(0.5)
input = svrt.generate_vignettes(problem_number, target)
- acc += input.float().sum() / input.numel()
- acc_sq += input.float().pow(2).sum() / input.numel()
+ acc += input.sum() / input.numel()
+ acc_sq += (input * input).sum() / input.numel()
self.targets.append(target)
self.input_storages.append(svrt.compress(input.storage()))
if logger is not None: logger(self.nb_batches * self.batch_size, b * self.batch_size)
+ # FIXME
+ if resource.getrusage(resource.RUSAGE_SELF).ru_maxrss > 16e6:
+ print('Memory leak?!')
+ raise
+
self.mean = acc / self.nb_batches
self.std = sqrt(acc_sq / self.nb_batches - self.mean * self.mean)