Last active
October 24, 2017 03:26
-
-
Save EthanRosenthal/ae1a6da04639292db28f345bec023b8a to your computer and use it in GitHub Desktop.
Speed test for explicit logistic losses
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| from time import time | |
| import pandas as pd | |
| import torch | |
| from torch import nn | |
| from torch.nn import functional as F | |
| from torch.autograd import Variable | |
| def hand(pred, obs): | |
| obs = (obs + 1) / 2 | |
| return F.binary_cross_entropy_with_logits(pred, | |
| obs, | |
| size_average=True) | |
| def relu(pred, obs): | |
| obs = F.relu(obs) | |
| return F.binary_cross_entropy_with_logits(pred, | |
| obs, | |
| size_average=True) | |
| def clamp(pred, obs): | |
| obs = torch.clamp(obs, 0, 1) | |
| return F.binary_cross_entropy_with_logits(pred, | |
| obs, | |
| size_average=True) | |
| def setup(): | |
| pred = torch.rand(10000, 1) | |
| obs = (torch.rand(10000, 1) > 0.5).float() | |
| layer = nn.Linear(1, 1) | |
| layer.weight.data.normal_(0, 1) | |
| pred = layer(Variable(pred)) | |
| obs = Variable(obs) | |
| return pred, obs | |
| if __name__ == '__main__': | |
| n_iters = 1000 | |
| times = [] | |
| for func, name in zip((hand, relu, clamp), | |
| ('hand', 'relu', 'clamp')): | |
| func_times = 0 | |
| torch.manual_seed(0) | |
| losses = 0 | |
| for _ in range(n_iters): | |
| pred, obs = setup() | |
| t0 = time() | |
| loss = func(pred, obs) | |
| loss.backward() | |
| losses += loss.data[0] | |
| t1 = time() | |
| func_times += t1 - t0 | |
| times.append((name, | |
| func_times / n_iters * 1000, | |
| losses / n_iters)) | |
| df = pd.DataFrame(times, columns=['function', 'time (ms)', 'loss']) | |
| df = df.sort_values('time (ms)', ascending=False) | |
| print(df) | |
| """ | |
| function time (ms) loss | |
| 1 relu 1.802599 0.771223 | |
| 2 clamp 1.799747 0.771223 | |
| 0 hand 1.761629 0.764366 | |
| """ |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment