List of commits:
Subject Hash Author Date (UTC)
add reset to auc estimator 333badd5489e538b0ee9b5441331322ba72d3981 Xiangru Lian 2019-01-08 21:17:22
add riemann auc estimator 8ce1b37008f10d6ca825728b1d0106b03bb0529d Xiangru Lian 2019-01-08 21:11:27
fix d4f0a50ffb6afea07df425d759fdf8460839d0ce Xiangru Lian 2019-01-07 22:27:56
add numpy support 2e10283edfc427ea4da6a76c8c3a6f85a44bace4 Xiangru Lian 2019-01-07 22:24:12
update fcfc8a26e275395688fb3fa50538f890c1f612e4 Xiangru Lian 2019-01-07 21:55:04
use markdown for readme f46e30761b4f361d5494484d9bdb20dc04a20d83 Xiangru Lian 2019-01-07 21:53:46
add readme a9a0b91ea0e0485039ea76b6b69c5f983815e8a3 Xiangru Lian 2019-01-07 21:52:31
fix 16a965862eaefa554a540fd2eeee26f73907d5dd Xiangru Lian 2019-01-07 21:37:12
fix setup.py 24e85045cc859ffa7d6f514c80257fde94c0794a Xiangru Lian 2019-01-07 21:35:15
compatible with setup.py 657782ac87ea9251f2e3726b483089eca5384caf Xiangru Lian 2019-01-07 21:33:48
initial commit 27cb0b3b4f5f20240af6d14ead4f373a1aaa5343 Xiangru Lian 2019-01-07 21:26:20
Update .gitignore 52642556fea807b773617938eecd2d9d17f34bc6 ikzk 2019-01-07 20:16:37
Commit 333badd5489e538b0ee9b5441331322ba72d3981 - add reset to auc estimator
Author: Xiangru Lian
Author date (UTC): 2019-01-08 21:17
Committer name: Xiangru Lian
Committer date (UTC): 2019-01-08 21:17
Parent(s): 8ce1b37008f10d6ca825728b1d0106b03bb0529d
Signing key:
Tree: 0672efd1abd5437164aca019ac44eecf99eae9eb
File Lines added Lines deleted
persia_pytorch_toolkit/meter_utils.py 5 2
File persia_pytorch_toolkit/meter_utils.py changed (mode: 100644) (index e641078..da129aa)
... ... class RiemannAUCMeter():
6 6 """ """
7 7 def __init__(self, num_bins=100000): def __init__(self, num_bins=100000):
8 8 self.num_bins = num_bins self.num_bins = num_bins
9 self.p_cnt = torch.zeros(self.num_bins, dtype=torch.long)
10 self.n_cnt = torch.zeros(self.num_bins, dtype=torch.long)
9 self.reset()
11 10
12 11 def add(self, outputs, labels): def add(self, outputs, labels):
13 12 """Outputs should be probabilities from 0 to 1.""" """Outputs should be probabilities from 0 to 1."""
 
... ... class RiemannAUCMeter():
31 30 except ZeroDivisionError: except ZeroDivisionError:
32 31 return 0 return 0
33 32
33 def reset(self):
34 self.p_cnt = torch.zeros(self.num_bins, dtype=torch.long)
35 self.n_cnt = torch.zeros(self.num_bins, dtype=torch.long)
36
34 37
35 38 if __name__ == "__main__": if __name__ == "__main__":
36 39 meter = RiemannAUCMeter() meter = RiemannAUCMeter()
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