You are viewing a plain text version of this content. The canonical link for it is here.
Posted to commits@mxnet.apache.org by jx...@apache.org on 2017/09/20 20:04:12 UTC
[incubator-mxnet] branch master updated: Increase the tolerance
(#7937)
This is an automated email from the ASF dual-hosted git repository.
jxie pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git
The following commit(s) were added to refs/heads/master by this push:
new a7fe0d3 Increase the tolerance (#7937)
a7fe0d3 is described below
commit a7fe0d33f3db2745cf4ece952d2ef4e0b9336de0
Author: Gautam Kumar <ga...@fb.com>
AuthorDate: Wed Sep 20 13:04:09 2017 -0700
Increase the tolerance (#7937)
---
tests/python/unittest/test_operator.py | 16 ++++++++--------
1 file changed, 8 insertions(+), 8 deletions(-)
diff --git a/tests/python/unittest/test_operator.py b/tests/python/unittest/test_operator.py
index 0c528e0..fa73584 100644
--- a/tests/python/unittest/test_operator.py
+++ b/tests/python/unittest/test_operator.py
@@ -903,28 +903,28 @@ def test_batchnorm_training():
mean_std = [mx.nd.array(rolling_mean).tostype(stype), mx.nd.array(rolling_std).tostype(stype)]
test = mx.symbol.BatchNorm_v1(data, fix_gamma=True)
- check_numeric_gradient(test, in_location, mean_std, numeric_eps=1e-2, rtol=0.16)
+ check_numeric_gradient(test, in_location, mean_std, numeric_eps=1e-2, rtol=0.16, atol=1e-4)
test = mx.symbol.BatchNorm(data, fix_gamma=True)
- check_numeric_gradient(test, in_location, mean_std, numeric_eps=1e-2, rtol=0.16)
+ check_numeric_gradient(test, in_location, mean_std, numeric_eps=1e-2, rtol=0.16, atol=1e-4)
test = mx.symbol.BatchNorm_v1(data, fix_gamma=True, use_global_stats=True)
- check_numeric_gradient(test, in_location, mean_std, numeric_eps=1e-2, rtol=0.16)
+ check_numeric_gradient(test, in_location, mean_std, numeric_eps=1e-2, rtol=0.16, atol=1e-4)
test = mx.symbol.BatchNorm(data, fix_gamma=True, use_global_stats=True)
- check_numeric_gradient(test, in_location, mean_std, numeric_eps=1e-2, rtol=0.16)
+ check_numeric_gradient(test, in_location, mean_std, numeric_eps=1e-2, rtol=0.16, atol=1e-4)
test = mx.symbol.BatchNorm_v1(data, fix_gamma=False)
- check_numeric_gradient(test, in_location, mean_std, numeric_eps=1e-2, rtol=0.16)
+ check_numeric_gradient(test, in_location, mean_std, numeric_eps=1e-2, rtol=0.16, atol=1e-4)
test = mx.symbol.BatchNorm(data, fix_gamma=False)
- check_numeric_gradient(test, in_location, mean_std, numeric_eps=1e-2, rtol=0.16)
+ check_numeric_gradient(test, in_location, mean_std, numeric_eps=1e-2, rtol=0.16, atol=1e-4)
test = mx.symbol.BatchNorm_v1(data, fix_gamma=False, use_global_stats=True)
- check_numeric_gradient(test, in_location, mean_std, numeric_eps=1e-2, rtol=0.16)
+ check_numeric_gradient(test, in_location, mean_std, numeric_eps=1e-2, rtol=0.16, atol=1e-4)
test = mx.symbol.BatchNorm(data, fix_gamma=False, use_global_stats=True)
- check_numeric_gradient(test, in_location, mean_std, numeric_eps=1e-2, rtol=0.16)
+ check_numeric_gradient(test, in_location, mean_std, numeric_eps=1e-2, rtol=0.16, atol=1e-4)
# Test varying channel axis
dim = len(shape)
--
To stop receiving notification emails like this one, please contact
['"commits@mxnet.apache.org" <co...@mxnet.apache.org>'].