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Posted to commits@mxnet.apache.org by la...@apache.org on 2020/11/08 02:32:17 UTC
[incubator-mxnet] branch master updated: Mark
test_batchnorm_with_type as flaky (#19492)
This is an automated email from the ASF dual-hosted git repository.
lausen 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 545e117 Mark test_batchnorm_with_type as flaky (#19492)
545e117 is described below
commit 545e11712d8860853c7b7a3dbc0318000250bbfe
Author: Leonard Lausen <la...@amazon.com>
AuthorDate: Sun Nov 8 02:30:35 2020 +0000
Mark test_batchnorm_with_type as flaky (#19492)
[2020-11-06T21:37:09.831Z] # V2, 1D
[2020-11-06T21:37:09.831Z] for fix_gamma, cudnn_off in itertools.product(bools, bools):
[2020-11-06T21:37:09.831Z] sym = mx.sym.BatchNorm(name='norm', fix_gamma=fix_gamma, cudnn_off=cudnn_off)
[2020-11-06T21:37:09.831Z] > check_consistency(sym, ctx_list_v2_1D)
[...]
[2020-11-06T21:37:09.831Z] E AssertionError:
[2020-11-06T21:37:09.831Z] E Items are not equal:
[2020-11-06T21:37:09.831Z] E Error 8317.657381 exceeds tolerance rtol=1.000000e-05, atol=1.000000e-20 (mismatch 50.000000%).
[2020-11-06T21:37:09.831Z] E Location of maximum error: (0,), a=-0.00000000, b=-0.00000000
[2020-11-06T21:37:09.831Z] E ACTUAL: array([ -0. , -39.62720511])
[2020-11-06T21:37:09.831Z] E DESIRED: array([ -0. , -39.62720511])
---
tests/python/gpu/test_operator_gpu.py | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/tests/python/gpu/test_operator_gpu.py b/tests/python/gpu/test_operator_gpu.py
index beb4e81..7087ee3 100644
--- a/tests/python/gpu/test_operator_gpu.py
+++ b/tests/python/gpu/test_operator_gpu.py
@@ -15,7 +15,6 @@
# specific language governing permissions and limitations
# under the License.
-from __future__ import print_function
import sys
import os
import time
@@ -372,6 +371,7 @@ def test_preloaded_multi_sgd():
@pytest.mark.serial
+@pytest.mark.flaky
def test_batchnorm_with_type():
ctx_list_v2_2D = [
{'ctx': mx.cpu(0), 'norm_data': (5, 2, 5, 5), 'type_dict': {'norm_data': np.float32}},