pytorch/caffe2/python/ideep/sigmoid_op_test.py
Hui Wu acd7811e33 Add sigmoid op based on MKL-DNN
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/13097

Differential Revision: D13105366

Pulled By: yinghai

fbshipit-source-id: d156e8fd519baeecf61c25dcd8fa2c2fa7351ef4
2018-11-19 22:56:35 -08:00

32 lines
881 B
Python

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
import unittest
import hypothesis.strategies as st
from hypothesis import given
import numpy as np
from caffe2.python import core, workspace
import caffe2.python.hypothesis_test_util as hu
@unittest.skipIf(not workspace.C.use_mkldnn, "No MKLDNN support.")
class SigmoidTest(hu.HypothesisTestCase):
@given(X=hu.tensor(dtype=np.float32),
inplace=st.booleans(),
**hu.gcs)
def test_sigmoid(self, X, inplace, gc, dc):
op = core.CreateOperator(
"Sigmoid",
["X"],
["Y"] if not inplace else ["X"],
)
self.assertDeviceChecks(dc, op, [X], [0])
self.assertGradientChecks(gc, op, [X], 0, [0])
if __name__ == "__main__":
unittest.main()