pytorch/caffe2/python/operator_test/glu_op_test.py
Bugra Akyildiz 27c7158166 Remove __future__ imports for legacy Python2 supports (#45033)
Summary:
There is a module called `2to3` which you can target for future specifically to remove these, the directory of `caffe2` has the most redundant imports:

```2to3 -f future -w caffe2```

Pull Request resolved: https://github.com/pytorch/pytorch/pull/45033

Reviewed By: seemethere

Differential Revision: D23808648

Pulled By: bugra

fbshipit-source-id: 38971900f0fe43ab44a9168e57f2307580d36a38
2020-09-23 17:57:02 -07:00

45 lines
1.2 KiB
Python

from caffe2.python import core
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
from hypothesis import assume, given, settings, HealthCheck
import hypothesis.strategies as st
import numpy as np
import unittest
@st.composite
def _glu_old_input(draw):
dims = draw(st.lists(st.integers(min_value=1, max_value=5), min_size=1, max_size=3))
axis = draw(st.integers(min_value=0, max_value=len(dims)))
# The axis dimension must be divisible by two
axis_dim = 2 * draw(st.integers(min_value=1, max_value=2))
dims.insert(axis, axis_dim)
X = draw(hu.arrays(dims, np.float32, None))
return (X, axis)
class TestGlu(serial.SerializedTestCase):
@given(
X_axis=_glu_old_input(),
**hu.gcs
)
@settings(deadline=10000)
def test_glu_old(self, X_axis, gc, dc):
X, axis = X_axis
def glu_ref(X):
x1, x2 = np.split(X, [X.shape[axis] // 2], axis=axis)
Y = x1 * (1. / (1. + np.exp(-x2)))
return [Y]
op = core.CreateOperator("Glu", ["X"], ["Y"], dim=axis)
self.assertReferenceChecks(gc, op, [X], glu_ref)
if __name__ == "__main__":
unittest.main()