pytorch/caffe2/python/operator_test/glu_op_test.py
Christopher Whelan 5cd0f5e8ec [PyFI] Update hypothesis and switch from tp2 (#41645)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/41645

Pull Request resolved: https://github.com/facebookresearch/pytext/pull/1405

Test Plan: buck test

Reviewed By: thatch

Differential Revision: D20323893

fbshipit-source-id: 54665d589568c4198e96a27f0ed8e5b41df7b86b
2020-08-08 12:13:04 -07:00

45 lines
1.3 KiB
Python

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
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()