pytorch/caffe2/python/ideep/elementwise_sum_op_test.py

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
import caffe2.python.ideep_test_util as mu


@unittest.skipIf(not workspace.C.use_ideep, "No IDEEP support.")
class ElementwiseSumTest(hu.HypothesisTestCase):
    @given(size=st.integers(7, 9),
           input_channels=st.integers(1, 3),
           batch_size=st.integers(1, 3),
           inputs=st.integers(2, 7),
           inplace=st.booleans(),
           **mu.gcs)
    def test_elementwise_sum(self,
                                 size,
                                 input_channels,
                                 batch_size,
                                 inputs,
                                 inplace,
                                 gc,
                                 dc):
        op = core.CreateOperator(
            "Sum",
            ["X_{}".format(i) for i in range(inputs)],
            ["X_0" if inplace else "Y"],
        )
        Xs = [np.random.rand(batch_size, input_channels, size, size).astype(
            np.float32) for _ in range(inputs)]
        self.assertDeviceChecks(dc, op, Xs, [0])


if __name__ == "__main__":
    unittest.main()