pytorch/caffe2/python/ideep/softmax_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 SoftmaxTest(hu.HypothesisTestCase):
    @given(size=st.integers(8, 20),
           input_channels=st.integers(1, 3),
           batch_size=st.integers(1, 3),
           inplace=st.booleans(),
           **mu.gcs)
    def test_softmax(self, size, input_channels, batch_size, inplace, gc, dc):
        op = core.CreateOperator(
            "Softmax",
            ["X"],
            ["Y"],
            axis=1,
        )
        X = np.random.rand(
            batch_size, input_channels, size, size).astype(np.float32) - 0.5
        self.assertDeviceChecks(dc, op, [X], [0])


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