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| | 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 |
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| | @unittest.skipIf(not workspace.C.use_mkldnn, "No MKLDNN 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]) |
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| | if __name__ == "__main__": |
| | unittest.main() |
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