pytorch

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from caffe2.python import core
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from hypothesis import given, settings
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from hypothesis import strategies as st
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import caffe2.python.hypothesis_test_util as hu
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import caffe2.python.serialized_test.serialized_test_util as serial
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import numpy as np
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import unittest
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class TestMathOps(serial.SerializedTestCase):
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    @given(X=hu.tensor(),
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           exponent=st.floats(min_value=2.0, max_value=3.0),
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           **hu.gcs)
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    def test_elementwise_power(self, X, exponent, gc, dc):
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        # negative integer raised with non-integer exponent is domain error
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        X = np.abs(X)
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        def powf(X):
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            return (X ** exponent,)
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        def powf_grad(g_out, outputs, fwd_inputs):
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            return (exponent * (fwd_inputs[0] ** (exponent - 1)) * g_out,)
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        op = core.CreateOperator(
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            "Pow", ["X"], ["Y"], exponent=exponent)
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        self.assertReferenceChecks(gc, op, [X], powf,
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                                   output_to_grad="Y",
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                                   grad_reference=powf_grad,
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                                   ensure_outputs_are_inferred=True)
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    @given(X=hu.tensor(),
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           exponent=st.floats(min_value=-3.0, max_value=3.0),
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           **hu.gcs)
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    @settings(deadline=10000)
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    def test_sign(self, X, exponent, gc, dc):
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        def signf(X):
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            return [np.sign(X)]
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        op = core.CreateOperator(
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            "Sign", ["X"], ["Y"])
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        self.assertReferenceChecks(
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            gc, op, [X], signf, ensure_outputs_are_inferred=True)
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        self.assertDeviceChecks(dc, op, [X], [0])
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if __name__ == "__main__":
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    unittest.main()
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