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bb9ff58c6d
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/9379 Add cudnn activation ops Reviewed By: houseroad Differential Revision: D8818013 fbshipit-source-id: d3881c634a46578b9331da07f9fdf7e1f31d7e8a
45 lines
1.4 KiB
Python
45 lines
1.4 KiB
Python
from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from __future__ import unicode_literals
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from caffe2.python import core
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from hypothesis import given
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import caffe2.python.hypothesis_test_util as hu
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import hypothesis.strategies as st
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import numpy as np
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class TestHyperbolicOps(hu.HypothesisTestCase):
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def _test_hyperbolic_op(self, op_name, np_ref, X, in_place, engine, gc, dc):
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op = core.CreateOperator(
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op_name,
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["X"],
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["X"] if in_place else ["Y"],
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engine=engine,)
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def ref(X):
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return [np_ref(X)]
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self.assertReferenceChecks(
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device_option=gc,
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op=op,
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inputs=[X],
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reference=ref,
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)
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self.assertDeviceChecks(dc, op, [X], [0])
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self.assertGradientChecks(gc, op, [X], 0, [0])
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@given(X=hu.tensor(dtype=np.float32), **hu.gcs)
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def test_sinh(self, X, gc, dc):
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self._test_hyperbolic_op("Sinh", np.sinh, X, False, "", gc, dc)
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@given(X=hu.tensor(dtype=np.float32), **hu.gcs)
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def test_cosh(self, X, gc, dc):
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self._test_hyperbolic_op("Cosh", np.cosh, X, False, "", gc, dc)
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@given(X=hu.tensor(dtype=np.float32), in_place=st.booleans(),
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engine=st.sampled_from(["", "CUDNN"]), **hu.gcs)
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def test_tanh(self, X, in_place, engine, gc, dc):
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self._test_hyperbolic_op("Tanh", np.tanh, X, in_place, engine, gc, dc)
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