mirror of
https://github.com/saymrwulf/pytorch.git
synced 2026-05-15 21:00:47 +00:00
3b1a5a1b8a
Summary: Followup to the [first refactor](https://github.com/pytorch/pytorch/pull/11350). Increase coverage of tests Pull Request resolved: https://github.com/pytorch/pytorch/pull/11811 Reviewed By: houseroad Differential Revision: D9923074 Pulled By: ajyu fbshipit-source-id: 0f899bb9e9a75bf7ed939e06cc9b028daa7f6bd9
98 lines
3.2 KiB
Python
98 lines
3.2 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 caffe2.python.serialized_test.serialized_test_util as serial
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import hypothesis.strategies as st
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import numpy as np
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import unittest
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class TestSelu(serial.SerializedTestCase):
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@serial.given(X=hu.tensor(),
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engine=st.sampled_from(["", "CUDNN"]),
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**hu.gcs)
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def test_selu_1(self, X, gc, dc, engine):
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alpha = 1.0
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scale = 2.0
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op = core.CreateOperator("Selu", ["X"], ["Y"],
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alpha=alpha, scale=scale, engine=engine)
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X = TestSelu.fix0(X)
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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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self.assertReferenceChecks(
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gc, op, [X], lambda x: TestSelu.selu_ref(x, alpha=alpha, scale=scale)
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)
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@given(X=hu.tensor(),
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engine=st.sampled_from(["", "CUDNN"]),
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**hu.gcs)
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def test_selu_2(self, X, gc, dc, engine):
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alpha = 1.6732
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scale = 1.0507
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op = core.CreateOperator("Selu", ["X"], ["Y"],
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alpha=alpha, scale=scale, engine=engine)
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X = TestSelu.fix0(X)
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self.assertDeviceChecks(dc, op, [X], [0])
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self.assertGradientChecks(gc, op, [X], 0, [0], stepsize=1e-2, threshold=1e-2)
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self.assertReferenceChecks(
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gc, op, [X], lambda x: TestSelu.selu_ref(x, alpha=alpha, scale=scale)
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)
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@given(X=hu.tensor(),
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engine=st.sampled_from(["", "CUDNN"]),
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**hu.gcs)
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def test_selu_3(self, X, gc, dc, engine):
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alpha = 1.3
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scale = 1.1
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op = core.CreateOperator("Selu", ["X"], ["Y"],
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alpha=alpha, scale=scale, engine=engine)
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X = TestSelu.fix0(X)
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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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self.assertReferenceChecks(
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gc, op, [X], lambda x: TestSelu.selu_ref(x, alpha=alpha, scale=scale)
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)
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@given(X=hu.tensor(),
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engine=st.sampled_from(["", "CUDNN"]),
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**hu.gcs)
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def test_selu_inplace(self, X, gc, dc, engine):
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alpha = 1.3
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scale = 1.1
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op = core.CreateOperator("Selu", ["X"], ["X"],
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alpha=alpha, scale=scale, engine=engine)
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X = TestSelu.fix0(X)
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self.assertDeviceChecks(dc, op, [X], [0])
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# inplace gradient
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Y = TestSelu.selu_ref(X, alpha=alpha, scale=scale)
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dX = np.ones_like(X)
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op2 = core.CreateOperator("SeluGradient", ["Y", "dX"], ["dX"],
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alpha=alpha, scale=scale, engine=engine)
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self.assertDeviceChecks(dc, op2, [Y, dX], [0])
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@staticmethod
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def fix0(X):
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# go away from the origin point to avoid kink problems
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X += 0.02 * np.sign(X)
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X[X == 0.0] += 0.02
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return X
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@staticmethod
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def selu_ref(x, scale, alpha):
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ret = scale * ((x > 0) * x + (x <= 0) * (alpha * (np.exp(x) - 1)))
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return [ret]
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if __name__ == "__main__":
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unittest.main()
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