mirror of
https://github.com/saymrwulf/pytorch.git
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dbab9b73b6
Summary: 1. Remove avx2 support in mkldnn 2. Seperate mkl, mklml, and mkldnn 3. Fix convfusion test case Pull Request resolved: https://github.com/pytorch/pytorch/pull/12170 Reviewed By: yinghai Differential Revision: D10207126 Pulled By: orionr fbshipit-source-id: 1e62eb47943f426a89d57e2d2606439f2b04fd51
46 lines
1.4 KiB
Python
46 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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import unittest
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import hypothesis.strategies as st
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from hypothesis import given, settings, assume
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import numpy as np
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from caffe2.python import core, workspace
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import caffe2.python.hypothesis_test_util as hu
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import caffe2.python.ideep_test_util as mu
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@unittest.skipIf(not workspace.C.use_mkldnn, "No MKLDNN support.")
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class PoolTest(hu.HypothesisTestCase):
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@given(stride=st.integers(1, 3),
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pad=st.integers(0, 3),
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kernel=st.integers(3, 5),
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size=st.integers(7, 9),
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input_channels=st.integers(1, 3),
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batch_size=st.integers(1, 3),
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method=st.sampled_from(["MaxPool", "AveragePool"]),
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**mu.gcs)
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def test_pooling(self, stride, pad, kernel, size,
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input_channels, batch_size,
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method, gc, dc):
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assume(pad < kernel)
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op = core.CreateOperator(
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method,
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["X"],
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["Y"],
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stride=stride,
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pad=pad,
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kernel=kernel,
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)
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X = np.random.rand(
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batch_size, input_channels, size, size).astype(np.float32)
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self.assertDeviceChecks(dc, op, [X], [0])
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if 'MaxPool' not in method:
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self.assertGradientChecks(gc, op, [X], 0, [0])
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if __name__ == "__main__":
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unittest.main()
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