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https://github.com/zebrajr/pytorch.git
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8286ce1e3a
Summary: Closes https://github.com/caffe2/caffe2/pull/1260 Differential Revision: D5906739 Pulled By: Yangqing fbshipit-source-id: e482ba9ba60b5337d9165f28f7ec68d4518a0902
65 lines
2.1 KiB
Python
65 lines
2.1 KiB
Python
# Copyright (c) 2016-present, Facebook, Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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##############################################################################
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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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import numpy as np
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import hypothesis.strategies as st
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import unittest
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import caffe2.python.hypothesis_test_util as hu
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from caffe2.python import core
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from hypothesis import given
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class TestPad(hu.HypothesisTestCase):
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@given(pad_t=st.integers(-5, 0),
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pad_l=st.integers(-5, 0),
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pad_b=st.integers(-5, 0),
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pad_r=st.integers(-5, 0),
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mode=st.sampled_from(["constant", "reflect", "edge"]),
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size_w=st.integers(16, 128),
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size_h=st.integers(16, 128),
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size_c=st.integers(1, 4),
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size_n=st.integers(1, 4),
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**hu.gcs)
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def test_crop(self,
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pad_t, pad_l, pad_b, pad_r,
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mode,
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size_w, size_h, size_c, size_n,
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gc, dc):
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op = core.CreateOperator(
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"PadImage",
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["X"],
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["Y"],
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pad_t=pad_t,
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pad_l=pad_l,
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pad_b=pad_b,
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pad_r=pad_r,
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)
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X = np.random.rand(
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size_n, size_c, size_h, size_w).astype(np.float32)
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def ref(X):
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return (X[:, :, -pad_t:pad_b or None, -pad_l:pad_r or None],)
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self.assertReferenceChecks(gc, op, [X], ref)
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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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