test_pairwise_distance.py 4.6 KB
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# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from __future__ import print_function

import paddle
import paddle.fluid as fluid
import numpy as np
import unittest


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def pairwise_distance(x, y, p=2.0, epsilon=1e-6, keepdim=False):
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    return np.linalg.norm(x - y, ord=p, axis=1, keepdims=keepdim)


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def test_static(x_np, y_np, p=2.0, epsilon=1e-6, keepdim=False):
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    prog = paddle.static.Program()
    startup_prog = paddle.static.Program()

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    place = fluid.CUDAPlace(
        0) if paddle.fluid.core.is_compiled_with_cuda() else fluid.CPUPlace()
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    with paddle.static.program_guard(prog, startup_prog):
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        x = paddle.fluid.data(name='x', shape=x_np.shape, dtype=x_np.dtype)
        y = paddle.fluid.data(name='y', shape=y_np.shape, dtype=x_np.dtype)
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        dist = paddle.nn.layer.distance.PairwiseDistance(p=p,
                                                         epsilon=epsilon,
                                                         keepdim=keepdim)
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        distance = dist(x, y)
        exe = paddle.static.Executor(place)
        static_ret = exe.run(prog,
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                             feed={
                                 'x': x_np,
                                 'y': y_np
                             },
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                             fetch_list=[distance])
        static_ret = static_ret[0]
    return static_ret


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def test_dygraph(x_np, y_np, p=2.0, epsilon=1e-6, keepdim=False):
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    paddle.disable_static()
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    x = paddle.to_tensor(x_np)
    y = paddle.to_tensor(y_np)
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    dist = paddle.nn.layer.distance.PairwiseDistance(p=p,
                                                     epsilon=epsilon,
                                                     keepdim=keepdim)
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    distance = dist(x, y)
    dygraph_ret = distance.numpy()
    paddle.enable_static()
    return dygraph_ret


class TestPairwiseDistance(unittest.TestCase):
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    def test_pairwise_distance(self):
        all_shape = [[100, 100], [4, 5, 6, 7]]
        dtypes = ['float32', 'float64']
        keeps = [False, True]
        for shape in all_shape:
            for dtype in dtypes:
                for keepdim in keeps:
                    x_np = np.random.random(shape).astype(dtype)
                    y_np = np.random.random(shape).astype(dtype)

                    static_ret = test_static(x_np, y_np, keepdim=keepdim)
                    dygraph_ret = test_dygraph(x_np, y_np, keepdim=keepdim)
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                    excepted_value = pairwise_distance(x_np,
                                                       y_np,
                                                       keepdim=keepdim)
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                    self.assertTrue(np.allclose(static_ret, dygraph_ret))
                    self.assertTrue(np.allclose(static_ret, excepted_value))
                    self.assertTrue(np.allclose(dygraph_ret, excepted_value))

    def test_pairwise_distance_broadcast(self):
        shape_x = [100, 100]
        shape_y = [100, 1]
        keepdim = False
        x_np = np.random.random(shape_x).astype('float32')
        y_np = np.random.random(shape_y).astype('float32')
        static_ret = test_static(x_np, y_np, keepdim=keepdim)
        dygraph_ret = test_dygraph(x_np, y_np, keepdim=keepdim)
        excepted_value = pairwise_distance(x_np, y_np, keepdim=keepdim)
        self.assertTrue(np.allclose(static_ret, dygraph_ret))
        self.assertTrue(np.allclose(static_ret, excepted_value))
        self.assertTrue(np.allclose(dygraph_ret, excepted_value))

    def test_pairwise_distance_different_p(self):
        shape = [100, 100]
        keepdim = False
        p = 3.0
        x_np = np.random.random(shape).astype('float32')
        y_np = np.random.random(shape).astype('float32')
        static_ret = test_static(x_np, y_np, p=p, keepdim=keepdim)
        dygraph_ret = test_dygraph(x_np, y_np, p=p, keepdim=keepdim)
        excepted_value = pairwise_distance(x_np, y_np, p=p, keepdim=keepdim)
        self.assertTrue(np.allclose(static_ret, dygraph_ret))
        self.assertTrue(np.allclose(static_ret, excepted_value))
        self.assertTrue(np.allclose(dygraph_ret, excepted_value))


if __name__ == "__main__":
    unittest.main()