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110 lines
4.3 KiB
110 lines
4.3 KiB
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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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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from __future__ import print_function
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import paddle
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import paddle.fluid as fluid
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import numpy as np
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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()
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startup_prog = paddle.static.Program()
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place = fluid.CUDAPlace(0) if paddle.fluid.core.is_compiled_with_cuda(
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) 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)
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y = paddle.fluid.data(name='y', shape=y_np.shape, dtype=x_np.dtype)
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dist = paddle.nn.layer.distance.PairwiseDistance(
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p=p, epsilon=epsilon, keepdim=keepdim)
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distance = dist(x, y)
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exe = paddle.static.Executor(place)
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static_ret = exe.run(prog,
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feed={'x': x_np,
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'y': y_np},
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fetch_list=[distance])
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static_ret = static_ret[0]
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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)
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y = paddle.to_tensor(y_np)
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dist = paddle.nn.layer.distance.PairwiseDistance(
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p=p, epsilon=epsilon, keepdim=keepdim)
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distance = dist(x, y)
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dygraph_ret = distance.numpy()
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paddle.enable_static()
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return dygraph_ret
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class TestPairwiseDistance(unittest.TestCase):
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def test_pairwise_distance(self):
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all_shape = [[100, 100], [4, 5, 6, 7]]
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dtypes = ['float32', 'float64']
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keeps = [False, True]
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for shape in all_shape:
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for dtype in dtypes:
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for keepdim in keeps:
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x_np = np.random.random(shape).astype(dtype)
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y_np = np.random.random(shape).astype(dtype)
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static_ret = test_static(x_np, y_np, keepdim=keepdim)
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dygraph_ret = test_dygraph(x_np, y_np, keepdim=keepdim)
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excepted_value = pairwise_distance(
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x_np, y_np, keepdim=keepdim)
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self.assertTrue(np.allclose(static_ret, dygraph_ret))
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self.assertTrue(np.allclose(static_ret, excepted_value))
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self.assertTrue(np.allclose(dygraph_ret, excepted_value))
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def test_pairwise_distance_broadcast(self):
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shape_x = [100, 100]
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shape_y = [100, 1]
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keepdim = False
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x_np = np.random.random(shape_x).astype('float32')
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y_np = np.random.random(shape_y).astype('float32')
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static_ret = test_static(x_np, y_np, keepdim=keepdim)
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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))
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self.assertTrue(np.allclose(static_ret, excepted_value))
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self.assertTrue(np.allclose(dygraph_ret, excepted_value))
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def test_pairwise_distance_different_p(self):
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shape = [100, 100]
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keepdim = False
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p = 3.0
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x_np = np.random.random(shape).astype('float32')
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y_np = np.random.random(shape).astype('float32')
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static_ret = test_static(x_np, y_np, p=p, keepdim=keepdim)
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dygraph_ret = test_dygraph(x_np, y_np, p=p, keepdim=keepdim)
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excepted_value = pairwise_distance(x_np, y_np, p=p, keepdim=keepdim)
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self.assertTrue(np.allclose(static_ret, dygraph_ret))
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self.assertTrue(np.allclose(static_ret, excepted_value))
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self.assertTrue(np.allclose(dygraph_ret, excepted_value))
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if __name__ == "__main__":
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unittest.main()
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