# 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. import unittest import numpy as np from op_test import OpTest import paddle import paddle.nn as nn import paddle.nn.functional as F import paddle.fluid.core as core from paddle.fluid import Program, program_guard, Executor, default_main_program class TestCosineSimilarityAPI(unittest.TestCase): def setUp(self): self.places = [paddle.CPUPlace()] if core.is_compiled_with_cuda(): self.places.append(paddle.CUDAPlace(0)) def _get_numpy_out(self, x1, x2, dim=1, eps=1e-8): w12 = np.sum(x1 * x2, axis=dim) w1 = np.sum(x1 * x1, axis=dim) w2 = np.sum(x2 * x2, axis=dim) n12 = np.sqrt(np.clip(w1 * w2, eps * eps, None)) cos_sim = w12 / n12 return cos_sim def check_static_result(self, place): paddle.enable_static() with program_guard(Program(), Program()): shape = [10, 15] dim = 1 eps = 1e-8 np.random.seed(0) np_x1 = np.random.rand(*shape).astype(np.float32) np_x2 = np.random.rand(*shape).astype(np.float32) x1 = paddle.data(name="x1", shape=shape) x2 = paddle.data(name="x2", shape=shape) result = F.cosine_similarity(x1, x2, dim=dim, eps=eps) exe = Executor(place) fetches = exe.run(default_main_program(), feed={"x1": np_x1, "x2": np_x2}, fetch_list=[result]) np_out = self._get_numpy_out(np_x1, np_x2, dim=dim, eps=eps) self.assertTrue(np.allclose(fetches[0], np_out)) def test_static(self): for place in self.places: self.check_static_result(place=place) def test_dygraph_1(self): paddle.disable_static() shape = [10, 15] dim = 1 eps = 1e-8 np.random.seed(1) np_x1 = np.random.rand(*shape).astype(np.float32) np_x2 = np.random.rand(*shape).astype(np.float32) np_out = self._get_numpy_out(np_x1, np_x2, dim=dim, eps=eps) tesnor_x1 = paddle.to_variable(np_x1) tesnor_x2 = paddle.to_variable(np_x2) y = F.cosine_similarity(tesnor_x1, tesnor_x2, dim=dim, eps=eps) self.assertTrue(np.allclose(y.numpy(), np_out)) def test_dygraph_2(self): paddle.disable_static() shape = [12, 13] dim = 0 eps = 1e-6 np.random.seed(1) np_x1 = np.random.rand(*shape).astype(np.float32) np_x2 = np.random.rand(*shape).astype(np.float32) np_out = self._get_numpy_out(np_x1, np_x2, dim=dim, eps=eps) tesnor_x1 = paddle.to_variable(np_x1) tesnor_x2 = paddle.to_variable(np_x2) y = F.cosine_similarity(tesnor_x1, tesnor_x2, dim=dim, eps=eps) self.assertTrue(np.allclose(y.numpy(), np_out)) def test_dygraph_3(self): paddle.disable_static() shape1 = [10, 12, 10] shape2 = [10, 1, 10] dim = 2 eps = 1e-6 np.random.seed(1) np_x1 = np.random.rand(*shape1).astype(np.float32) np_x2 = np.random.rand(*shape2).astype(np.float32) np_out = self._get_numpy_out(np_x1, np_x2, dim=dim, eps=eps) tesnor_x1 = paddle.to_variable(np_x1) tesnor_x2 = paddle.to_variable(np_x2) y = F.cosine_similarity(tesnor_x1, tesnor_x2, dim=dim, eps=eps) self.assertTrue(np.allclose(y.numpy(), np_out)) if __name__ == '__main__': unittest.main()