# Copyright (c) 2024 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. # [AUTO-GENERATED] Unit test for paddle.tensor.math # 自动生成的单测，覆盖 paddle.tensor.math 模块中未覆盖的代码 """ 测试模块：paddle.tensor.math (inner, outer, dist, lerp, frac, diff, logit, i0) Test Module: paddle.tensor.math 本测试覆盖以下功能： This test covers the following functions: 1. inner - 内积 / Inner product of tensors 2. outer - 外积 / Outer product of vectors 3. dist - 距离 / Distance with various p values 4. lerp - 线性插值 / Linear interpolation 5. frac - 小数部分 / Fractional part 6. diff - 差分 / Difference 7. logit - logit函数 / Logit function 覆盖的未覆盖行：inner/outer各分支, dist p值分支, lerp/frac动态图路径 """ import unittest import numpy as np import paddle class TestInner(unittest.TestCase): """测试inner内积运算 Test inner product""" def setUp(self): paddle.disable_static() def test_inner_1d(self): """1D向量内积 / 1D vector inner product""" x = paddle.to_tensor([1.0, 2.0, 3.0], dtype='float32') y = paddle.to_tensor([4.0, 5.0, 6.0], dtype='float32') out = paddle.inner(x, y) np.testing.assert_allclose(float(out.numpy()), 32.0, rtol=1e-5) def test_inner_2d(self): """2D矩阵内积 / 2D matrix inner product""" x = paddle.to_tensor([[1.0, 2.0], [3.0, 4.0]], dtype='float32') y = paddle.to_tensor([[5.0, 6.0], [7.0, 8.0]], dtype='float32') out = paddle.inner(x, y) self.assertEqual(list(out.shape), [2, 2]) class TestOuter(unittest.TestCase): """测试outer外积运算 Test outer product""" def setUp(self): paddle.disable_static() def test_outer_basic(self): """基本外积 / Basic outer product""" x = paddle.to_tensor([1.0, 2.0, 3.0], dtype='float32') y = paddle.to_tensor([4.0, 5.0], dtype='float32') out = paddle.outer(x, y) expected = np.array([[4.0, 5.0], [8.0, 10.0], [12.0, 15.0]]) np.testing.assert_allclose(out.numpy(), expected, rtol=1e-5) def test_outer_shape(self): """外积形状验证 / Outer product shape""" x = paddle.ones([5], dtype='float32') y = paddle.ones([3], dtype='float32') out = paddle.outer(x, y) self.assertEqual(list(out.shape), [5, 3]) class TestDist(unittest.TestCase): """测试dist距离计算 Test dist function""" def setUp(self): paddle.disable_static() def test_dist_p2(self): """L2距离 / L2 distance""" x = paddle.to_tensor([1.0, 0.0, 0.0], dtype='float32') y = paddle.to_tensor([0.0, 1.0, 0.0], dtype='float32') out = paddle.dist(x, y, p=2) np.testing.assert_allclose(float(out.numpy()), np.sqrt(2.0), rtol=1e-5) def test_dist_p1(self): """L1距离 / L1 distance""" x = paddle.to_tensor([1.0, 2.0, 3.0], dtype='float32') y = paddle.to_tensor([4.0, 5.0, 6.0], dtype='float32') out = paddle.dist(x, y, p=1) np.testing.assert_allclose(float(out.numpy()), 9.0, rtol=1e-5) def test_dist_inf(self): """无穷距离 / Infinity distance""" x = paddle.to_tensor([1.0, 2.0, 3.0], dtype='float32') y = paddle.to_tensor([4.0, 5.0, 10.0], dtype='float32') out = paddle.dist(x, y, p=float('inf')) np.testing.assert_allclose(float(out.numpy()), 7.0, rtol=1e-5) def test_dist_p0(self): """L0距离 / L0 distance""" x = paddle.to_tensor([1.0, 2.0, 3.0], dtype='float32') y = paddle.to_tensor([1.0, 5.0, 6.0], dtype='float32') out = paddle.dist(x, y, p=0) np.testing.assert_allclose(float(out.numpy()), 2.0, rtol=1e-5) class TestLerp(unittest.TestCase): """测试lerp线性插值 Test lerp function""" def setUp(self): paddle.disable_static() def test_lerp_basic(self): """基本线性插值 / Basic lerp""" x = paddle.to_tensor([0.0, 0.0], dtype='float32') y = paddle.to_tensor([10.0, 10.0], dtype='float32') out = paddle.lerp(x, y, 0.5) np.testing.assert_allclose(out.numpy(), [5.0, 5.0], rtol=1e-5) def test_lerp_weight_zero(self): """weight=0返回x / Lerp with weight=0 returns x""" x = paddle.to_tensor([1.0, 2.0], dtype='float32') y = paddle.to_tensor([10.0, 20.0], dtype='float32') out = paddle.lerp(x, y, 0.0) np.testing.assert_allclose(out.numpy(), [1.0, 2.0], rtol=1e-5) def test_lerp_weight_one(self): """weight=1返回y / Lerp with weight=1 returns y""" x = paddle.to_tensor([1.0, 2.0], dtype='float32') y = paddle.to_tensor([10.0, 20.0], dtype='float32') out = paddle.lerp(x, y, 1.0) np.testing.assert_allclose(out.numpy(), [10.0, 20.0], rtol=1e-5) def test_lerp_tensor_weight(self): """Tensor权重 / Lerp with tensor weight""" x = paddle.zeros([3], dtype='float32') y = paddle.ones([3], dtype='float32') weight = paddle.to_tensor([0.0, 0.5, 1.0], dtype='float32') out = paddle.lerp(x, y, weight) np.testing.assert_allclose(out.numpy(), [0.0, 0.5, 1.0], rtol=1e-5) class TestFrac(unittest.TestCase): """测试frac小数部分 Test frac function""" def setUp(self): paddle.disable_static() def test_frac_positive(self): """正数小数部分 / Frac of positive numbers""" x = paddle.to_tensor([1.5, 2.7, 3.0], dtype='float32') out = paddle.frac(x) np.testing.assert_allclose(out.numpy(), [0.5, 0.7, 0.0], rtol=1e-4) def test_frac_negative(self): """负数小数部分 / Frac of negative numbers""" x = paddle.to_tensor([-1.5, -2.3], dtype='float32') out = paddle.frac(x) np.testing.assert_allclose(out.numpy(), [-0.5, -0.3], rtol=1e-4) class TestDiff(unittest.TestCase): """测试diff差分 Test diff function""" def setUp(self): paddle.disable_static() def test_diff_basic(self): """基本差分 / Basic diff""" x = paddle.to_tensor([1.0, 4.0, 9.0, 16.0], dtype='float32') out = paddle.diff(x) np.testing.assert_allclose(out.numpy(), [3.0, 5.0, 7.0], rtol=1e-5) def test_diff_n2(self): """二阶差分 / Second order diff""" x = paddle.to_tensor([1.0, 4.0, 9.0, 16.0], dtype='float32') out = paddle.diff(x, n=2) np.testing.assert_allclose(out.numpy(), [2.0, 2.0], rtol=1e-5) def test_diff_2d(self): """2D差分 / 2D diff""" x = paddle.to_tensor( [[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]], dtype='float32' ) out = paddle.diff(x, axis=1) expected = np.array([[1.0, 1.0], [1.0, 1.0]]) np.testing.assert_allclose(out.numpy(), expected, rtol=1e-5) if __name__ == '__main__': unittest.main()