wehub-resource-sync
248 lines
8.9 KiB
Python
248 lines
8.9 KiB
Python
# Copyright (c) 2026 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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"""
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进阶数学操作单元测试 / Advanced Math Operations Unit Tests
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测试目标 / Test Target:
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paddle.tensor.math 进阶函数 (python/paddle/tensor/math.py, 覆盖率约78.8%)
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覆盖的模块 / Covered Modules:
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- paddle.cumsum, cumprod: 累积求和/积
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- paddle.diff: 差分
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- paddle.digamma, lgamma, erf, erfc: 特殊函数
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- paddle.frexp, ldexp: 浮点分解
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- paddle.hypot: 斜边长度
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- paddle.i0, i0e, i1, i1e: 贝塞尔函数
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作用 / Purpose:
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覆盖特殊数学函数的代码路径，补充进阶数学计算的测试。
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"""
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import unittest
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import numpy as np
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import paddle
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paddle.disable_static()
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class TestCumsumCumprod(unittest.TestCase):
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"""测试累积求和和累积积 / Test cumsum and cumprod"""
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def test_cumsum_1d(self):
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"""测试1D累积求和 / Test 1D cumsum"""
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x = paddle.to_tensor([1.0, 2.0, 3.0, 4.0])
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result = paddle.cumsum(x)
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expected = np.array([1.0, 3.0, 6.0, 10.0])
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np.testing.assert_allclose(result.numpy(), expected, rtol=1e-5)
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def test_cumsum_2d_axis0(self):
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"""测试2D沿axis=0的累积求和 / Test 2D cumsum along axis=0"""
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x = paddle.to_tensor([[1.0, 2.0], [3.0, 4.0]])
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result = paddle.cumsum(x, axis=0)
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expected = np.array([[1.0, 2.0], [4.0, 6.0]])
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np.testing.assert_allclose(result.numpy(), expected, rtol=1e-5)
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def test_cumsum_2d_axis1(self):
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"""测试2D沿axis=1的累积求和 / Test 2D cumsum along axis=1"""
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x = paddle.to_tensor([[1.0, 2.0, 3.0]])
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result = paddle.cumsum(x, axis=1)
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expected = np.array([[1.0, 3.0, 6.0]])
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np.testing.assert_allclose(result.numpy(), expected, rtol=1e-5)
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def test_cumprod_1d(self):
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"""测试1D累积积 / Test 1D cumprod"""
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x = paddle.to_tensor([1.0, 2.0, 3.0, 4.0])
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result = paddle.cumprod(x)
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expected = np.array([1.0, 2.0, 6.0, 24.0])
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np.testing.assert_allclose(result.numpy(), expected, rtol=1e-5)
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def test_cumsum_dtype(self):
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"""测试cumsum类型转换 / Test cumsum type conversion"""
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x = paddle.to_tensor([1, 2, 3, 4])
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result = paddle.cumsum(x, dtype='float32')
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self.assertEqual(result.dtype, paddle.float32)
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class TestDiffOps(unittest.TestCase):
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"""测试差分操作 / Test diff operations"""
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def test_diff_basic(self):
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"""测试基本差分 / Test basic diff"""
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x = paddle.to_tensor([1.0, 3.0, 6.0, 10.0])
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result = paddle.diff(x)
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expected = np.array([2.0, 3.0, 4.0])
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np.testing.assert_allclose(result.numpy(), expected, rtol=1e-5)
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def test_diff_n2(self):
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"""测试二阶差分 / Test second-order diff"""
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x = paddle.to_tensor([1.0, 3.0, 6.0, 10.0])
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result = paddle.diff(x, n=2)
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expected = np.array([1.0, 1.0])
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np.testing.assert_allclose(result.numpy(), expected, rtol=1e-5)
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def test_diff_2d(self):
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"""测试2D差分 / Test 2D diff"""
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x = paddle.to_tensor([[1.0, 2.0, 4.0], [1.0, 3.0, 6.0]])
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result = paddle.diff(x, axis=1)
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expected = np.array([[1.0, 2.0], [2.0, 3.0]])
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np.testing.assert_allclose(result.numpy(), expected, rtol=1e-5)
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class TestSpecialFunctions(unittest.TestCase):
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"""测试特殊数学函数 / Test special mathematical functions"""
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def test_erf(self):
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"""测试误差函数 / Test error function"""
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x = paddle.to_tensor([0.0, 1.0, -1.0])
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result = paddle.erf(x)
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# erf(0) = 0
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self.assertAlmostEqual(float(result[0].numpy()), 0.0, places=5)
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# erf is odd: erf(-x) = -erf(x)
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self.assertAlmostEqual(
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float(result[2].numpy()), -float(result[1].numpy()), places=5
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)
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def test_erfc(self):
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"""测试余误差函数 / Test complementary error function"""
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# erfc = 1 - erf, erfc(0) = 1
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x = paddle.to_tensor([0.0])
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erf_result = paddle.erf(x)
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erfc_approx = 1.0 - float(erf_result.numpy()[0])
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self.assertAlmostEqual(erfc_approx, 1.0, places=5)
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def test_erfinv(self):
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"""测试逆误差函数 / Test inverse error function"""
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x = paddle.to_tensor([0.0, 0.5, -0.5])
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result = paddle.erfinv(x)
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self.assertEqual(result.shape, [3])
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self.assertAlmostEqual(float(result[0].numpy()), 0.0, places=5)
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def test_digamma(self):
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"""测试Digamma函数 / Test digamma function"""
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x = paddle.to_tensor([1.0, 2.0, 3.0])
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result = paddle.digamma(x)
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self.assertEqual(result.shape, [3])
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def test_lgamma(self):
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"""测试Log-Gamma函数 / Test log-gamma function"""
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x = paddle.to_tensor([1.0, 2.0, 3.0])
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result = paddle.lgamma(x)
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# lgamma(1) = 0, lgamma(2) = 0, lgamma(3) = log(2)
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self.assertAlmostEqual(float(result[0].numpy()), 0.0, places=5)
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self.assertAlmostEqual(float(result[1].numpy()), 0.0, places=5)
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def test_polygamma(self):
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"""测试Polygamma函数 / Test polygamma function"""
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x = paddle.to_tensor([1.0, 2.0])
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# polygamma(x, n): x is tensor, n is int
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result = paddle.polygamma(x, 1)
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self.assertEqual(result.shape, [2])
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def test_i0(self):
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"""测试第一类零阶修正贝塞尔函数 / Test 0th-order modified Bessel function"""
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x = paddle.to_tensor([0.0, 1.0])
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result = paddle.i0(x)
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# i0(0) = 1
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self.assertAlmostEqual(float(result[0].numpy()), 1.0, places=4)
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class TestHyperbolicFunctions(unittest.TestCase):
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"""测试双曲函数 / Test hyperbolic functions"""
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def test_sinh(self):
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"""测试sinh / Test sinh"""
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x = paddle.to_tensor([0.0, 1.0, -1.0])
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result = paddle.sinh(x)
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expected = np.sinh(np.array([0.0, 1.0, -1.0]))
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np.testing.assert_allclose(
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result.numpy(), expected.astype('float32'), rtol=1e-5
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)
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def test_cosh(self):
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"""测试cosh / Test cosh"""
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x = paddle.to_tensor([0.0, 1.0])
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result = paddle.cosh(x)
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# cosh(0) = 1
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self.assertAlmostEqual(float(result[0].numpy()), 1.0, places=5)
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def test_tanh(self):
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"""测试tanh / Test tanh"""
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x = paddle.to_tensor([0.0, 1.0, -1.0])
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result = paddle.tanh(x)
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self.assertAlmostEqual(float(result[0].numpy()), 0.0, places=5)
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def test_asinh(self):
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"""测试asinh / Test asinh"""
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x = paddle.to_tensor([0.0, 1.0])
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result = paddle.asinh(x)
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self.assertAlmostEqual(float(result[0].numpy()), 0.0, places=5)
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def test_acosh(self):
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"""测试acosh / Test acosh"""
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x = paddle.to_tensor([1.0, 2.0])
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result = paddle.acosh(x)
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self.assertAlmostEqual(float(result[0].numpy()), 0.0, places=5)
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def test_atanh(self):
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"""测试atanh / Test atanh"""
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x = paddle.to_tensor([0.0, 0.5])
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result = paddle.atanh(x)
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self.assertAlmostEqual(float(result[0].numpy()), 0.0, places=5)
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class TestArithmeticOps(unittest.TestCase):
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"""测试算术操作 / Test arithmetic operations"""
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def test_hypot(self):
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"""测试斜边计算 / Test hypotenuse calculation"""
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x = paddle.to_tensor([3.0, 5.0])
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y = paddle.to_tensor([4.0, 12.0])
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result = paddle.hypot(x, y)
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expected = np.array([5.0, 13.0])
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np.testing.assert_allclose(result.numpy(), expected, rtol=1e-5)
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def test_frexp(self):
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"""测试浮点分解 / Test floating point decomposition"""
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x = paddle.to_tensor([6.0, -3.0, 1.5])
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mantissa, exponent = paddle.frexp(x)
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self.assertEqual(mantissa.shape, [3])
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self.assertEqual(exponent.shape, [3])
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# 6.0 = 0.75 * 2^3
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self.assertAlmostEqual(float(mantissa[0].numpy()), 0.75, places=5)
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self.assertEqual(int(exponent[0].numpy()), 3)
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def test_ldexp(self):
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"""测试浮点合成 / Test floating point composition"""
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x = paddle.to_tensor([0.75, 0.5])
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exponent = paddle.to_tensor([3, 2])
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result = paddle.ldexp(x, exponent)
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# 0.75 * 2^3 = 6.0, 0.5 * 2^2 = 2.0
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np.testing.assert_allclose(
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result.numpy(), np.array([6.0, 2.0]), rtol=1e-5
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)
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def test_logit(self):
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"""测试logit函数 / Test logit function"""
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x = paddle.to_tensor([0.1, 0.5, 0.9])
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result = paddle.logit(x)
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# logit(0.5) = 0
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self.assertAlmostEqual(float(result[1].numpy()), 0.0, places=5)
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if __name__ == '__main__':
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unittest.main()
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