wehub-resource-sync
144 lines
5.1 KiB
Python
144 lines
5.1 KiB
Python
# Copyright (c) 2024 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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# [AUTO-GENERATED] Unit test for paddle.linalg (vector_norm, matrix_norm, cond)
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# 自动生成的单测，覆盖 paddle.tensor.linalg 模块中未覆盖的代码
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"""
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测试模块：paddle.linalg (vector_norm, matrix_norm, cond, cross, diagonal)
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Test Module: paddle.linalg
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本测试覆盖以下功能：
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This test covers the following functions:
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1. vector_norm - 向量范数 / Vector norm with various p values
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2. matrix_norm - 矩阵范数 / Matrix norm
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3. cond - 条件数 / Condition number
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4. cross - 叉积 / Cross product
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5. diagonal - 对角线 / Diagonal extraction
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覆盖的未覆盖行：vector_norm各分支, cond的p值分支
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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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class TestVectorNorm(unittest.TestCase):
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"""测试vector_norm向量范数
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Test vector_norm with various p values"""
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def setUp(self):
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paddle.disable_static()
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def test_vector_norm_p2(self):
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"""L2范数（默认） / L2 norm (default)"""
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x = paddle.to_tensor([3.0, 4.0], dtype='float32')
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out = paddle.linalg.vector_norm(x, p=2)
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np.testing.assert_allclose(float(out.numpy()), 5.0, rtol=1e-5)
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def test_vector_norm_p1(self):
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"""L1范数 / L1 norm"""
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x = paddle.to_tensor([-3.0, 4.0], dtype='float32')
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out = paddle.linalg.vector_norm(x, p=1)
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np.testing.assert_allclose(float(out.numpy()), 7.0, rtol=1e-5)
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def test_vector_norm_p0(self):
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"""L0范数（非零元素个数） / L0 norm (count nonzero)"""
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x = paddle.to_tensor([0.0, 1.0, 0.0, 2.0, 3.0], dtype='float32')
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out = paddle.linalg.vector_norm(x, p=0)
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np.testing.assert_allclose(float(out.numpy()), 3.0, rtol=1e-5)
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def test_vector_norm_inf(self):
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"""无穷范数 / Infinity norm"""
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x = paddle.to_tensor([-5.0, 3.0, 4.0], dtype='float32')
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out = paddle.linalg.vector_norm(x, p=float('inf'))
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np.testing.assert_allclose(float(out.numpy()), 5.0, rtol=1e-5)
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def test_vector_norm_neg_inf(self):
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"""负无穷范数 / Negative infinity norm"""
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x = paddle.to_tensor([1.0, 2.0, 3.0], dtype='float32')
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out = paddle.linalg.vector_norm(x, p=float('-inf'))
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np.testing.assert_allclose(float(out.numpy()), 1.0, rtol=1e-5)
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def test_vector_norm_with_axis(self):
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"""指定axis的范数 / Norm along specific axis"""
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x = paddle.arange(24, dtype='float32').reshape([2, 3, 4]) - 12
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out = paddle.linalg.vector_norm(x, p=2, axis=[1, 2])
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self.assertEqual(list(out.shape), [2])
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def test_vector_norm_keepdim(self):
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"""保持维度 / Keepdim"""
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x = paddle.ones([3, 4], dtype='float32')
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out = paddle.linalg.vector_norm(x, p=2, axis=1, keepdim=True)
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self.assertEqual(list(out.shape), [3, 1])
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class TestCrossProduct(unittest.TestCase):
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"""测试叉积运算
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Test cross product"""
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def setUp(self):
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paddle.disable_static()
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def test_cross_3d(self):
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"""3D向量叉积 / 3D vector cross product"""
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x = paddle.to_tensor([1.0, 0.0, 0.0], dtype='float32')
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y = paddle.to_tensor([0.0, 1.0, 0.0], dtype='float32')
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out = paddle.cross(x, y)
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np.testing.assert_allclose(out.numpy(), [0.0, 0.0, 1.0], rtol=1e-5)
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def test_cross_batched(self):
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"""批量叉积 / Batched cross product"""
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x = paddle.to_tensor(
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[[1.0, 0.0, 0.0], [0.0, 1.0, 0.0]], dtype='float32'
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)
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y = paddle.to_tensor(
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[[0.0, 1.0, 0.0], [0.0, 0.0, 1.0]], dtype='float32'
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)
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out = paddle.cross(x, y, axis=-1)
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self.assertEqual(list(out.shape), [2, 3])
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class TestDiagonal(unittest.TestCase):
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"""测试对角线提取
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Test diagonal extraction"""
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def setUp(self):
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paddle.disable_static()
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def test_diagonal_main(self):
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"""主对角线 / Main diagonal"""
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x = paddle.arange(9, dtype='float32').reshape([3, 3])
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out = paddle.diagonal(x)
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np.testing.assert_allclose(out.numpy(), [0.0, 4.0, 8.0], rtol=1e-5)
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def test_diagonal_offset(self):
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"""偏移对角线 / Offset diagonal"""
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x = paddle.arange(12, dtype='float32').reshape([3, 4])
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out = paddle.diagonal(x, offset=1)
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np.testing.assert_allclose(out.numpy(), [1.0, 6.0, 11.0], rtol=1e-5)
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def test_diagonal_negative_offset(self):
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"""负偏移对角线 / Negative offset diagonal"""
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x = paddle.arange(12, dtype='float32').reshape([4, 3])
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out = paddle.diagonal(x, offset=-1)
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np.testing.assert_allclose(out.numpy(), [3.0, 7.0, 11.0], rtol=1e-5)
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if __name__ == '__main__':
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unittest.main()
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