wehub-resource-sync
202 lines
7.5 KiB
Python
202 lines
7.5 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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# [AUTO-GENERATED] Test file for paddle.nn.functional.vision
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# 覆盖模块: paddle/nn/functional/vision.py
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# Uncovered lines: affine_grid, grid_sample, pixel_shuffle, pixel_unshuffle
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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 TestAffineGrid(unittest.TestCase):
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"""测试 affine_grid 函数
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Test affine_grid function"""
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def test_affine_grid_identity(self):
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"""测试恒等变换的 affine_grid
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Test identity affine_grid"""
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theta = paddle.to_tensor([[[1.0, 0.0, 0.0], [0.0, 1.0, 0.0]]])
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grid = paddle.nn.functional.affine_grid(theta, [1, 1, 3, 3])
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self.assertEqual(grid.shape, [1, 3, 3, 2])
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def test_affine_grid_shape(self):
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"""测试 affine_grid 输出形状
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Test affine_grid output shape"""
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# Batch size comes from theta, not from output_shape
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theta = paddle.to_tensor(
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[
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[[1.0, 0.0, 0.0], [0.0, 1.0, 0.0]],
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[[1.0, 0.0, 0.0], [0.0, 1.0, 0.0]],
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]
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)
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grid = paddle.nn.functional.affine_grid(theta, [2, 1, 4, 4])
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self.assertEqual(grid.shape, [2, 4, 4, 2])
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def test_affine_grid_values(self):
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"""测试 affine_grid 输出值范围
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Test affine_grid output value range"""
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theta = paddle.to_tensor([[[1.0, 0.0, 0.0], [0.0, 1.0, 0.0]]])
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grid = paddle.nn.functional.affine_grid(theta, [1, 1, 2, 2])
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# Grid values should be in [-1, 1]
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self.assertTrue(paddle.all(grid >= -1.0).item())
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self.assertTrue(paddle.all(grid <= 1.0).item())
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class TestGridSample(unittest.TestCase):
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"""测试 grid_sample 函数
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Test grid_sample function"""
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def test_grid_sample_basic(self):
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"""测试基本 grid_sample
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Test basic grid_sample"""
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x = paddle.randn([1, 1, 4, 4])
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theta = paddle.to_tensor([[[1.0, 0.0, 0.0], [0.0, 1.0, 0.0]]])
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grid = paddle.nn.functional.affine_grid(theta, [1, 1, 4, 4])
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result = paddle.nn.functional.grid_sample(x, grid)
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self.assertEqual(result.shape, [1, 1, 4, 4])
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def test_grid_sample_bilinear(self):
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"""测试双线性插值的 grid_sample
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Test grid_sample with bilinear interpolation"""
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x = paddle.randn([1, 3, 8, 8])
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theta = paddle.to_tensor([[[1.0, 0.0, 0.0], [0.0, 1.0, 0.0]]])
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grid = paddle.nn.functional.affine_grid(theta, [1, 3, 4, 4])
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result = paddle.nn.functional.grid_sample(x, grid, mode='bilinear')
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self.assertEqual(result.shape, [1, 3, 4, 4])
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def test_grid_sample_nearest(self):
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"""测试最近邻插值的 grid_sample
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Test grid_sample with nearest interpolation"""
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x = paddle.randn([1, 1, 4, 4])
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theta = paddle.to_tensor([[[1.0, 0.0, 0.0], [0.0, 1.0, 0.0]]])
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grid = paddle.nn.functional.affine_grid(theta, [1, 1, 4, 4])
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result = paddle.nn.functional.grid_sample(x, grid, mode='nearest')
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self.assertEqual(result.shape, [1, 1, 4, 4])
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def test_grid_sample_padding_zeros(self):
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"""测试零填充的 grid_sample
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Test grid_sample with zeros padding"""
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x = paddle.randn([1, 1, 4, 4])
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theta = paddle.to_tensor([[[1.0, 0.0, 0.0], [0.0, 1.0, 0.0]]])
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grid = paddle.nn.functional.affine_grid(theta, [1, 1, 4, 4])
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result = paddle.nn.functional.grid_sample(x, grid, padding_mode='zeros')
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self.assertEqual(result.shape, [1, 1, 4, 4])
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class TestPixelShuffle(unittest.TestCase):
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"""测试 pixel_shuffle 函数
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Test pixel_shuffle function"""
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def test_pixel_shuffle_basic(self):
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"""测试基本 pixel_shuffle
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Test basic pixel_shuffle"""
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x = paddle.randn([1, 9, 2, 2])
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result = paddle.nn.functional.pixel_shuffle(x, upscale_factor=3)
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self.assertEqual(result.shape, [1, 1, 6, 6])
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def test_pixel_shuffle_factor2(self):
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"""测试 upscale_factor=2 的 pixel_shuffle
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Test pixel_shuffle with upscale_factor=2"""
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x = paddle.randn([1, 4, 3, 3])
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result = paddle.nn.functional.pixel_shuffle(x, upscale_factor=2)
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self.assertEqual(result.shape, [1, 1, 6, 6])
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def test_pixel_shuffle_batch(self):
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"""测试批量 pixel_shuffle
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Test batched pixel_shuffle"""
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x = paddle.randn([2, 16, 4, 4])
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result = paddle.nn.functional.pixel_shuffle(x, upscale_factor=4)
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self.assertEqual(result.shape, [2, 1, 16, 16])
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class TestPixelUnshuffle(unittest.TestCase):
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"""测试 pixel_unshuffle 函数
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Test pixel_unshuffle function"""
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def test_pixel_unshuffle_basic(self):
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"""测试基本 pixel_unshuffle
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Test basic pixel_unshuffle"""
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x = paddle.randn([1, 1, 6, 6])
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result = paddle.nn.functional.pixel_unshuffle(x, downscale_factor=3)
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self.assertEqual(result.shape, [1, 9, 2, 2])
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def test_pixel_unshuffle_roundtrip(self):
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"""测试 pixel_shuffle 和 pixel_unshuffle 往返
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Test pixel_shuffle and pixel_unshuffle roundtrip"""
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x = paddle.randn([1, 4, 3, 3])
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shuffled = paddle.nn.functional.pixel_shuffle(x, upscale_factor=2)
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unshuffled = paddle.nn.functional.pixel_unshuffle(
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shuffled, downscale_factor=2
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)
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np.testing.assert_allclose(unshuffled.numpy(), x.numpy(), atol=1e-6)
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class TestOneHot(unittest.TestCase):
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"""测试 one_hot 函数
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Test one_hot function"""
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def test_one_hot_basic(self):
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"""测试基本 one_hot
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Test basic one_hot"""
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x = paddle.to_tensor([0, 1, 2, 3])
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result = paddle.nn.functional.one_hot(x, num_classes=4)
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self.assertEqual(result.shape, [4, 4])
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# Check that diagonal is 1
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for i in range(4):
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self.assertEqual(result[i, i].item(), 1)
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def test_one_hot_2d(self):
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"""测试二维输入 one_hot
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Test 2D input one_hot"""
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x = paddle.to_tensor([[0, 1], [2, 3]])
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result = paddle.nn.functional.one_hot(x, num_classes=4)
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self.assertEqual(result.shape, [2, 2, 4])
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class TestEmbedding(unittest.TestCase):
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"""测试 embedding 函数
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Test embedding function"""
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def test_embedding_basic(self):
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"""测试基本 embedding
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Test basic embedding"""
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x = paddle.to_tensor([0, 1, 2, 3])
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weight = paddle.randn([4, 5])
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result = paddle.nn.functional.embedding(x, weight)
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self.assertEqual(result.shape, [4, 5])
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def test_embedding_2d_input(self):
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"""测试二维输入 embedding
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Test 2D input embedding"""
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x = paddle.to_tensor([[0, 1], [2, 3]])
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weight = paddle.randn([4, 5])
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result = paddle.nn.functional.embedding(x, weight)
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self.assertEqual(result.shape, [2, 2, 5])
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def test_embedding_padding_idx(self):
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"""测试带 padding_idx 的 embedding
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Test embedding with padding_idx"""
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x = paddle.to_tensor([0, 1, 2])
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weight = paddle.randn([4, 5])
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result = paddle.nn.functional.embedding(x, weight, padding_idx=0)
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self.assertEqual(result.shape, [3, 5])
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if __name__ == '__main__':
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unittest.main()
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