wehub-resource-sync
218 lines
8.1 KiB
Python
218 lines
8.1 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.extension
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# 覆盖模块: paddle/nn/functional/extension.py
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# 未覆盖行: 130,131,133,134,135,136,137,139,141,145,146,231,232,233,236,238,244,323,324,330,331,333,335,336,338,348
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# Covered module: paddle/nn/functional/extension.py
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# Uncovered lines: 130,131,133,134,135,136,137,139,141,145,146,231,232,233,236,238,244,323,324,330,331,333,335,336,338,348
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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 TestSequenceMask(unittest.TestCase):
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"""测试 sequence_mask 函数
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Test sequence_mask function"""
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def test_sequence_mask_basic(self):
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"""测试基本的 sequence_mask
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Test basic sequence_mask"""
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lengths = paddle.to_tensor([10, 9, 8])
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mask = paddle.nn.functional.sequence_mask(lengths)
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self.assertEqual(mask.shape, [3, 10])
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self.assertEqual(mask.dtype, paddle.int64)
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def test_sequence_mask_with_maxlen(self):
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"""测试指定 maxlen 的 sequence_mask
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Test sequence_mask with specified maxlen"""
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lengths = paddle.to_tensor([3, 1, 1, 0])
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mask = paddle.nn.functional.sequence_mask(lengths, maxlen=4)
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self.assertEqual(mask.shape, [4, 4])
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expected = np.array(
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[
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[1, 1, 1, 0],
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[1, 0, 0, 0],
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[1, 0, 0, 0],
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[0, 0, 0, 0],
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]
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)
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np.testing.assert_array_equal(mask.numpy(), expected)
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def test_sequence_mask_dtype_float32(self):
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"""测试 float32 输出类型的 sequence_mask
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Test sequence_mask with float32 output dtype"""
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lengths = paddle.to_tensor([2, 3])
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mask = paddle.nn.functional.sequence_mask(lengths, dtype='float32')
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self.assertEqual(mask.dtype, paddle.float32)
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def test_sequence_mask_dtype_int32(self):
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"""测试 int32 输出类型的 sequence_mask
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Test sequence_mask with int32 output dtype"""
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lengths = paddle.to_tensor([2, 3])
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mask = paddle.nn.functional.sequence_mask(lengths, dtype='int32')
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self.assertEqual(mask.dtype, paddle.int32)
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def test_sequence_mask_dtype_bool(self):
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"""测试 bool 输出类型的 sequence_mask
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Test sequence_mask with bool output dtype"""
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lengths = paddle.to_tensor([2, 3])
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mask = paddle.nn.functional.sequence_mask(lengths, dtype='bool')
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self.assertEqual(mask.dtype, paddle.bool)
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def test_sequence_mask_2d_input(self):
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"""测试2D输入的 sequence_mask
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Test sequence_mask with 2D input"""
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lengths = paddle.to_tensor([[2, 3], [1, 4]])
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mask = paddle.nn.functional.sequence_mask(lengths, maxlen=5)
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self.assertEqual(mask.shape, [2, 2, 5])
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def test_sequence_mask_no_maxlen(self):
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"""测试不指定 maxlen 的 sequence_mask (使用 max(x))
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Test sequence_mask without maxlen (uses max(x))"""
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lengths = paddle.to_tensor([2, 5, 3])
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mask = paddle.nn.functional.sequence_mask(lengths)
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self.assertEqual(mask.shape, [3, 5])
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class TestGatherTree(unittest.TestCase):
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"""测试 gather_tree 函数
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Test gather_tree function"""
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def test_gather_tree_basic(self):
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"""测试基本的 gather_tree
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Test basic gather_tree"""
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ids = paddle.to_tensor(
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[[[2, 2], [6, 1]], [[3, 9], [6, 1]], [[0, 1], [9, 0]]]
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)
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parents = paddle.to_tensor(
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[[[0, 0], [1, 1]], [[1, 0], [1, 0]], [[0, 0], [0, 1]]]
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)
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result = paddle.nn.functional.gather_tree(ids, parents)
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self.assertEqual(result.shape, [3, 2, 2])
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expected = np.array(
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[
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[[2, 2], [1, 6]],
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[[3, 3], [6, 1]],
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[[0, 1], [9, 0]],
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]
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)
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np.testing.assert_array_equal(result.numpy(), expected)
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def test_gather_tree_not_3d(self):
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"""测试非3D输入的 gather_tree 报错
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Test gather_tree raises error for non-3D input"""
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ids = paddle.to_tensor([[1, 2], [3, 4]])
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parents = paddle.to_tensor([[0, 0], [1, 1]])
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with self.assertRaises(ValueError):
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paddle.nn.functional.gather_tree(ids, parents)
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def test_gather_tree_shape_mismatch(self):
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"""测试 ids 和 parents 形状不匹配时报错
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Test gather_tree raises error when ids and parents shapes differ"""
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ids = paddle.to_tensor([[[1, 2]]])
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parents = paddle.to_tensor([[[1, 2], [3, 4]]])
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with self.assertRaises(ValueError):
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paddle.nn.functional.gather_tree(ids, parents)
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def test_gather_tree_int32(self):
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"""测试 int32 类型的 gather_tree
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Test gather_tree with int32 dtype"""
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ids = paddle.to_tensor(
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[[[2, 2], [6, 1]], [[3, 9], [6, 1]], [[0, 1], [9, 0]]],
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dtype='int32',
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)
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parents = paddle.to_tensor(
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[[[0, 0], [1, 1]], [[1, 0], [1, 0]], [[0, 0], [0, 1]]],
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dtype='int32',
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)
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result = paddle.nn.functional.gather_tree(ids, parents)
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self.assertEqual(result.shape, [3, 2, 2])
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class TestTemporalShift(unittest.TestCase):
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"""测试 temporal_shift 函数
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Test temporal_shift function"""
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def test_temporal_shift_basic(self):
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"""测试基本的 temporal_shift
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Test basic temporal_shift"""
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x = paddle.randn([6, 4, 2, 2])
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out = paddle.nn.functional.temporal_shift(
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x, seg_num=2, shift_ratio=0.25
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)
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self.assertEqual(out.shape, [6, 4, 2, 2])
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def test_temporal_shift_nhwc(self):
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"""测试 NHWC 格式的 temporal_shift
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Test temporal_shift with NHWC format"""
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x = paddle.randn([6, 2, 2, 4])
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out = paddle.nn.functional.temporal_shift(
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x, seg_num=2, shift_ratio=0.25, data_format='NHWC'
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)
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self.assertEqual(out.shape, [6, 2, 2, 4])
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def test_temporal_shift_invalid_format(self):
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"""测试无效的 data_format 报错
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Test temporal_shift raises error for invalid data_format"""
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x = paddle.randn([6, 4, 2, 2])
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with self.assertRaises(ValueError):
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paddle.nn.functional.temporal_shift(
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x, seg_num=2, shift_ratio=0.25, data_format='INVALID'
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)
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def test_temporal_shift_different_seg_num(self):
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"""测试不同 seg_num 的 temporal_shift
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Test temporal_shift with different seg_num"""
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x = paddle.randn([9, 8, 3, 3])
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out = paddle.nn.functional.temporal_shift(
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x, seg_num=3, shift_ratio=0.125
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)
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self.assertEqual(out.shape, [9, 8, 3, 3])
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def test_temporal_shift_float64(self):
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"""测试 float64 类型的 temporal_shift
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Test temporal_shift with float64 dtype"""
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x = paddle.randn([6, 4, 2, 2], dtype='float64')
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out = paddle.nn.functional.temporal_shift(
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x, seg_num=2, shift_ratio=0.25
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)
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self.assertEqual(out.dtype, paddle.float64)
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class TestDiagEmbed(unittest.TestCase):
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"""测试 diag_embed 函数 (deprecated)
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Test diag_embed function (deprecated)"""
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def test_diag_embed_basic(self):
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"""测试基本的 diag_embed
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Test basic diag_embed"""
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x = paddle.to_tensor([1.0, 2.0, 3.0])
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result = paddle.nn.functional.diag_embed(x)
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self.assertEqual(result.shape, [3, 3])
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def test_diag_embed_with_offset(self):
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"""测试带 offset 的 diag_embed
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Test diag_embed with offset"""
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x = paddle.to_tensor([1.0, 2.0])
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result = paddle.nn.functional.diag_embed(x, offset=1)
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self.assertEqual(result.shape, [3, 3])
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if __name__ == '__main__':
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unittest.main()
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