wehub-resource-sync
226 lines
6.6 KiB
Python
226 lines
6.6 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.nn.layer.common (Dropout, Linear, Flatten, etc.)
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# 自动生成的单测，覆盖 paddle.nn.layer.common 模块中未覆盖的代码路径
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# Target: cover uncovered lines in paddle/python/paddle/nn/layer/common.py
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# 目标：覆盖 Linear, Dropout, Flatten, Pad 等 common layer 的各种参数路径
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"""
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This test covers the following modules and code paths:
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这个测试覆盖以下模块和代码路径：
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1. Linear - 各种参数 (in_features, out_features, weight_attr, bias_attr, name)
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2. Dropout - p, mode, axis 参数
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3. Flatten - start_axis, stop_axis 参数
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4. Pad1D, Pad2D, Pad3D - 各种 padding 模式
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5. Identity - 恒等层
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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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from paddle import nn
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class TestLinear(unittest.TestCase):
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"""Test Linear layer.
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测试 Linear 层。
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"""
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def setUp(self):
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paddle.disable_static()
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def test_linear_basic(self):
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"""Basic Linear."""
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linear = nn.Linear(10, 5)
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x = paddle.randn([4, 10])
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out = linear(x)
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self.assertEqual(out.shape, [4, 5])
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def test_linear_no_bias(self):
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"""Linear without bias."""
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linear = nn.Linear(10, 5, bias_attr=False)
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self.assertIsNone(linear.bias)
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x = paddle.randn([4, 10])
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out = linear(x)
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self.assertEqual(out.shape, [4, 5])
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def test_linear_with_name(self):
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"""Linear with name."""
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linear = nn.Linear(10, 5, name='my_linear')
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x = paddle.randn([4, 10])
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out = linear(x)
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self.assertEqual(out.shape, [4, 5])
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def test_linear_3d_input(self):
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"""Linear with 3D input."""
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linear = nn.Linear(10, 5)
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x = paddle.randn([2, 3, 10])
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out = linear(x)
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self.assertEqual(out.shape, [2, 3, 5])
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def test_linear_1d_input(self):
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"""Linear with 1D input (per-sample)."""
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linear = nn.Linear(10, 5)
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x = paddle.randn([10])
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out = linear(x)
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self.assertEqual(out.shape, [5])
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class TestDropout(unittest.TestCase):
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"""Test Dropout layer.
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测试 Dropout 层。
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"""
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def setUp(self):
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paddle.disable_static()
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def test_dropout_train(self):
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"""Dropout in training mode."""
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dp = nn.Dropout(p=0.5)
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dp.train()
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x = paddle.ones([1000])
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out = dp(x)
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# Some values should be 0
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self.assertTrue(paddle.sum(out == 0).numpy() > 0)
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def test_dropout_eval(self):
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"""Dropout in eval mode should be identity."""
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dp = nn.Dropout(p=0.5)
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dp.eval()
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x = paddle.ones([10])
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out = dp(x)
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np.testing.assert_allclose(out.numpy(), np.ones([10]))
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def test_dropout_zero_p(self):
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"""Dropout with p=0 should be identity."""
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dp = nn.Dropout(p=0.0)
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x = paddle.randn([10])
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out = dp(x)
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np.testing.assert_allclose(out.numpy(), x.numpy())
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def test_dropout_axis(self):
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"""Dropout along specific axis."""
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dp = nn.Dropout(p=0.5, axis=1)
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dp.train()
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x = paddle.ones([4, 10])
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out = dp(x)
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self.assertEqual(out.shape, [4, 10])
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class TestFlatten(unittest.TestCase):
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"""Test Flatten layer.
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测试 Flatten 层。
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"""
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def setUp(self):
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paddle.disable_static()
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def test_flatten_default(self):
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"""Flatten with default start_axis=1."""
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flatten = nn.Flatten()
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x = paddle.randn([2, 3, 4, 5])
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out = flatten(x)
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self.assertEqual(out.shape, [2, 60])
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def test_flatten_start_axis_0(self):
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"""Flatten from axis 0."""
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flatten = nn.Flatten(start_axis=0)
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x = paddle.randn([2, 3, 4])
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out = flatten(x)
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self.assertEqual(out.shape, [24])
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def test_flatten_start_stop(self):
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"""Flatten with custom start_axis and stop_axis."""
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flatten = nn.Flatten(start_axis=1, stop_axis=2)
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x = paddle.randn([2, 3, 4, 5])
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out = flatten(x)
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self.assertEqual(out.shape, [2, 12, 5])
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class TestIdentity(unittest.TestCase):
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"""Test Identity layer.
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测试 Identity 层。
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"""
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def setUp(self):
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paddle.disable_static()
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def test_identity_basic(self):
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"""Identity should pass through."""
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identity = nn.Identity()
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x = paddle.randn([2, 3, 4])
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out = identity(x)
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np.testing.assert_allclose(out.numpy(), x.numpy())
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class TestPad2D(unittest.TestCase):
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"""Test Pad2D layer.
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测试 Pad2D 层。
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"""
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def setUp(self):
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paddle.disable_static()
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def test_pad2d_constant(self):
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"""Pad2D with constant mode."""
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pad = nn.Pad2D(padding=1, mode='constant', value=0)
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x = paddle.randn([2, 3, 4, 4])
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out = pad(x)
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self.assertEqual(out.shape, [2, 3, 6, 6])
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def test_pad2d_reflect(self):
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"""Pad2D with reflect mode."""
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pad = nn.Pad2D(padding=1, mode='reflect')
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x = paddle.randn([2, 3, 4, 4])
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out = pad(x)
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self.assertEqual(out.shape, [2, 3, 6, 6])
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def test_pad2d_replicate(self):
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"""Pad2D with replicate mode."""
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pad = nn.Pad2D(padding=1, mode='replicate')
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x = paddle.randn([2, 3, 4, 4])
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out = pad(x)
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self.assertEqual(out.shape, [2, 3, 6, 6])
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def test_pad2d_tuple_padding(self):
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"""Pad2D with tuple padding."""
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# Paddle Pad2D tuple: (pad_left, pad_right, pad_top, pad_bottom)
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# Input [2, 3, 4, 4] -> H=4+1+2=7, W=4+1+2=7 -> [2, 3, 7, 7]
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pad = nn.Pad2D(padding=(1, 2, 1, 2), mode='constant')
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x = paddle.randn([2, 3, 4, 4])
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out = pad(x)
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self.assertEqual(out.shape, [2, 3, 7, 7])
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def test_pad1d(self):
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"""Pad1D basic."""
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pad = nn.Pad1D(padding=1, mode='constant')
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x = paddle.randn([2, 3, 10])
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out = pad(x)
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self.assertEqual(out.shape, [2, 3, 12])
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def test_pad3d(self):
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"""Pad3D basic."""
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pad = nn.Pad3D(padding=1, mode='constant')
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x = paddle.randn([2, 3, 4, 4, 4])
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out = pad(x)
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self.assertEqual(out.shape, [2, 3, 6, 6, 6])
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if __name__ == '__main__':
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unittest.main()
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