# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # [AUTO-GENERATED] Unit test for paddle.nn.layer.common (Dropout, Linear, Flatten, etc.) # 自动生成的单测，覆盖 paddle.nn.layer.common 模块中未覆盖的代码路径 # Target: cover uncovered lines in paddle/python/paddle/nn/layer/common.py # 目标：覆盖 Linear, Dropout, Flatten, Pad 等 common layer 的各种参数路径 """ This test covers the following modules and code paths: 这个测试覆盖以下模块和代码路径： 1. Linear - 各种参数 (in_features, out_features, weight_attr, bias_attr, name) 2. Dropout - p, mode, axis 参数 3. Flatten - start_axis, stop_axis 参数 4. Pad1D, Pad2D, Pad3D - 各种 padding 模式 5. Identity - 恒等层 """ import unittest import numpy as np import paddle from paddle import nn class TestLinear(unittest.TestCase): """Test Linear layer. 测试 Linear 层。 """ def setUp(self): paddle.disable_static() def test_linear_basic(self): """Basic Linear.""" linear = nn.Linear(10, 5) x = paddle.randn([4, 10]) out = linear(x) self.assertEqual(out.shape, [4, 5]) def test_linear_no_bias(self): """Linear without bias.""" linear = nn.Linear(10, 5, bias_attr=False) self.assertIsNone(linear.bias) x = paddle.randn([4, 10]) out = linear(x) self.assertEqual(out.shape, [4, 5]) def test_linear_with_name(self): """Linear with name.""" linear = nn.Linear(10, 5, name='my_linear') x = paddle.randn([4, 10]) out = linear(x) self.assertEqual(out.shape, [4, 5]) def test_linear_3d_input(self): """Linear with 3D input.""" linear = nn.Linear(10, 5) x = paddle.randn([2, 3, 10]) out = linear(x) self.assertEqual(out.shape, [2, 3, 5]) def test_linear_1d_input(self): """Linear with 1D input (per-sample).""" linear = nn.Linear(10, 5) x = paddle.randn([10]) out = linear(x) self.assertEqual(out.shape, [5]) class TestDropout(unittest.TestCase): """Test Dropout layer. 测试 Dropout 层。 """ def setUp(self): paddle.disable_static() def test_dropout_train(self): """Dropout in training mode.""" dp = nn.Dropout(p=0.5) dp.train() x = paddle.ones([1000]) out = dp(x) # Some values should be 0 self.assertTrue(paddle.sum(out == 0).numpy() > 0) def test_dropout_eval(self): """Dropout in eval mode should be identity.""" dp = nn.Dropout(p=0.5) dp.eval() x = paddle.ones([10]) out = dp(x) np.testing.assert_allclose(out.numpy(), np.ones([10])) def test_dropout_zero_p(self): """Dropout with p=0 should be identity.""" dp = nn.Dropout(p=0.0) x = paddle.randn([10]) out = dp(x) np.testing.assert_allclose(out.numpy(), x.numpy()) def test_dropout_axis(self): """Dropout along specific axis.""" dp = nn.Dropout(p=0.5, axis=1) dp.train() x = paddle.ones([4, 10]) out = dp(x) self.assertEqual(out.shape, [4, 10]) class TestFlatten(unittest.TestCase): """Test Flatten layer. 测试 Flatten 层。 """ def setUp(self): paddle.disable_static() def test_flatten_default(self): """Flatten with default start_axis=1.""" flatten = nn.Flatten() x = paddle.randn([2, 3, 4, 5]) out = flatten(x) self.assertEqual(out.shape, [2, 60]) def test_flatten_start_axis_0(self): """Flatten from axis 0.""" flatten = nn.Flatten(start_axis=0) x = paddle.randn([2, 3, 4]) out = flatten(x) self.assertEqual(out.shape, [24]) def test_flatten_start_stop(self): """Flatten with custom start_axis and stop_axis.""" flatten = nn.Flatten(start_axis=1, stop_axis=2) x = paddle.randn([2, 3, 4, 5]) out = flatten(x) self.assertEqual(out.shape, [2, 12, 5]) class TestIdentity(unittest.TestCase): """Test Identity layer. 测试 Identity 层。 """ def setUp(self): paddle.disable_static() def test_identity_basic(self): """Identity should pass through.""" identity = nn.Identity() x = paddle.randn([2, 3, 4]) out = identity(x) np.testing.assert_allclose(out.numpy(), x.numpy()) class TestPad2D(unittest.TestCase): """Test Pad2D layer. 测试 Pad2D 层。 """ def setUp(self): paddle.disable_static() def test_pad2d_constant(self): """Pad2D with constant mode.""" pad = nn.Pad2D(padding=1, mode='constant', value=0) x = paddle.randn([2, 3, 4, 4]) out = pad(x) self.assertEqual(out.shape, [2, 3, 6, 6]) def test_pad2d_reflect(self): """Pad2D with reflect mode.""" pad = nn.Pad2D(padding=1, mode='reflect') x = paddle.randn([2, 3, 4, 4]) out = pad(x) self.assertEqual(out.shape, [2, 3, 6, 6]) def test_pad2d_replicate(self): """Pad2D with replicate mode.""" pad = nn.Pad2D(padding=1, mode='replicate') x = paddle.randn([2, 3, 4, 4]) out = pad(x) self.assertEqual(out.shape, [2, 3, 6, 6]) def test_pad2d_tuple_padding(self): """Pad2D with tuple padding.""" # Paddle Pad2D tuple: (pad_left, pad_right, pad_top, pad_bottom) # Input [2, 3, 4, 4] -> H=4+1+2=7, W=4+1+2=7 -> [2, 3, 7, 7] pad = nn.Pad2D(padding=(1, 2, 1, 2), mode='constant') x = paddle.randn([2, 3, 4, 4]) out = pad(x) self.assertEqual(out.shape, [2, 3, 7, 7]) def test_pad1d(self): """Pad1D basic.""" pad = nn.Pad1D(padding=1, mode='constant') x = paddle.randn([2, 3, 10]) out = pad(x) self.assertEqual(out.shape, [2, 3, 12]) def test_pad3d(self): """Pad3D basic.""" pad = nn.Pad3D(padding=1, mode='constant') x = paddle.randn([2, 3, 4, 4, 4]) out = pad(x) self.assertEqual(out.shape, [2, 3, 6, 6, 6]) if __name__ == '__main__': unittest.main()