wehub-resource-sync
235 lines
7.3 KiB
Python
235 lines
7.3 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.conv (Conv1D, Conv2D, Conv3D, etc.)
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# 自动生成的单测，覆盖 paddle.nn.layer.conv 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/conv.py
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# 目标：覆盖 Conv 层的各种初始化参数组合和前向传播
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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. Conv1D - 各种参数 (stride, padding, dilation, groups)
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2. Conv2D - 各种参数 (padding_mode, weight_attr)
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3. Conv3D - 基本功能
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4. Conv1DTranspose - 各种参数
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5. Conv2DTranspose - 各种参数 (output_padding)
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6. Conv3DTranspose - 基本功能
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"""
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import unittest
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import paddle
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from paddle import nn
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class TestConv1D(unittest.TestCase):
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"""Test Conv1D layer.
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测试 Conv1D 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_conv1d_basic(self):
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"""Basic Conv1D."""
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conv = nn.Conv1D(3, 16, 3)
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x = paddle.randn([2, 3, 10])
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out = conv(x)
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self.assertEqual(out.shape, [2, 16, 8])
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def test_conv1d_padding_same(self):
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"""Conv1D with padding='same'."""
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conv = nn.Conv1D(3, 16, 3, padding='same')
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x = paddle.randn([2, 3, 10])
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out = conv(x)
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self.assertEqual(out.shape, [2, 16, 10])
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def test_conv1d_padding_valid(self):
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"""Conv1D with padding='valid'."""
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conv = nn.Conv1D(3, 16, 3, padding='valid')
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x = paddle.randn([2, 3, 10])
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out = conv(x)
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self.assertEqual(out.shape, [2, 16, 8])
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def test_conv1d_stride(self):
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"""Conv1D with stride."""
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conv = nn.Conv1D(3, 16, 3, stride=2)
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x = paddle.randn([2, 3, 10])
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out = conv(x)
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self.assertEqual(out.shape[2], 4)
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def test_conv1d_dilation(self):
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"""Conv1D with dilation."""
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conv = nn.Conv1D(3, 16, 3, dilation=2)
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x = paddle.randn([2, 3, 10])
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out = conv(x)
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self.assertEqual(out.shape[2], 6)
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def test_conv1d_groups(self):
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"""Conv1D with groups (depthwise)."""
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conv = nn.Conv1D(4, 4, 3, groups=4)
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x = paddle.randn([2, 4, 10])
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out = conv(x)
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self.assertEqual(out.shape[1], 4)
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def test_conv1d_bias_false(self):
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"""Conv1D without bias."""
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conv = nn.Conv1D(3, 16, 3, bias_attr=False)
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self.assertIsNone(conv.bias)
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class TestConv2D(unittest.TestCase):
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"""Test Conv2D layer.
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测试 Conv2D 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_conv2d_basic(self):
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"""Basic Conv2D."""
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conv = nn.Conv2D(3, 16, 3)
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x = paddle.randn([2, 3, 8, 8])
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out = conv(x)
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self.assertEqual(out.shape, [2, 16, 6, 6])
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def test_conv2d_padding_same(self):
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"""Conv2D with padding='same'."""
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conv = nn.Conv2D(3, 16, 3, padding='same')
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x = paddle.randn([2, 3, 8, 8])
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out = conv(x)
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self.assertEqual(out.shape, [2, 16, 8, 8])
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def test_conv2d_padding_valid(self):
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"""Conv2D with padding='valid'."""
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conv = nn.Conv2D(3, 16, 3, padding='valid')
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x = paddle.randn([2, 3, 8, 8])
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out = conv(x)
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self.assertEqual(out.shape, [2, 16, 6, 6])
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def test_conv2d_tuple_kernel(self):
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"""Conv2D with tuple kernel_size."""
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conv = nn.Conv2D(3, 16, (3, 5))
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x = paddle.randn([2, 3, 8, 10])
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out = conv(x)
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self.assertEqual(out.shape, [2, 16, 6, 6])
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def test_conv2d_tuple_padding(self):
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"""Conv2D with tuple padding."""
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conv = nn.Conv2D(3, 16, 3, padding=(1, 2))
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x = paddle.randn([2, 3, 8, 8])
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out = conv(x)
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self.assertEqual(out.shape, [2, 16, 8, 10])
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def test_conv2d_tuple_stride(self):
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"""Conv2D with tuple stride."""
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conv = nn.Conv2D(3, 16, 3, stride=(1, 2))
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x = paddle.randn([2, 3, 8, 8])
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out = conv(x)
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self.assertEqual(out.shape, [2, 16, 6, 3])
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def test_conv2d_dilation(self):
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"""Conv2D with dilation."""
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conv = nn.Conv2D(3, 16, 3, dilation=2)
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x = paddle.randn([2, 3, 8, 8])
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out = conv(x)
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self.assertEqual(out.shape, [2, 16, 4, 4])
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def test_conv2d_groups(self):
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"""Conv2D with groups."""
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conv = nn.Conv2D(4, 4, 3, groups=4)
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x = paddle.randn([2, 4, 8, 8])
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out = conv(x)
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self.assertEqual(out.shape[1], 4)
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def test_conv2d_bias_false(self):
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"""Conv2D without bias."""
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conv = nn.Conv2D(3, 16, 3, bias_attr=False)
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self.assertIsNone(conv.bias)
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class TestConv3D(unittest.TestCase):
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"""Test Conv3D layer.
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测试 Conv3D 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_conv3d_basic(self):
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"""Basic Conv3D."""
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conv = nn.Conv3D(3, 16, 3)
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x = paddle.randn([2, 3, 4, 4, 4])
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out = conv(x)
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self.assertEqual(out.shape, [2, 16, 2, 2, 2])
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def test_conv3d_padding_same(self):
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"""Conv3D with padding='same'."""
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conv = nn.Conv3D(3, 16, 3, padding='same')
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x = paddle.randn([2, 3, 4, 4, 4])
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out = conv(x)
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self.assertEqual(out.shape, [2, 16, 4, 4, 4])
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class TestConvTranspose(unittest.TestCase):
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"""Test ConvTranspose layers.
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测试 ConvTranspose 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_conv1d_transpose_basic(self):
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"""Basic Conv1DTranspose."""
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conv = nn.Conv1DTranspose(16, 3, 3)
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x = paddle.randn([2, 16, 4])
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out = conv(x)
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self.assertEqual(out.shape, [2, 3, 6])
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def test_conv2d_transpose_basic(self):
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"""Basic Conv2DTranspose."""
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conv = nn.Conv2DTranspose(16, 3, 3)
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x = paddle.randn([2, 16, 4, 4])
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out = conv(x)
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self.assertEqual(out.shape, [2, 3, 6, 6])
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def test_conv2d_transpose_with_output_padding(self):
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"""Conv2DTranspose with output_padding."""
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conv = nn.Conv2DTranspose(16, 3, 3, stride=2, output_padding=1)
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x = paddle.randn([2, 16, 4, 4])
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out = conv(x)
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# output_size = (input_size - 1) * stride - 2*padding + kernel + output_padding
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# = (4 - 1) * 2 - 0 + 3 + 1 = 10
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self.assertEqual(out.shape, [2, 3, 10, 10])
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def test_conv3d_transpose_basic(self):
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"""Basic Conv3DTranspose."""
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conv = nn.Conv3DTranspose(16, 3, 3)
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x = paddle.randn([2, 16, 2, 2, 2])
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out = conv(x)
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self.assertEqual(out.shape, [2, 3, 4, 4, 4])
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def test_conv2d_transpose_padding_same(self):
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"""Conv2DTranspose with padding='same'."""
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conv = nn.Conv2DTranspose(16, 3, 3, padding='same')
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x = paddle.randn([2, 16, 4, 4])
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out = conv(x)
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self.assertEqual(out.shape, [2, 3, 4, 4])
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if __name__ == '__main__':
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unittest.main()
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