718c41634f
1.项目后端整体迁移至PaddleOCR-NCNN算法,已通过基本的兼容性测试 2.工程改为使用CMake组织,后续为了更好地兼容第三方库,不再提供QMake工程 3.重整权利声明文件,重整代码工程,确保最小化侵权风险 Log: 切换后端至PaddleOCR-NCNN,切换工程为CMake Change-Id: I4d5d2c5d37505a4a24b389b1a4c5d12f17bfa38c
111 lines
4.6 KiB
C++
111 lines
4.6 KiB
C++
// Tencent is pleased to support the open source community by making ncnn available.
|
|
//
|
|
// Copyright (C) 2022 THL A29 Limited, a Tencent company. All rights reserved.
|
|
//
|
|
// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
|
|
// in compliance with the License. You may obtain a copy of the License at
|
|
//
|
|
// https://opensource.org/licenses/BSD-3-Clause
|
|
//
|
|
// 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.
|
|
|
|
#include "layer/deconvolutiondepthwise3d.h"
|
|
#include "testutil.h"
|
|
|
|
static int test_deconvolutiondepthwise3d(int w, int h, int d, int c, int outch, int kernel, int dilation, int stride, int pad, int bias, int group, int output_pad_right, int output_pad_bottom, int output_pad_behind, int output_w, int output_h, int output_d)
|
|
{
|
|
ncnn::Mat a = RandomMat(w, h, d, c);
|
|
|
|
if (output_w > 0 && output_h > 0 && output_d > 0 && pad != -233 && pad != -234)
|
|
{
|
|
pad = -233;
|
|
}
|
|
|
|
ncnn::ParamDict pd;
|
|
pd.set(0, outch);
|
|
pd.set(1, kernel);
|
|
pd.set(2, dilation);
|
|
pd.set(3, stride);
|
|
pd.set(4, pad);
|
|
pd.set(5, bias);
|
|
pd.set(6, outch / group * c / group * kernel * kernel * kernel * group);
|
|
pd.set(7, group);
|
|
|
|
int activation_type = RAND() % 5; // 0 1 2 3 4
|
|
ncnn::Mat activation_params(2);
|
|
activation_params[0] = RandomFloat(-1, 0); // alpha
|
|
activation_params[1] = RandomFloat(0, 1); // beta
|
|
pd.set(9, activation_type);
|
|
pd.set(10, activation_params);
|
|
|
|
pd.set(18, output_pad_right);
|
|
pd.set(19, output_pad_bottom);
|
|
pd.set(20, output_pad_behind);
|
|
pd.set(25, output_w);
|
|
pd.set(26, output_h);
|
|
pd.set(27, output_d);
|
|
|
|
std::vector<ncnn::Mat> weights(2);
|
|
weights[0] = RandomMat(outch / group * c / group * kernel * kernel * kernel * group);
|
|
weights[1] = RandomMat(outch);
|
|
|
|
int ret = test_layer<ncnn::DeconvolutionDepthWise3D>("DeconvolutionDepthWise3D", pd, weights, a);
|
|
if (ret != 0)
|
|
{
|
|
fprintf(stderr, "test_deconvolutiondepthwise3d failed w=%d h=%d d=%d c=%d outch=%d kernel=%d dilation=%d stride=%d pad=%d bias=%d group=%d act=%d actparams=[%f,%f] output_pad_right=%d output_pad_bottom=%d output_pad_behind=%d output_w=%d output_h=%d output_d=%d\n", w, h, c, outch, kernel, dilation, stride, pad, bias, group, activation_type, activation_params[0], activation_params[1], output_pad_right, output_pad_bottom, output_pad_behind, output_w, output_h, output_d);
|
|
}
|
|
|
|
return ret;
|
|
}
|
|
|
|
static int test_deconvolutiondepthwise3d_0()
|
|
{
|
|
static const int kdsp[7][4] = {
|
|
{1, 1, 1, 0},
|
|
{1, 1, 2, 0},
|
|
{2, 1, 1, 1},
|
|
{2, 1, 2, -233},
|
|
{3, 1, 1, 1},
|
|
{3, 1, 2, 1},
|
|
{3, 2, 1, -234},
|
|
};
|
|
|
|
for (int i = 0; i < 7; i++)
|
|
{
|
|
const int k = kdsp[i][0];
|
|
const int d = kdsp[i][1];
|
|
const int s = kdsp[i][2];
|
|
const int p = kdsp[i][3];
|
|
|
|
int ret = 0
|
|
|| test_deconvolutiondepthwise3d(15, 11, 7, 1, 1, k, d, s, p, 1, 1, 0, 0, 0, 0, 0, 0)
|
|
|| test_deconvolutiondepthwise3d(15, 11, 7, 2, 2, k, d, s, p, 0, 1, 1, 1, 1, 7, 6, 5)
|
|
|| test_deconvolutiondepthwise3d(15, 11, 7, 2, 2, k, d, s, p, 1, 2, 1, 0, 0, 0, 0, 0)
|
|
|| test_deconvolutiondepthwise3d(15, 11, 7, 3, 3, k, d, s, p, 0, 3, 0, 1, 0, 0, 0, 0)
|
|
|| test_deconvolutiondepthwise3d(15, 11, 7, 4, 2, k, d, s, p, 1, 2, 0, 0, 0, 7, 6, 5)
|
|
|| test_deconvolutiondepthwise3d(15, 11, 7, 4, 4, k, d, s, p, 0, 4, 2, 2, 2, 0, 0, 0)
|
|
|| test_deconvolutiondepthwise3d(15, 11, 7, 7, 7, k, d, s, p, 1, 7, 2, 0, 2, 0, 0, 0)
|
|
|| test_deconvolutiondepthwise3d(15, 11, 7, 8, 8, k, d, s, p, 0, 2, 0, 2, 0, 7, 6, 5)
|
|
|| test_deconvolutiondepthwise3d(15, 11, 7, 8, 8, k, d, s, p, 1, 8, 0, 0, 0, 0, 0, 0)
|
|
|| test_deconvolutiondepthwise3d(15, 11, 7, 12, 12, k, d, s, p, 0, 4, 3, 3, 3, 0, 0, 0)
|
|
|| test_deconvolutiondepthwise3d(15, 11, 7, 15, 15, k, d, s, p, 1, 15, 3, 0, 0, 7, 6, 5)
|
|
|| test_deconvolutiondepthwise3d(15, 11, 7, 16, 8, k, d, s, p, 0, 2, 0, 3, 3, 0, 0, 0)
|
|
|| test_deconvolutiondepthwise3d(15, 11, 7, 16, 16, k, d, s, p, 1, 16, 0, 0, 0, 0, 0, 0);
|
|
|
|
if (ret != 0)
|
|
return -1;
|
|
}
|
|
|
|
return 0;
|
|
}
|
|
|
|
int main()
|
|
{
|
|
SRAND(7767517);
|
|
|
|
return test_deconvolutiondepthwise3d_0();
|
|
}
|