deepin-ocr/3rdparty/ncnn/tests/test_rnn.cpp
wangzhengyang 718c41634f feat: 切换后端至PaddleOCR-NCNN,切换工程为CMake
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
2022-05-10 10:22:11 +08:00

257 lines
10 KiB
C++

// Tencent is pleased to support the open source community by making ncnn available.
//
// Copyright (C) 2021 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/rnn.h"
#include "testutil.h"
static int test_rnn(const ncnn::Mat& a, int outch, int direction)
{
int input_size = a.w;
int num_directions = direction == 2 ? 2 : 1;
ncnn::ParamDict pd;
pd.set(0, outch);
pd.set(1, outch * input_size * num_directions);
pd.set(2, direction);
std::vector<ncnn::Mat> weights(3);
weights[0] = RandomMat(outch * input_size * num_directions);
weights[1] = RandomMat(outch * num_directions);
weights[2] = RandomMat(outch * outch * num_directions);
int ret = test_layer<ncnn::RNN>("RNN", pd, weights, a);
if (ret != 0)
{
fprintf(stderr, "test_rnn failed a.dims=%d a=(%d %d %d) outch=%d, direction = %d \n", a.dims, a.w, a.h, a.c, outch, direction);
}
return ret;
}
int test_rnn_layer_with_hidden(const ncnn::Mat& a, int outch, int direction)
{
int input_size = a.w;
int num_directions = direction == 2 ? 2 : 1;
ncnn::ParamDict pd;
pd.set(0, outch);
pd.set(1, outch * input_size * num_directions);
pd.set(2, direction);
std::vector<ncnn::Mat> weights(3);
weights[0] = RandomMat(outch * input_size * num_directions);
weights[1] = RandomMat(outch * num_directions);
weights[2] = RandomMat(outch * outch * num_directions);
// initial hidden state
ncnn::Mat hidden = RandomMat(outch, num_directions);
std::vector<ncnn::Mat> as(2);
as[0] = a;
as[1] = hidden;
int ret = test_layer<ncnn::RNN>("RNN", pd, weights, as, 2);
if (ret != 0)
{
fprintf(stderr, "test_rnn_layer_with_hidden failed a.dims=%d a=(%d %d %d) outch=%d, direction = %d \n", a.dims, a.w, a.h, a.c, outch, direction);
}
return ret;
}
int test_rnn_layer_with_hidden_input(const ncnn::Mat& a, int outch, int direction)
{
int input_size = a.w;
int num_directions = direction == 2 ? 2 : 1;
ncnn::ParamDict pd;
pd.set(0, outch);
pd.set(1, outch * input_size * num_directions);
pd.set(2, direction);
std::vector<ncnn::Mat> weights(3);
weights[0] = RandomMat(outch * input_size * num_directions);
weights[1] = RandomMat(outch * num_directions);
weights[2] = RandomMat(outch * outch * num_directions);
// initial hidden state
ncnn::Mat hidden = RandomMat(outch, num_directions);
std::vector<ncnn::Mat> as(2);
as[0] = a;
as[1] = hidden;
int ret = test_layer<ncnn::RNN>("RNN", pd, weights, as, 1);
if (ret != 0)
{
fprintf(stderr, "test_rnn_layer_with_hidden_input failed a.dims=%d a=(%d %d %d) outch=%d, direction = %d \n", a.dims, a.w, a.h, a.c, outch, direction);
}
return ret;
}
int test_rnn_layer_with_hidden_output(const ncnn::Mat& a, int outch, int direction)
{
int input_size = a.w;
int num_directions = direction == 2 ? 2 : 1;
ncnn::ParamDict pd;
pd.set(0, outch);
pd.set(1, outch * input_size * num_directions);
pd.set(2, direction);
std::vector<ncnn::Mat> weights(3);
weights[0] = RandomMat(outch * input_size * num_directions);
weights[1] = RandomMat(outch * num_directions);
weights[2] = RandomMat(outch * outch * num_directions);
std::vector<ncnn::Mat> as(1);
as[0] = a;
int ret = test_layer<ncnn::RNN>("RNN", pd, weights, as, 2);
if (ret != 0)
{
fprintf(stderr, "test_rnn_layer_with_hidden_output failed a.dims=%d a=(%d %d %d) outch=%d, direction = %d \n", a.dims, a.w, a.h, a.c, outch, direction);
}
return ret;
}
static int test_rnn_0()
{
return 0
|| test_rnn(RandomMat(4, 1), 2, 2)
|| test_rnn(RandomMat(8, 2), 2, 2)
|| test_rnn(RandomMat(16, 8), 7, 2)
|| test_rnn(RandomMat(17, 8), 8, 2)
|| test_rnn(RandomMat(19, 15), 8, 2)
|| test_rnn(RandomMat(5, 16), 16, 2)
|| test_rnn(RandomMat(3, 16), 8, 2)
|| test_rnn(RandomMat(8, 16), 16, 2)
|| test_rnn(RandomMat(2, 5), 17, 2);
}
static int test_rnn_1()
{
return 0
|| test_rnn_layer_with_hidden(RandomMat(4, 4), 1, 2)
|| test_rnn_layer_with_hidden(RandomMat(8, 2), 2, 2)
|| test_rnn_layer_with_hidden(RandomMat(16, 8), 7, 2)
|| test_rnn_layer_with_hidden(RandomMat(17, 8), 8, 2)
|| test_rnn_layer_with_hidden(RandomMat(19, 15), 8, 2)
|| test_rnn_layer_with_hidden(RandomMat(5, 16), 16, 2)
|| test_rnn_layer_with_hidden(RandomMat(3, 16), 8, 2)
|| test_rnn_layer_with_hidden(RandomMat(2, 5), 99, 2)
|| test_rnn_layer_with_hidden(RandomMat(4, 4), 1, 1)
|| test_rnn_layer_with_hidden(RandomMat(8, 2), 2, 1)
|| test_rnn_layer_with_hidden(RandomMat(16, 8), 7, 1)
|| test_rnn_layer_with_hidden(RandomMat(17, 8), 8, 1)
|| test_rnn_layer_with_hidden(RandomMat(19, 15), 8, 1)
|| test_rnn_layer_with_hidden(RandomMat(5, 16), 16, 1)
|| test_rnn_layer_with_hidden(RandomMat(3, 16), 8, 1)
|| test_rnn_layer_with_hidden(RandomMat(2, 5), 99, 1)
|| test_rnn_layer_with_hidden(RandomMat(4, 2), 1, 0)
|| test_rnn_layer_with_hidden(RandomMat(8, 2), 2, 0)
|| test_rnn_layer_with_hidden(RandomMat(16, 8), 7, 0)
|| test_rnn_layer_with_hidden(RandomMat(17, 8), 8, 0)
|| test_rnn_layer_with_hidden(RandomMat(19, 15), 8, 0)
|| test_rnn_layer_with_hidden(RandomMat(5, 16), 16, 0)
|| test_rnn_layer_with_hidden(RandomMat(3, 16), 8, 0)
|| test_rnn_layer_with_hidden(RandomMat(2, 5), 17, 0)
|| test_rnn_layer_with_hidden_input(RandomMat(4, 4), 1, 2)
|| test_rnn_layer_with_hidden_input(RandomMat(8, 2), 2, 2)
|| test_rnn_layer_with_hidden_input(RandomMat(16, 8), 7, 2)
|| test_rnn_layer_with_hidden_input(RandomMat(17, 8), 8, 2)
|| test_rnn_layer_with_hidden_input(RandomMat(19, 15), 8, 2)
|| test_rnn_layer_with_hidden_input(RandomMat(5, 16), 16, 2)
|| test_rnn_layer_with_hidden_input(RandomMat(3, 16), 8, 2)
|| test_rnn_layer_with_hidden_input(RandomMat(2, 5), 99, 2)
|| test_rnn_layer_with_hidden_input(RandomMat(4, 4), 1, 1)
|| test_rnn_layer_with_hidden_input(RandomMat(8, 2), 2, 1)
|| test_rnn_layer_with_hidden_input(RandomMat(16, 8), 7, 1)
|| test_rnn_layer_with_hidden_input(RandomMat(17, 8), 8, 1)
|| test_rnn_layer_with_hidden_input(RandomMat(19, 15), 8, 1)
|| test_rnn_layer_with_hidden_input(RandomMat(5, 16), 16, 1)
|| test_rnn_layer_with_hidden_input(RandomMat(3, 16), 8, 1)
|| test_rnn_layer_with_hidden_input(RandomMat(2, 5), 99, 1)
|| test_rnn_layer_with_hidden_input(RandomMat(4, 2), 1, 0)
|| test_rnn_layer_with_hidden_input(RandomMat(8, 2), 2, 0)
|| test_rnn_layer_with_hidden_input(RandomMat(16, 8), 7, 0)
|| test_rnn_layer_with_hidden_input(RandomMat(17, 8), 8, 0)
|| test_rnn_layer_with_hidden_input(RandomMat(19, 15), 8, 0)
|| test_rnn_layer_with_hidden_input(RandomMat(5, 16), 16, 0)
|| test_rnn_layer_with_hidden_input(RandomMat(3, 16), 8, 0)
|| test_rnn_layer_with_hidden_input(RandomMat(2, 5), 17, 0)
|| test_rnn_layer_with_hidden_output(RandomMat(4, 4), 1, 2)
|| test_rnn_layer_with_hidden_output(RandomMat(8, 2), 2, 2)
|| test_rnn_layer_with_hidden_output(RandomMat(16, 8), 7, 2)
|| test_rnn_layer_with_hidden_output(RandomMat(17, 8), 8, 2)
|| test_rnn_layer_with_hidden_output(RandomMat(19, 15), 8, 2)
|| test_rnn_layer_with_hidden_output(RandomMat(5, 16), 16, 2)
|| test_rnn_layer_with_hidden_output(RandomMat(3, 16), 8, 2)
|| test_rnn_layer_with_hidden_output(RandomMat(2, 5), 99, 2)
|| test_rnn_layer_with_hidden_output(RandomMat(4, 4), 1, 1)
|| test_rnn_layer_with_hidden_output(RandomMat(8, 2), 2, 1)
|| test_rnn_layer_with_hidden_output(RandomMat(16, 8), 7, 1)
|| test_rnn_layer_with_hidden_output(RandomMat(17, 8), 8, 1)
|| test_rnn_layer_with_hidden_output(RandomMat(19, 15), 8, 1)
|| test_rnn_layer_with_hidden_output(RandomMat(5, 16), 16, 1)
|| test_rnn_layer_with_hidden_output(RandomMat(3, 16), 8, 1)
|| test_rnn_layer_with_hidden_output(RandomMat(2, 5), 99, 1)
|| test_rnn_layer_with_hidden_output(RandomMat(4, 2), 1, 0)
|| test_rnn_layer_with_hidden_output(RandomMat(8, 2), 2, 0)
|| test_rnn_layer_with_hidden_output(RandomMat(16, 8), 7, 0)
|| test_rnn_layer_with_hidden_output(RandomMat(17, 8), 8, 0)
|| test_rnn_layer_with_hidden_output(RandomMat(19, 15), 8, 0)
|| test_rnn_layer_with_hidden_output(RandomMat(5, 16), 16, 0)
|| test_rnn_layer_with_hidden_output(RandomMat(3, 16), 8, 0)
|| test_rnn_layer_with_hidden_output(RandomMat(2, 5), 17, 0);
}
static int test_rnn_2()
{
return 0
|| test_rnn(RandomMat(4, 1), 1, 0)
|| test_rnn(RandomMat(8, 2), 2, 0)
|| test_rnn(RandomMat(16, 8), 7, 0)
|| test_rnn(RandomMat(17, 8), 8, 0)
|| test_rnn(RandomMat(19, 15), 8, 0)
|| test_rnn(RandomMat(5, 16), 16, 0)
|| test_rnn(RandomMat(3, 16), 8, 0)
|| test_rnn(RandomMat(8, 16), 16, 0)
|| test_rnn(RandomMat(2, 5), 17, 0);
}
static int test_rnn_3()
{
return 0
|| test_rnn(RandomMat(4, 1), 1, 1)
|| test_rnn(RandomMat(8, 2), 2, 1)
|| test_rnn(RandomMat(16, 8), 7, 1)
|| test_rnn(RandomMat(17, 8), 8, 1)
|| test_rnn(RandomMat(19, 15), 8, 1)
|| test_rnn(RandomMat(5, 16), 16, 1)
|| test_rnn(RandomMat(3, 16), 8, 1)
|| test_rnn(RandomMat(8, 16), 16, 1)
|| test_rnn(RandomMat(2, 5), 17, 1);
}
int main()
{
SRAND(7767517);
return test_rnn_0() || test_rnn_1() || test_rnn_2() || test_rnn_3();
}