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
104 lines
3.0 KiB
C++
104 lines
3.0 KiB
C++
// Tencent is pleased to support the open source community by making ncnn available.
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//
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// Copyright (C) 2021 THL A29 Limited, a Tencent company. All rights reserved.
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//
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// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
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// in compliance with the License. You may obtain a copy of the License at
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//
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// https://opensource.org/licenses/BSD-3-Clause
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//
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// Unless required by applicable law or agreed to in writing, software distributed
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// under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
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// CONDITIONS OF ANY KIND, either express or implied. See the License for the
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// specific language governing permissions and limitations under the License.
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#include "layer/multiheadattention.h"
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#include "testutil.h"
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static int test_multiheadattention(const ncnn::Mat& a, int num_heads)
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{
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int embed_dim = a.w;
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ncnn::ParamDict pd;
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pd.set(0, embed_dim);
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pd.set(1, num_heads);
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pd.set(2, embed_dim * embed_dim);
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std::vector<ncnn::Mat> weights(8);
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weights[0] = RandomMat(embed_dim * embed_dim);
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weights[1] = RandomMat(embed_dim);
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weights[2] = RandomMat(embed_dim * embed_dim);
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weights[3] = RandomMat(embed_dim);
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weights[4] = RandomMat(embed_dim * embed_dim);
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weights[5] = RandomMat(embed_dim);
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weights[6] = RandomMat(embed_dim * embed_dim);
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weights[7] = RandomMat(embed_dim);
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std::vector<ncnn::Mat> as(3);
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as[0] = a;
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as[1] = a;
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as[2] = a;
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int ret = test_layer<ncnn::MultiHeadAttention>("MultiHeadAttention", pd, weights, as);
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if (ret != 0)
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{
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fprintf(stderr, "test_multiheadattention failed a=(%d %d)\n", a.w, a.h);
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}
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return ret;
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}
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static int test_multiheadattention_sameqkv(const ncnn::Mat& a, int num_heads)
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{
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int embed_dim = a.w;
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ncnn::ParamDict pd;
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pd.set(0, embed_dim);
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pd.set(1, num_heads);
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pd.set(2, embed_dim * embed_dim);
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std::vector<ncnn::Mat> weights(8);
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weights[0] = RandomMat(embed_dim * embed_dim);
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weights[1] = RandomMat(embed_dim);
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weights[2] = RandomMat(embed_dim * embed_dim);
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weights[3] = RandomMat(embed_dim);
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weights[4] = RandomMat(embed_dim * embed_dim);
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weights[5] = RandomMat(embed_dim);
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weights[6] = RandomMat(embed_dim * embed_dim);
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weights[7] = RandomMat(embed_dim);
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std::vector<ncnn::Mat> as(1);
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as[0] = a;
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int ret = test_layer<ncnn::MultiHeadAttention>("MultiHeadAttention", pd, weights, as);
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if (ret != 0)
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{
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fprintf(stderr, "test_multiheadattention failed a=(%d %d)\n", a.w, a.h);
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}
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return ret;
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}
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static int test_multiheadattention_0()
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{
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return 0
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|| test_multiheadattention(RandomMat(64, 128), 4)
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|| test_multiheadattention(RandomMat(64, 127), 16);
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}
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static int test_multiheadattention_1()
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{
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return 0
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|| test_multiheadattention_sameqkv(RandomMat(64, 128), 8)
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|| test_multiheadattention_sameqkv(RandomMat(64, 127), 32);
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}
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int main()
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{
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SRAND(7767517);
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return 0
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|| test_multiheadattention_0()
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|| test_multiheadattention_1();
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}
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