ncnn

test_multiheadattention.cpp
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// 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 "testutil.h"
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static int test_multiheadattention(const ncnn::Mat& q, const ncnn::Mat& k, const ncnn::Mat& v, int embed_dim, int num_heads, int attn_mask)
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{
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    const int qdim = q.w;
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    const int kdim = k.w;
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    const int vdim = v.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 * qdim);
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    pd.set(3, kdim);
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    pd.set(4, vdim);
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    pd.set(5, attn_mask);
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    std::vector<ncnn::Mat> weights(8);
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    weights[0] = RandomMat(embed_dim * qdim);
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    weights[1] = RandomMat(embed_dim);
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    weights[2] = RandomMat(embed_dim * kdim);
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    weights[3] = RandomMat(embed_dim);
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    weights[4] = RandomMat(embed_dim * vdim);
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    weights[5] = RandomMat(embed_dim);
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    weights[6] = RandomMat(qdim * embed_dim);
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    weights[7] = RandomMat(qdim);
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    std::vector<ncnn::Mat> as(3);
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    as[0] = q;
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    as[1] = k;
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    as[2] = v;
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    if (attn_mask)
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    {
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        as.push_back(RandomMat(k.h, q.h));
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    }
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    float epsilon = 0.005;
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    int ret = test_layer("MultiHeadAttention", pd, weights, as, 1, epsilon);
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    if (ret != 0)
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    {
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        fprintf(stderr, "test_multiheadattention failed q=(%d %d) k=(%d %d) v=(%d %d) embed_dim=%d num_heads=%d kdim=%d vdim=%d attn_mask=%d\n", q.w, q.h, k.w, k.h, v.w, v.h, embed_dim, num_heads, kdim, vdim, attn_mask);
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    }
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    return ret;
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}
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static int test_multiheadattention_samekv(const ncnn::Mat& q, const ncnn::Mat& kv, int embed_dim, int num_heads)
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{
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    const int qdim = q.w;
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    const int kvdim = kv.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 * qdim);
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    pd.set(3, kvdim);
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    pd.set(4, kvdim);
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    std::vector<ncnn::Mat> weights(8);
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    weights[0] = RandomMat(embed_dim * qdim);
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    weights[1] = RandomMat(embed_dim);
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    weights[2] = RandomMat(embed_dim * kvdim);
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    weights[3] = RandomMat(embed_dim);
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    weights[4] = RandomMat(embed_dim * kvdim);
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    weights[5] = RandomMat(embed_dim);
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    weights[6] = RandomMat(qdim * embed_dim);
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    weights[7] = RandomMat(qdim);
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    std::vector<ncnn::Mat> as(2);
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    as[0] = q;
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    as[1] = kv;
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    float epsilon = 0.005;
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    int ret = test_layer("MultiHeadAttention", pd, weights, as, 1, epsilon);
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    if (ret != 0)
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    {
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        fprintf(stderr, "test_multiheadattention_samekv failed q=(%d %d) kv=(%d %d) embed_dim=%d num_heads=%d kvdim=%d\n", q.w, q.h, kv.w, kv.h, embed_dim, num_heads, kvdim);
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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 embed_dim, int num_heads)
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{
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    const int qdim = 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 * qdim);
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    pd.set(3, qdim);
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    pd.set(4, qdim);
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    pd.set(6, 0.7f / sqrtf(embed_dim / num_heads));
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    std::vector<ncnn::Mat> weights(8);
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    weights[0] = RandomMat(embed_dim * qdim);
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    weights[1] = RandomMat(embed_dim);
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    weights[2] = RandomMat(embed_dim * qdim);
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    weights[3] = RandomMat(embed_dim);
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    weights[4] = RandomMat(embed_dim * qdim);
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    weights[5] = RandomMat(embed_dim);
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    weights[6] = RandomMat(qdim * embed_dim);
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    weights[7] = RandomMat(qdim);
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    std::vector<ncnn::Mat> as(1);
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    as[0] = a;
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    float epsilon = 0.005;
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    int ret = test_layer("MultiHeadAttention", pd, weights, as, 1, epsilon);
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    if (ret != 0)
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    {
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        fprintf(stderr, "test_multiheadattention_sameqkv failed a=(%d %d) embed_dim=%d num_heads=%d\n", a.w, a.h, embed_dim, num_heads);
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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(62, 66), RandomMat(32, 66), RandomMat(20, 66), 62, 2, 0)
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           || test_multiheadattention(RandomMat(26, 64), RandomMat(32, 64), RandomMat(18, 64), 26, 2, 1)
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           || test_multiheadattention(RandomMat(64, 128), RandomMat(64, 128), RandomMat(64, 128), 64, 4, 0)
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           || test_multiheadattention(RandomMat(48, 127), RandomMat(64, 127), RandomMat(64, 127), 64, 16, 1)
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           || test_multiheadattention(RandomMat(16, 128), RandomMat(44, 128), RandomMat(55, 128), 16, 2, 0)
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           || test_multiheadattention(RandomMat(12, 128), RandomMat(44, 127), RandomMat(55, 127), 16, 4, 1)
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           || test_multiheadattention(RandomMat(12, 17), RandomMat(28, 127), RandomMat(32, 127), 12, 3, 0)
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           || test_multiheadattention(RandomMat(12, 17), RandomMat(28, 32), RandomMat(11, 32), 12, 3, 1);
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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_samekv(RandomMat(64, 128), RandomMat(64, 128), 64, 4)
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           || test_multiheadattention_samekv(RandomMat(48, 127), RandomMat(64, 127), 64, 16)
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           || test_multiheadattention_samekv(RandomMat(16, 128), RandomMat(44, 128), 16, 2)
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           || test_multiheadattention_samekv(RandomMat(12, 128), RandomMat(22, 127), 16, 4)
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           || test_multiheadattention_samekv(RandomMat(12, 17), RandomMat(28, 127), 12, 3)
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           || test_multiheadattention_samekv(RandomMat(12, 17), RandomMat(11, 32), 12, 3);
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}
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static int test_multiheadattention_2()
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{
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    return 0
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           || test_multiheadattention_sameqkv(RandomMat(64, 128), 64, 4)
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           || test_multiheadattention_sameqkv(RandomMat(48, 127), 64, 8);
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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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           || test_multiheadattention_2();
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}
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