mirror of
https://github.com/Tencent/ncnn.git
synced 2026-10-18 21:54:39 +08:00
nihui
388 lines
9.5 KiB
C++
388 lines
9.5 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) 2020 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/binaryop.h"
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#include "testutil.h"
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#define OP_TYPE_MAX 10
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static int op_type = 0;
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static int test_binaryop(const ncnn::Mat& _a, const ncnn::Mat& _b)
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{
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ncnn::Mat a = _a;
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ncnn::Mat b = _b;
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if (op_type == 6 || op_type == 9)
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{
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// value must be positive for pow/rpow
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a = a.clone();
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b = b.clone();
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Randomize(a, 0.001f, 2.f);
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Randomize(b, 0.001f, 2.f);
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}
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if (op_type == 3 || op_type == 8)
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{
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// value must be positive for div/rdiv
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a = a.clone();
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b = b.clone();
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Randomize(a, 0.1f, 10.f);
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Randomize(b, 0.1f, 10.f);
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}
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ncnn::ParamDict pd;
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pd.set(0, op_type);
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pd.set(1, 0); // with_scalar
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pd.set(2, 0.f); // b
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std::vector<ncnn::Mat> weights(0);
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std::vector<ncnn::Mat> ab(2);
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ab[0] = a;
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ab[1] = b;
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int ret = test_layer<ncnn::BinaryOp>("BinaryOp", pd, weights, ab);
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if (ret != 0)
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{
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fprintf(stderr, "test_binaryop failed a.dims=%d a=(%d %d %d %d) b.dims=%d b=(%d %d %d %d) op_type=%d\n", a.dims, a.w, a.h, a.d, a.c, b.dims, b.w, b.h, b.d, b.c, op_type);
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}
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return ret;
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}
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static int test_binaryop(const ncnn::Mat& _a, float b)
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{
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ncnn::Mat a = _a;
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if (op_type == 6 || op_type == 9)
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{
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// value must be positive for pow
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Randomize(a, 0.001f, 2.f);
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b = RandomFloat(0.001f, 2.f);
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}
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if (op_type == 3 || op_type == 8)
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{
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// value must be positive for div/rdiv
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a = a.clone();
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Randomize(a, 0.1f, 10.f);
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}
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ncnn::ParamDict pd;
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pd.set(0, op_type);
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pd.set(1, 1); // with_scalar
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pd.set(2, b); // b
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std::vector<ncnn::Mat> weights(0);
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int ret = test_layer<ncnn::BinaryOp>("BinaryOp", pd, weights, a);
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if (ret != 0)
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{
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fprintf(stderr, "test_binaryop failed a.dims=%d a=(%d %d %d %d) b=%f op_type=%d\n", a.dims, a.w, a.h, a.d, a.c, b, op_type);
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}
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return ret;
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}
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static int test_binaryop_1()
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{
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ncnn::Mat a[] = {
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RandomMat(31),
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RandomMat(28),
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RandomMat(24),
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RandomMat(32),
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RandomMat(13, 31),
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RandomMat(14, 28),
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RandomMat(15, 24),
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RandomMat(16, 32),
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RandomMat(7, 3, 31),
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RandomMat(6, 4, 28),
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RandomMat(5, 5, 24),
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RandomMat(4, 6, 32),
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RandomMat(2, 7, 3, 31),
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RandomMat(3, 6, 4, 28),
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RandomMat(4, 5, 5, 24),
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RandomMat(5, 4, 6, 32)
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};
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ncnn::Mat b[] = {
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RandomMat(1),
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RandomMat(1, 1),
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RandomMat(1, 1, 1),
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RandomMat(1, 1, 1, 1)
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};
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for (int i = 0; i < sizeof(a) / sizeof(a[0]); i++)
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{
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for (int j = 0; j < sizeof(b) / sizeof(b[0]); j++)
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{
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int ret = test_binaryop(a[i], b[j]) || test_binaryop(b[j], a[i]);
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if (ret != 0)
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return ret;
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}
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int ret = test_binaryop(a[i], 0.2f);
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if (ret != 0)
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return ret;
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}
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return 0;
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}
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static int test_binaryop_2()
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{
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ncnn::Mat a[] = {
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RandomMat(31),
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RandomMat(28),
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RandomMat(24),
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RandomMat(32),
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RandomMat(13, 31),
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RandomMat(14, 28),
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RandomMat(15, 24),
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RandomMat(16, 32),
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RandomMat(7, 3, 31),
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RandomMat(6, 4, 28),
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RandomMat(5, 5, 24),
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RandomMat(4, 6, 32),
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RandomMat(2, 7, 3, 31),
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RandomMat(3, 6, 4, 28),
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RandomMat(4, 5, 5, 24),
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RandomMat(5, 4, 6, 32)
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};
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for (int i = 0; i < sizeof(a) / sizeof(a[0]); i++)
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{
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ncnn::Mat b;
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b.create_like(a[i]);
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Randomize(b);
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int ret = test_binaryop(a[i], b) || test_binaryop(b, a[i]);
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if (ret != 0)
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return ret;
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}
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return 0;
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}
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static int test_binaryop_3()
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{
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ncnn::Mat a[] = {
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RandomMat(13, 31),
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RandomMat(14, 28),
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RandomMat(15, 24),
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RandomMat(16, 32)
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};
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for (int i = 0; i < sizeof(a) / sizeof(a[0]); i++)
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{
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ncnn::Mat b0(a[i].h);
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ncnn::Mat b1(1, a[i].h);
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Randomize(b0);
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Randomize(b1);
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int ret = test_binaryop(a[i], b0) || test_binaryop(b0, a[i])
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|| test_binaryop(a[i], b1) || test_binaryop(b1, a[i]);
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if (ret != 0)
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return ret;
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}
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return 0;
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}
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static int test_binaryop_4()
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{
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ncnn::Mat a[] = {
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RandomMat(7, 3, 31),
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RandomMat(6, 4, 28),
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RandomMat(5, 5, 24),
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RandomMat(4, 6, 32)
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};
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for (int i = 0; i < sizeof(a) / sizeof(a[0]); i++)
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{
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ncnn::Mat b0(a[i].c);
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ncnn::Mat b1(1, 1, a[i].c);
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ncnn::Mat b2(a[i].h, a[i].c);
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ncnn::Mat b3(1, a[i].h, a[i].c);
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Randomize(b0);
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Randomize(b1);
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Randomize(b2);
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Randomize(b3);
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int ret = test_binaryop(a[i], b0) || test_binaryop(b0, a[i])
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|| test_binaryop(a[i], b1) || test_binaryop(b1, a[i])
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|| test_binaryop(a[i], b2) || test_binaryop(b2, a[i])
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|| test_binaryop(a[i], b3) || test_binaryop(b3, a[i]);
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if (ret != 0)
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return ret;
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}
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return 0;
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}
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static int test_binaryop_5()
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{
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ncnn::Mat a[] = {
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RandomMat(2, 7, 3, 31),
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RandomMat(3, 6, 4, 28),
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RandomMat(4, 5, 5, 24),
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RandomMat(5, 4, 6, 32)
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};
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for (int i = 0; i < sizeof(a) / sizeof(a[0]); i++)
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{
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ncnn::Mat b0(a[i].c);
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ncnn::Mat b1(1, 1, 1, a[i].c);
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ncnn::Mat b2(a[i].d, a[i].c);
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ncnn::Mat b3(1, 1, a[i].d, a[i].c);
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ncnn::Mat b4(a[i].h, a[i].d, a[i].c);
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ncnn::Mat b5(1, a[i].h, a[i].d, a[i].c);
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Randomize(b0);
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Randomize(b1);
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Randomize(b2);
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Randomize(b3);
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Randomize(b4);
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Randomize(b5);
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int ret = test_binaryop(a[i], b0) || test_binaryop(b0, a[i])
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|| test_binaryop(a[i], b1) || test_binaryop(b1, a[i])
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|| test_binaryop(a[i], b2) || test_binaryop(b2, a[i])
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|| test_binaryop(a[i], b3) || test_binaryop(b3, a[i])
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|| test_binaryop(a[i], b4) || test_binaryop(b4, a[i])
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|| test_binaryop(a[i], b5) || test_binaryop(b5, a[i]);
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if (ret != 0)
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return ret;
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}
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return 0;
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}
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static int test_binaryop_6()
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{
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ncnn::Mat a[] = {
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RandomMat(13, 31),
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RandomMat(14, 28),
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RandomMat(15, 24),
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RandomMat(16, 32)
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};
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for (int i = 0; i < sizeof(a) / sizeof(a[0]); i++)
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{
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ncnn::Mat b0(a[i].w, 1);
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Randomize(b0);
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int ret = test_binaryop(a[i], b0) || test_binaryop(b0, a[i]);
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if (ret != 0)
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return ret;
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}
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return 0;
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}
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static int test_binaryop_7()
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{
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ncnn::Mat a[] = {
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RandomMat(7, 3, 31),
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RandomMat(6, 4, 28),
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RandomMat(5, 5, 24),
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RandomMat(4, 6, 32)
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};
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for (int i = 0; i < sizeof(a) / sizeof(a[0]); i++)
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{
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ncnn::Mat b0(a[i].w, 1, 1);
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ncnn::Mat b1(a[i].w, a[i].h, 1);
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Randomize(b0);
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Randomize(b1);
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int ret = test_binaryop(a[i], b0) || test_binaryop(b0, a[i])
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|| test_binaryop(a[i], b1) || test_binaryop(b1, a[i]);
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if (ret != 0)
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return ret;
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}
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return 0;
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}
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static int test_binaryop_8()
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{
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ncnn::Mat a[] = {
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RandomMat(2, 7, 3, 31),
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RandomMat(3, 6, 4, 28),
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RandomMat(4, 5, 5, 24),
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RandomMat(5, 4, 6, 32)
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};
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for (int i = 0; i < sizeof(a) / sizeof(a[0]); i++)
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{
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ncnn::Mat b0(a[i].w, 1, 1, 1);
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ncnn::Mat b1(a[i].w, a[i].h, 1, 1);
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ncnn::Mat b2(a[i].w, a[i].h, a[i].d, 1);
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Randomize(b0);
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Randomize(b1);
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Randomize(b2);
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int ret = test_binaryop(a[i], b0) || test_binaryop(b0, a[i])
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|| test_binaryop(a[i], b1) || test_binaryop(b1, a[i])
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|| test_binaryop(a[i], b2) || test_binaryop(b2, a[i]);
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if (ret != 0)
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return ret;
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}
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return 0;
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}
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static int test_binaryop_9()
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{
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ncnn::Mat a[] = {
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RandomMat(7, 3, 31),
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RandomMat(6, 4, 28),
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RandomMat(5, 5, 24),
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RandomMat(4, 6, 32)
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};
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for (int i = 0; i < sizeof(a) / sizeof(a[0]); i++)
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{
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ncnn::Mat b0(a[i].w, 1, a[i].c);
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Randomize(b0);
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int ret = test_binaryop(a[i], b0) || test_binaryop(b0, a[i]);
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if (ret != 0)
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return ret;
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}
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return 0;
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}
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int main()
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{
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SRAND(7767517);
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for (op_type = 0; op_type < 3; op_type++)
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{
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int ret = 0
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|| test_binaryop_1()
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|| test_binaryop_2()
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|| test_binaryop_3()
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|| test_binaryop_4()
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|| test_binaryop_5()
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|| test_binaryop_6()
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|| test_binaryop_7()
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|| test_binaryop_8()
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|| test_binaryop_9();
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if (ret != 0)
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return ret;
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}
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return 0;
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}
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