mirror of
https://github.com/Tencent/ncnn.git
synced 2026-10-24 09:45:20 +08:00
Tijmen VerhulsdonckandRestyled.io
d1b5711791
* added avx implementations of FC and Max pool * Specify AVX2 * Small fixes and using Fused avx activations * fix type casting * fixing some CI errors * Fix code format * fix pooling test * remove vector typedef * More compile fixes * remove vector typedef * set c++ version to 17 * Force c++ 17 * Fixing mathfun * Try and workaround typedef issues * typefix * Remove typedef * switch to static inline * attempting to fix msvc bug * Verified MSVX FIX * Fixing clang build * commit before switch * More avx and packing implementation * Fix ctest * starting the depthwise pack 8 implementation * Unrolled loop * add depthwise pack 8 implementations * Working 1x1 pack 8 implementation added * revert incorrect changes * added conact elempack 8 * more elempack enabled layers added and started on the conversion of the winograd pack4 conv 3x3 * Added code formatting * fix styling * Unroll loops * unrolling loops * Added more elempac layers for mobilenet v3 * revert commit * fix code style * remove arm neon references * remove pack4 references * More cleanup * added packing avx code * fixing linux build ctests * remove usage of aligned loads * More aligned mem ops removed * Cleanup, revert some files and remove not working winograd and shufflechannel implementation * add stackoverflow referal * Fix windows build * Restyled by clang-format * Restyled by astyle * Restyled by clang-format * Restyled by astyle * implement requested chaanges * remove reshape * revert arm file change * Restyled by clang-format * Restyled by astyle * Restyled by clang-format * Restyled by astyle * fix unterminated directive Co-authored-by: Restyled.io <commits@restyled.io>
608 lines
18 KiB
C++
608 lines
18 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/packing.h"
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#include "testutil.h"
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static int test_packing_cpu(const ncnn::Mat& a, int in_elempack, int out_elempack)
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{
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ncnn::ParamDict pd;
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pd.set(0, out_elempack);
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std::vector<ncnn::Mat> weights(0);
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ncnn::Option opt;
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opt.num_threads = 1;
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opt.use_vulkan_compute = false;
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opt.use_int8_inference = false;
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opt.use_packing_layout = false;
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ncnn::Layer* op = ncnn::create_layer("Packing");
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op->load_param(pd);
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ncnn::ModelBinFromMatArray mb(weights.data());
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op->load_model(mb);
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op->create_pipeline(opt);
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ncnn::Mat ap;
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ncnn::convert_packing(a, ap, in_elempack);
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ncnn::Mat b;
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((ncnn::Packing*)op)->ncnn::Packing::forward(ap, b, opt);
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ncnn::Mat c;
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op->forward(ap, c, opt);
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op->destroy_pipeline(opt);
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delete op;
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if (CompareMat(b, c, 0.001) != 0)
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{
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fprintf(stderr, "test_packing_cpu failed a.dims=%d a=(%d %d %d) in_elempack=%d out_elempack=%d\n", a.dims, a.w, a.h, a.c, in_elempack, out_elempack);
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return -1;
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}
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return 0;
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}
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#if NCNN_VULKAN
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#include "layer/vulkan/packing_vulkan.h"
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static int test_packing_gpu_buffer(const ncnn::Mat& a, int in_elempack, int out_elempack)
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{
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ncnn::ParamDict pd;
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pd.set(0, out_elempack);
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pd.set(2, 1); // cast_type_from
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pd.set(3, 1); // cast_type_to
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pd.set(4, 0); // storage_type_from
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pd.set(5, 0); // storage_type_to
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std::vector<ncnn::Mat> weights(0);
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ncnn::Option opt;
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opt.num_threads = 1;
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opt.use_vulkan_compute = true;
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opt.use_int8_inference = false;
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opt.use_fp16_packed = false;
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opt.use_fp16_storage = false;
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opt.use_fp16_arithmetic = false;
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opt.use_int8_storage = false;
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opt.use_int8_arithmetic = false;
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opt.use_packing_layout = true;
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opt.use_shader_pack8 = true;
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opt.use_image_storage = false;
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ncnn::VulkanDevice* vkdev = ncnn::get_gpu_device();
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ncnn::VkAllocator* blob_vkallocator = vkdev->acquire_blob_allocator();
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ncnn::VkAllocator* staging_vkallocator = vkdev->acquire_staging_allocator();
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opt.blob_vkallocator = blob_vkallocator;
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opt.workspace_vkallocator = blob_vkallocator;
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opt.staging_vkallocator = staging_vkallocator;
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if (!vkdev->info.support_fp16_packed) opt.use_fp16_packed = false;
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if (!vkdev->info.support_fp16_storage) opt.use_fp16_storage = false;
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ncnn::Layer* op = ncnn::create_layer("Packing");
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op->vkdev = vkdev;
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op->load_param(pd);
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ncnn::ModelBinFromMatArray mb(weights.data());
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op->load_model(mb);
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op->create_pipeline(opt);
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ncnn::Mat ap;
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ncnn::convert_packing(a, ap, in_elempack);
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ncnn::Mat b;
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((ncnn::Packing*)op)->ncnn::Packing::forward(ap, b, opt);
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ncnn::Mat d;
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// forward
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ncnn::VkCompute cmd(vkdev);
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// upload
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ncnn::VkMat a_gpu;
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cmd.record_clone(ap, a_gpu, opt);
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ncnn::VkMat d_gpu;
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op->forward(a_gpu, d_gpu, cmd, opt);
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// download
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cmd.record_clone(d_gpu, d, opt);
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cmd.submit_and_wait();
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op->destroy_pipeline(opt);
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delete op;
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vkdev->reclaim_blob_allocator(blob_vkallocator);
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vkdev->reclaim_staging_allocator(staging_vkallocator);
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if (CompareMat(b, d, 0.001) != 0)
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{
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fprintf(stderr, "test_packing_gpu_buffer failed a.dims=%d a=(%d %d %d) in_elempack=%d out_elempack=%d\n", a.dims, a.w, a.h, a.c, in_elempack, out_elempack);
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return -1;
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}
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return 0;
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}
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static int test_packing_gpu_image(const ncnn::Mat& a, int in_elempack, int out_elempack)
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{
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ncnn::ParamDict pd;
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pd.set(0, out_elempack);
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pd.set(2, 1); // cast_type_from
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pd.set(3, 1); // cast_type_to
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pd.set(4, 1); // storage_type_from
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pd.set(5, 1); // storage_type_to
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std::vector<ncnn::Mat> weights(0);
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ncnn::Option opt;
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opt.num_threads = 1;
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opt.use_vulkan_compute = true;
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opt.use_int8_inference = false;
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opt.use_fp16_packed = false;
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opt.use_fp16_storage = false;
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opt.use_fp16_arithmetic = false;
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opt.use_int8_storage = false;
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opt.use_int8_arithmetic = false;
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opt.use_packing_layout = true;
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opt.use_shader_pack8 = true;
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opt.use_image_storage = true;
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ncnn::VulkanDevice* vkdev = ncnn::get_gpu_device();
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if (vkdev->info.bug_layout_binding_id_alias)
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return 0;
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ncnn::VkAllocator* blob_vkallocator = vkdev->acquire_blob_allocator();
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ncnn::VkAllocator* staging_vkallocator = vkdev->acquire_staging_allocator();
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opt.blob_vkallocator = blob_vkallocator;
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opt.workspace_vkallocator = blob_vkallocator;
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opt.staging_vkallocator = staging_vkallocator;
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if (!vkdev->info.support_fp16_packed) opt.use_fp16_packed = false;
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if (!vkdev->info.support_fp16_storage) opt.use_fp16_storage = false;
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ncnn::Layer* op = ncnn::create_layer("Packing");
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op->vkdev = vkdev;
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op->load_param(pd);
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ncnn::ModelBinFromMatArray mb(weights.data());
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op->load_model(mb);
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op->create_pipeline(opt);
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ncnn::Mat ap;
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ncnn::convert_packing(a, ap, in_elempack);
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ncnn::Mat b;
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((ncnn::Packing*)op)->ncnn::Packing::forward(ap, b, opt);
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ncnn::Mat d;
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// forward
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ncnn::VkCompute cmd(vkdev);
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// upload
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ncnn::VkImageMat a_gpu;
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cmd.record_clone(ap, a_gpu, opt);
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ncnn::VkImageMat d_gpu;
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op->forward(a_gpu, d_gpu, cmd, opt);
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// download
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cmd.record_clone(d_gpu, d, opt);
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cmd.submit_and_wait();
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op->destroy_pipeline(opt);
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delete op;
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vkdev->reclaim_blob_allocator(blob_vkallocator);
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vkdev->reclaim_staging_allocator(staging_vkallocator);
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if (CompareMat(b, d, 0.001) != 0)
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{
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fprintf(stderr, "test_packing_gpu_image failed a.dims=%d a=(%d %d %d) in_elempack=%d out_elempack=%d\n", a.dims, a.w, a.h, a.c, in_elempack, out_elempack);
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return -1;
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}
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return 0;
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}
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static int test_packing_gpu_buffer2image(const ncnn::Mat& a, int in_elempack, int out_elempack)
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{
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ncnn::ParamDict pd;
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pd.set(0, out_elempack);
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pd.set(2, 1); // cast_type_from
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pd.set(3, 1); // cast_type_to
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pd.set(4, 0); // storage_type_from
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pd.set(5, 1); // storage_type_to
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std::vector<ncnn::Mat> weights(0);
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ncnn::Option opt;
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opt.num_threads = 1;
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opt.use_vulkan_compute = true;
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opt.use_int8_inference = false;
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opt.use_fp16_packed = false;
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opt.use_fp16_storage = false;
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opt.use_fp16_arithmetic = false;
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opt.use_int8_storage = false;
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opt.use_int8_arithmetic = false;
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opt.use_packing_layout = true;
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opt.use_shader_pack8 = true;
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opt.use_image_storage = true;
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ncnn::VulkanDevice* vkdev = ncnn::get_gpu_device();
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if (vkdev->info.bug_layout_binding_id_alias)
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return 0;
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ncnn::VkAllocator* blob_vkallocator = vkdev->acquire_blob_allocator();
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ncnn::VkAllocator* staging_vkallocator = vkdev->acquire_staging_allocator();
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opt.blob_vkallocator = blob_vkallocator;
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opt.workspace_vkallocator = blob_vkallocator;
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opt.staging_vkallocator = staging_vkallocator;
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if (!vkdev->info.support_fp16_packed) opt.use_fp16_packed = false;
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if (!vkdev->info.support_fp16_storage) opt.use_fp16_storage = false;
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ncnn::Packing_vulkan* op = new ncnn::Packing_vulkan;
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op->vkdev = vkdev;
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op->load_param(pd);
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ncnn::ModelBinFromMatArray mb(weights.data());
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op->load_model(mb);
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op->create_pipeline(opt);
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ncnn::Mat ap;
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ncnn::convert_packing(a, ap, in_elempack);
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ncnn::Mat b;
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((ncnn::Packing*)op)->ncnn::Packing::forward(ap, b, opt);
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ncnn::Mat d;
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// forward
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ncnn::VkCompute cmd(vkdev);
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// upload
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ncnn::VkMat a_gpu;
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cmd.record_clone(ap, a_gpu, opt);
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ncnn::VkImageMat d_gpu;
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op->forward(a_gpu, d_gpu, cmd, opt);
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// download
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cmd.record_clone(d_gpu, d, opt);
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cmd.submit_and_wait();
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op->destroy_pipeline(opt);
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delete op;
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vkdev->reclaim_blob_allocator(blob_vkallocator);
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vkdev->reclaim_staging_allocator(staging_vkallocator);
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if (CompareMat(b, d, 0.001) != 0)
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{
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fprintf(stderr, "test_packing_gpu_buffer2image failed a.dims=%d a=(%d %d %d) in_elempack=%d out_elempack=%d\n", a.dims, a.w, a.h, a.c, in_elempack, out_elempack);
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return -1;
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}
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return 0;
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}
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static int test_packing_gpu_image2buffer(const ncnn::Mat& a, int in_elempack, int out_elempack)
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{
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ncnn::ParamDict pd;
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pd.set(0, out_elempack);
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pd.set(2, 1); // cast_type_from
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pd.set(3, 1); // cast_type_to
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pd.set(4, 1); // storage_type_from
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pd.set(5, 0); // storage_type_to
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std::vector<ncnn::Mat> weights(0);
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ncnn::Option opt;
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opt.num_threads = 1;
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opt.use_vulkan_compute = true;
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opt.use_int8_inference = false;
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opt.use_fp16_packed = false;
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opt.use_fp16_storage = false;
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opt.use_fp16_arithmetic = false;
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opt.use_int8_storage = false;
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opt.use_int8_arithmetic = false;
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opt.use_packing_layout = true;
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opt.use_shader_pack8 = true;
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opt.use_image_storage = true;
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ncnn::VulkanDevice* vkdev = ncnn::get_gpu_device();
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if (vkdev->info.bug_layout_binding_id_alias)
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return 0;
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ncnn::VkAllocator* blob_vkallocator = vkdev->acquire_blob_allocator();
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ncnn::VkAllocator* staging_vkallocator = vkdev->acquire_staging_allocator();
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opt.blob_vkallocator = blob_vkallocator;
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opt.workspace_vkallocator = blob_vkallocator;
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opt.staging_vkallocator = staging_vkallocator;
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if (!vkdev->info.support_fp16_packed) opt.use_fp16_packed = false;
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if (!vkdev->info.support_fp16_storage) opt.use_fp16_storage = false;
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ncnn::Packing_vulkan* op = new ncnn::Packing_vulkan;
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op->vkdev = vkdev;
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op->load_param(pd);
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ncnn::ModelBinFromMatArray mb(weights.data());
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op->load_model(mb);
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op->create_pipeline(opt);
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ncnn::Mat ap;
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ncnn::convert_packing(a, ap, in_elempack);
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ncnn::Mat b;
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((ncnn::Packing*)op)->ncnn::Packing::forward(ap, b, opt);
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ncnn::Mat d;
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// forward
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ncnn::VkCompute cmd(vkdev);
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// upload
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ncnn::VkImageMat a_gpu;
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cmd.record_clone(ap, a_gpu, opt);
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ncnn::VkMat d_gpu;
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op->forward(a_gpu, d_gpu, cmd, opt);
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// download
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cmd.record_clone(d_gpu, d, opt);
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cmd.submit_and_wait();
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op->destroy_pipeline(opt);
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delete op;
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vkdev->reclaim_blob_allocator(blob_vkallocator);
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vkdev->reclaim_staging_allocator(staging_vkallocator);
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if (CompareMat(b, d, 0.001) != 0)
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{
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fprintf(stderr, "test_packing_gpu_image2buffer failed a.dims=%d a=(%d %d %d) in_elempack=%d out_elempack=%d\n", a.dims, a.w, a.h, a.c, in_elempack, out_elempack);
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return -1;
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}
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return 0;
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}
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#endif
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static int test_packing_0()
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{
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ncnn::Mat a = RandomMat(9, 10, 16);
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ncnn::Mat b = RandomMat(9, 10, 3);
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return 0
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|| test_packing_cpu(a, 1, 1)
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|| test_packing_cpu(a, 4, 4)
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|| test_packing_cpu(a, 4, 8)
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|| test_packing_cpu(a, 1, 4)
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|| test_packing_cpu(a, 4, 1)
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|| test_packing_cpu(a, 1, 8)
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|| test_packing_cpu(a, 8, 1)
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|| test_packing_cpu(a, 4, 8)
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|| test_packing_cpu(a, 8, 4)
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|| test_packing_cpu(b, 1, 1)
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|| test_packing_cpu(b, 4, 4)
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|| test_packing_cpu(b, 4, 8)
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|| test_packing_cpu(b, 1, 4)
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|| test_packing_cpu(b, 4, 1)
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|| test_packing_cpu(b, 1, 8)
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|| test_packing_cpu(b, 8, 1)
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|| test_packing_cpu(b, 4, 8)
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|| test_packing_cpu(b, 8, 4)
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#if NCNN_VULKAN
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|| test_packing_gpu_buffer(a, 1, 1)
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|| test_packing_gpu_buffer(a, 4, 4)
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|| test_packing_gpu_buffer(a, 8, 8)
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|| test_packing_gpu_buffer(a, 1, 4)
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|| test_packing_gpu_buffer(a, 4, 1)
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|| test_packing_gpu_buffer(a, 1, 8)
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|| test_packing_gpu_buffer(a, 8, 1)
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|| test_packing_gpu_buffer(a, 4, 8)
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|| test_packing_gpu_buffer(a, 8, 4)
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|| test_packing_gpu_image(a, 1, 1)
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|| test_packing_gpu_image(a, 4, 4)
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|| test_packing_gpu_image(a, 8, 8)
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|| test_packing_gpu_image(a, 1, 4)
|
|
|| test_packing_gpu_image(a, 4, 1)
|
|
|| test_packing_gpu_image(a, 1, 8)
|
|
|| test_packing_gpu_image(a, 8, 1)
|
|
|| test_packing_gpu_image(a, 4, 8)
|
|
|| test_packing_gpu_image(a, 8, 4)
|
|
|| test_packing_gpu_buffer2image(a, 1, 1)
|
|
|| test_packing_gpu_buffer2image(a, 4, 4)
|
|
|| test_packing_gpu_buffer2image(a, 8, 8)
|
|
|| test_packing_gpu_buffer2image(a, 1, 4)
|
|
|| test_packing_gpu_buffer2image(a, 4, 1)
|
|
|| test_packing_gpu_buffer2image(a, 1, 8)
|
|
|| test_packing_gpu_buffer2image(a, 8, 1)
|
|
|| test_packing_gpu_buffer2image(a, 4, 8)
|
|
|| test_packing_gpu_buffer2image(a, 8, 4)
|
|
|| test_packing_gpu_image2buffer(a, 1, 1)
|
|
|| test_packing_gpu_image2buffer(a, 4, 4)
|
|
|| test_packing_gpu_image2buffer(a, 8, 8)
|
|
|| test_packing_gpu_image2buffer(a, 1, 4)
|
|
|| test_packing_gpu_image2buffer(a, 4, 1)
|
|
|| test_packing_gpu_image2buffer(a, 1, 8)
|
|
|| test_packing_gpu_image2buffer(a, 8, 1)
|
|
|| test_packing_gpu_image2buffer(a, 4, 8)
|
|
|| test_packing_gpu_image2buffer(a, 8, 4)
|
|
#endif // NCNN_VULKAN
|
|
;
|
|
}
|
|
|
|
static int test_packing_1()
|
|
{
|
|
ncnn::Mat a = RandomMat(9, 16);
|
|
|
|
return 0
|
|
|| test_packing_cpu(a, 1, 1)
|
|
|| test_packing_cpu(a, 4, 4)
|
|
|| test_packing_cpu(a, 4, 8)
|
|
|| test_packing_cpu(a, 1, 4)
|
|
|| test_packing_cpu(a, 4, 1)
|
|
|| test_packing_cpu(a, 1, 8)
|
|
|| test_packing_cpu(a, 8, 1)
|
|
|| test_packing_cpu(a, 4, 8)
|
|
|| test_packing_cpu(a, 8, 4)
|
|
#if NCNN_VULKAN
|
|
|| test_packing_gpu_buffer(a, 1, 1)
|
|
|| test_packing_gpu_buffer(a, 4, 4)
|
|
|| test_packing_gpu_buffer(a, 8, 8)
|
|
|| test_packing_gpu_buffer(a, 1, 4)
|
|
|| test_packing_gpu_buffer(a, 4, 1)
|
|
|| test_packing_gpu_buffer(a, 1, 8)
|
|
|| test_packing_gpu_buffer(a, 8, 1)
|
|
|| test_packing_gpu_buffer(a, 4, 8)
|
|
|| test_packing_gpu_buffer(a, 8, 4)
|
|
|| test_packing_gpu_image(a, 1, 1)
|
|
|| test_packing_gpu_image(a, 4, 4)
|
|
|| test_packing_gpu_image(a, 8, 8)
|
|
|| test_packing_gpu_image(a, 1, 4)
|
|
|| test_packing_gpu_image(a, 4, 1)
|
|
|| test_packing_gpu_image(a, 1, 8)
|
|
|| test_packing_gpu_image(a, 8, 1)
|
|
|| test_packing_gpu_image(a, 4, 8)
|
|
|| test_packing_gpu_image(a, 8, 4)
|
|
|| test_packing_gpu_buffer2image(a, 1, 1)
|
|
|| test_packing_gpu_buffer2image(a, 4, 4)
|
|
|| test_packing_gpu_buffer2image(a, 8, 8)
|
|
|| test_packing_gpu_buffer2image(a, 1, 4)
|
|
|| test_packing_gpu_buffer2image(a, 4, 1)
|
|
|| test_packing_gpu_buffer2image(a, 1, 8)
|
|
|| test_packing_gpu_buffer2image(a, 8, 1)
|
|
|| test_packing_gpu_buffer2image(a, 4, 8)
|
|
|| test_packing_gpu_buffer2image(a, 8, 4)
|
|
|| test_packing_gpu_image2buffer(a, 1, 1)
|
|
|| test_packing_gpu_image2buffer(a, 4, 4)
|
|
|| test_packing_gpu_image2buffer(a, 8, 8)
|
|
|| test_packing_gpu_image2buffer(a, 1, 4)
|
|
|| test_packing_gpu_image2buffer(a, 4, 1)
|
|
|| test_packing_gpu_image2buffer(a, 1, 8)
|
|
|| test_packing_gpu_image2buffer(a, 8, 1)
|
|
|| test_packing_gpu_image2buffer(a, 4, 8)
|
|
|| test_packing_gpu_image2buffer(a, 8, 4)
|
|
#endif // NCNN_VULKAN
|
|
;
|
|
}
|
|
|
|
static int test_packing_2()
|
|
{
|
|
ncnn::Mat a = RandomMat(40);
|
|
|
|
return 0
|
|
|| test_packing_cpu(a, 1, 1)
|
|
|| test_packing_cpu(a, 4, 4)
|
|
|| test_packing_cpu(a, 4, 8)
|
|
|| test_packing_cpu(a, 1, 4)
|
|
|| test_packing_cpu(a, 4, 1)
|
|
|| test_packing_cpu(a, 1, 8)
|
|
|| test_packing_cpu(a, 8, 1)
|
|
|| test_packing_cpu(a, 4, 8)
|
|
|| test_packing_cpu(a, 8, 4)
|
|
#if NCNN_VULKAN
|
|
|| test_packing_gpu_buffer(a, 1, 1)
|
|
|| test_packing_gpu_buffer(a, 4, 4)
|
|
|| test_packing_gpu_buffer(a, 8, 8)
|
|
|| test_packing_gpu_buffer(a, 1, 4)
|
|
|| test_packing_gpu_buffer(a, 4, 1)
|
|
|| test_packing_gpu_buffer(a, 1, 8)
|
|
|| test_packing_gpu_buffer(a, 8, 1)
|
|
|| test_packing_gpu_buffer(a, 4, 8)
|
|
|| test_packing_gpu_buffer(a, 8, 4)
|
|
|| test_packing_gpu_image(a, 1, 1)
|
|
|| test_packing_gpu_image(a, 4, 4)
|
|
|| test_packing_gpu_image(a, 8, 8)
|
|
|| test_packing_gpu_image(a, 1, 4)
|
|
|| test_packing_gpu_image(a, 4, 1)
|
|
|| test_packing_gpu_image(a, 1, 8)
|
|
|| test_packing_gpu_image(a, 8, 1)
|
|
|| test_packing_gpu_image(a, 4, 8)
|
|
|| test_packing_gpu_image(a, 8, 4)
|
|
|| test_packing_gpu_buffer2image(a, 1, 1)
|
|
|| test_packing_gpu_buffer2image(a, 4, 4)
|
|
|| test_packing_gpu_buffer2image(a, 8, 8)
|
|
|| test_packing_gpu_buffer2image(a, 1, 4)
|
|
|| test_packing_gpu_buffer2image(a, 4, 1)
|
|
|| test_packing_gpu_buffer2image(a, 1, 8)
|
|
|| test_packing_gpu_buffer2image(a, 8, 1)
|
|
|| test_packing_gpu_buffer2image(a, 4, 8)
|
|
|| test_packing_gpu_buffer2image(a, 8, 4)
|
|
|| test_packing_gpu_image2buffer(a, 1, 1)
|
|
|| test_packing_gpu_image2buffer(a, 4, 4)
|
|
|| test_packing_gpu_image2buffer(a, 8, 8)
|
|
|| test_packing_gpu_image2buffer(a, 1, 4)
|
|
|| test_packing_gpu_image2buffer(a, 4, 1)
|
|
|| test_packing_gpu_image2buffer(a, 1, 8)
|
|
|| test_packing_gpu_image2buffer(a, 8, 1)
|
|
|| test_packing_gpu_image2buffer(a, 4, 8)
|
|
|| test_packing_gpu_image2buffer(a, 8, 4)
|
|
#endif // NCNN_VULKAN
|
|
;
|
|
}
|
|
|
|
int main()
|
|
{
|
|
SRAND(7767517);
|
|
|
|
return 0
|
|
|| test_packing_0()
|
|
|| test_packing_1()
|
|
|| test_packing_2();
|
|
}
|