在线图片编辑器,网站优化网站建设,在线制作gif,网站开发与管理大作业对动作捕捉的几篇论文感兴趣#xff0c;想复现一下#xff0c;需要caffe环境就折腾了下#xff01;转模型需要python 2.7环境#xff0c;我顺便也弄了#xff01;#xff01;#xff01;
1. 环境
Windows10 RTX2080TI 11G Anaconda Python2.7 visual studio 2013 cuda…对动作捕捉的几篇论文感兴趣想复现一下需要caffe环境就折腾了下转模型需要python 2.7环境我顺便也弄了
1. 环境
Windows10 RTX2080TI 11G Anaconda Python2.7 visual studio 2013 cuda 11.1 cudnn 8.2.0 cmake 3.26.1 git
2. 具体步骤
2.1 安装cuda和cudnn
略 这部分看其他博客 cuda_11.1.0_456.43_win10.exe cudnn-11.3-windows-x64-v8.2.0.53.zip
2.2 安装caffe
1.下载源码
git clone https://github.com/BVLC/caffe.git
cd caffe
git checkout windows2.修改build_win.cmd 这一步决定着后面能不能编译成功 path/caffe/scripts/build_win.cmd
a.需要确定visual studio的版本 MSVC版本号对应关系 我在这边踩了坑因为我看的那个博客这边弄错了。这个链接没问题。MSVC_VERSION 12表示VS2013MSVC_VERSION 14表示VS2015 b.确定GPU的显卡架构 架构表 一定要看 下面开始修改文件: 1.修改caffe源码中./scripts/build_win.cmd 修改caffe源码中./cmake/Cuda.cmake: 我的显卡是2080ti对应着75我只要保证有75就行 这里的80需要根据我的显卡情况改成75 这里面是一定要改的不然找不到cudnn因为caffe之类的代码很久不更新了只支持到了使用cudnn7.x在使用了cudnn8的环境下编译caffe时会在src/caffe/layers/cudnn_conv_layer.cpp等文件里出错 报错信息是这样的
error: identifier CUDNN_CONVOLUTION_FWD_SPECIFY_WORKSPACE_LIMIT is undefined
error: identifier cudnnGetConvolutionForwardAlgorithm is undefined这是因为cudnn8里没有cudnnGetConvolutionForwardAlgorithm()这个函数了改成了cudnnGetConvolutionForwardAlgorithm_v7()也没了CUDNN_CONVOLUTION_FWD_SPECIFY_WORKSPACE_LIMIT这个宏定义这些都是API不兼容但是NVIDIA声明cudnn8不支持了caffe的代码也没人去更新了所以不能指望NVIDIA或者berkeley只能自行修改。将cudnn_conv_layer.cpp文件替换成如下:
#ifdef USE_CUDNN
#include algorithm
#include vector#include caffe/layers/cudnn_conv_layer.hppnamespace caffe {// Set to three for the benefit of the backward pass, which
// can use separate streams for calculating the gradient w.r.t.
// bias, filter weights, and bottom data for each group independently
#define CUDNN_STREAMS_PER_GROUP 3/*** TODO(dox) explain cuDNN interface*/
template typename Dtype
void CuDNNConvolutionLayerDtype::LayerSetUp(const vectorBlobDtype* bottom, const vectorBlobDtype* top) {ConvolutionLayerDtype::LayerSetUp(bottom, top);// Initialize CUDA streams and cuDNN.stream_ new cudaStream_t[this-group_ * CUDNN_STREAMS_PER_GROUP];handle_ new cudnnHandle_t[this-group_ * CUDNN_STREAMS_PER_GROUP];// Initialize algorithm arraysfwd_algo_ new cudnnConvolutionFwdAlgo_t[bottom.size()];bwd_filter_algo_ new cudnnConvolutionBwdFilterAlgo_t[bottom.size()];bwd_data_algo_ new cudnnConvolutionBwdDataAlgo_t[bottom.size()];// initialize size arraysworkspace_fwd_sizes_ new size_t[bottom.size()];workspace_bwd_filter_sizes_ new size_t[bottom.size()];workspace_bwd_data_sizes_ new size_t[bottom.size()];// workspace dataworkspaceSizeInBytes 0;workspaceData NULL;workspace new void*[this-group_ * CUDNN_STREAMS_PER_GROUP];for (size_t i 0; i bottom.size(); i) {// initialize all to default algorithmsfwd_algo_[i] (cudnnConvolutionFwdAlgo_t)0;bwd_filter_algo_[i] (cudnnConvolutionBwdFilterAlgo_t)0;bwd_data_algo_[i] (cudnnConvolutionBwdDataAlgo_t)0;// default algorithms dont require workspaceworkspace_fwd_sizes_[i] 0;workspace_bwd_data_sizes_[i] 0;workspace_bwd_filter_sizes_[i] 0;}for (int g 0; g this-group_ * CUDNN_STREAMS_PER_GROUP; g) {CUDA_CHECK(cudaStreamCreate(stream_[g]));CUDNN_CHECK(cudnnCreate(handle_[g]));CUDNN_CHECK(cudnnSetStream(handle_[g], stream_[g]));workspace[g] NULL;}// Set the indexing parameters.bias_offset_ (this-num_output_ / this-group_);// Create filter descriptor.const int* kernel_shape_data this-kernel_shape_.cpu_data();const int kernel_h kernel_shape_data[0];const int kernel_w kernel_shape_data[1];cudnn::createFilterDescDtype(filter_desc_,this-num_output_ / this-group_, this-channels_ / this-group_,kernel_h, kernel_w);// Create tensor descriptor(s) for data and corresponding convolution(s).for (int i 0; i bottom.size(); i) {cudnnTensorDescriptor_t bottom_desc;cudnn::createTensor4dDescDtype(bottom_desc);bottom_descs_.push_back(bottom_desc);cudnnTensorDescriptor_t top_desc;cudnn::createTensor4dDescDtype(top_desc);top_descs_.push_back(top_desc);cudnnConvolutionDescriptor_t conv_desc;cudnn::createConvolutionDescDtype(conv_desc);conv_descs_.push_back(conv_desc);}// Tensor descriptor for bias.if (this-bias_term_) {cudnn::createTensor4dDescDtype(bias_desc_);}handles_setup_ true;
}template typename Dtype
void CuDNNConvolutionLayerDtype::Reshape(const vectorBlobDtype* bottom, const vectorBlobDtype* top) {ConvolutionLayerDtype::Reshape(bottom, top);CHECK_EQ(2, this-num_spatial_axes_) CuDNNConvolution input must have 2 spatial axes (e.g., height and width). Use engine: CAFFE for general ND convolution.;bottom_offset_ this-bottom_dim_ / this-group_;top_offset_ this-top_dim_ / this-group_;const int height bottom[0]-shape(this-channel_axis_ 1);const int width bottom[0]-shape(this-channel_axis_ 2);const int height_out top[0]-shape(this-channel_axis_ 1);const int width_out top[0]-shape(this-channel_axis_ 2);const int* pad_data this-pad_.cpu_data();const int pad_h pad_data[0];const int pad_w pad_data[1];const int* stride_data this-stride_.cpu_data();const int stride_h stride_data[0];const int stride_w stride_data[1];
#if CUDNN_VERSION_MIN(8, 0, 0)int RetCnt;bool found_conv_algorithm;size_t free_memory, total_memory;cudnnConvolutionFwdAlgoPerf_t fwd_algo_pref_[4];cudnnConvolutionBwdDataAlgoPerf_t bwd_data_algo_pref_[4];//get memory sizescudaMemGetInfo(free_memory, total_memory);
#else// Specify workspace limit for kernels directly until we have a// planning strategy and a rewrite of Caffes GPU memory mangagementsize_t workspace_limit_bytes 8*1024*1024;
#endiffor (int i 0; i bottom.size(); i) {cudnn::setTensor4dDescDtype(bottom_descs_[i],this-num_,this-channels_ / this-group_, height, width,this-channels_ * height * width,height * width, width, 1);cudnn::setTensor4dDescDtype(top_descs_[i],this-num_,this-num_output_ / this-group_, height_out, width_out,this-num_output_ * this-out_spatial_dim_,this-out_spatial_dim_, width_out, 1);cudnn::setConvolutionDescDtype(conv_descs_[i], bottom_descs_[i],filter_desc_, pad_h, pad_w,stride_h, stride_w);#if CUDNN_VERSION_MIN(8, 0, 0)// choose forward algorithm for filter// in forward filter the CUDNN_CONVOLUTION_FWD_ALGO_WINOGRAD_NONFUSED is not implemented in cuDNN 8CUDNN_CHECK(cudnnGetConvolutionForwardAlgorithm_v7(handle_[0],bottom_descs_[i],filter_desc_,conv_descs_[i],top_descs_[i],4,RetCnt,fwd_algo_pref_));found_conv_algorithm false;for(int n0;nRetCnt;n){if (fwd_algo_pref_[n].status CUDNN_STATUS_SUCCESS fwd_algo_pref_[n].algo ! CUDNN_CONVOLUTION_FWD_ALGO_WINOGRAD_NONFUSED fwd_algo_pref_[n].memory free_memory){found_conv_algorithm true;fwd_algo_[i] fwd_algo_pref_[n].algo;workspace_fwd_sizes_[i] fwd_algo_pref_[n].memory;break;}}if(!found_conv_algorithm) LOG(ERROR) cuDNN did not return a suitable algorithm for convolution.;else{// choose backward algorithm for filter// for better or worse, just a fixed constant due to the missing // cudnnGetConvolutionBackwardFilterAlgorithm in cuDNN version 8.0bwd_filter_algo_[i] CUDNN_CONVOLUTION_BWD_FILTER_ALGO_0;//twice the amount of the forward search to be save workspace_bwd_filter_sizes_[i] 2*workspace_fwd_sizes_[i];}// choose backward algo for dataCUDNN_CHECK(cudnnGetConvolutionBackwardDataAlgorithm_v7(handle_[0],filter_desc_, top_descs_[i], conv_descs_[i], bottom_descs_[i],4,RetCnt,bwd_data_algo_pref_));found_conv_algorithm false;for(int n0;nRetCnt;n){if (bwd_data_algo_pref_[n].status CUDNN_STATUS_SUCCESS bwd_data_algo_pref_[n].algo ! CUDNN_CONVOLUTION_BWD_DATA_ALGO_WINOGRAD bwd_data_algo_pref_[n].algo ! CUDNN_CONVOLUTION_BWD_DATA_ALGO_WINOGRAD_NONFUSED bwd_data_algo_pref_[n].memory free_memory){found_conv_algorithm true;bwd_data_algo_[i] bwd_data_algo_pref_[n].algo;workspace_bwd_data_sizes_[i] bwd_data_algo_pref_[n].memory;break;}}if(!found_conv_algorithm) LOG(ERROR) cuDNN did not return a suitable algorithm for convolution.;
#else// choose forward and backward algorithms workspace(s)CUDNN_CHECK(cudnnGetConvolutionForwardAlgorithm(handle_[0],bottom_descs_[i],filter_desc_,conv_descs_[i],top_descs_[i],CUDNN_CONVOLUTION_FWD_SPECIFY_WORKSPACE_LIMIT,workspace_limit_bytes,fwd_algo_[i]));CUDNN_CHECK(cudnnGetConvolutionForwardWorkspaceSize(handle_[0],bottom_descs_[i],filter_desc_,conv_descs_[i],top_descs_[i],fwd_algo_[i],(workspace_fwd_sizes_[i])));// choose backward algorithm for filterCUDNN_CHECK(cudnnGetConvolutionBackwardFilterAlgorithm(handle_[0],bottom_descs_[i], top_descs_[i], conv_descs_[i], filter_desc_,CUDNN_CONVOLUTION_BWD_FILTER_SPECIFY_WORKSPACE_LIMIT,workspace_limit_bytes, bwd_filter_algo_[i]) );// get workspace for backwards filter algorithmCUDNN_CHECK(cudnnGetConvolutionBackwardFilterWorkspaceSize(handle_[0],bottom_descs_[i], top_descs_[i], conv_descs_[i], filter_desc_,bwd_filter_algo_[i], workspace_bwd_filter_sizes_[i]));// choose backward algo for dataCUDNN_CHECK(cudnnGetConvolutionBackwardDataAlgorithm(handle_[0],filter_desc_, top_descs_[i], conv_descs_[i], bottom_descs_[i],CUDNN_CONVOLUTION_BWD_DATA_SPECIFY_WORKSPACE_LIMIT,workspace_limit_bytes, bwd_data_algo_[i]));// get workspace sizeCUDNN_CHECK(cudnnGetConvolutionBackwardDataWorkspaceSize(handle_[0],filter_desc_, top_descs_[i], conv_descs_[i], bottom_descs_[i],bwd_data_algo_[i], workspace_bwd_data_sizes_[i]) );
#endif}// reduce over all workspace sizes to get a maximum to allocate / reallocatesize_t total_workspace_fwd 0;size_t total_workspace_bwd_data 0;size_t total_workspace_bwd_filter 0;for (size_t i 0; i bottom.size(); i) {total_workspace_fwd std::max(total_workspace_fwd,workspace_fwd_sizes_[i]);total_workspace_bwd_data std::max(total_workspace_bwd_data,workspace_bwd_data_sizes_[i]);total_workspace_bwd_filter std::max(total_workspace_bwd_filter,workspace_bwd_filter_sizes_[i]);}// get max over all operationssize_t max_workspace std::max(total_workspace_fwd,total_workspace_bwd_data);max_workspace std::max(max_workspace, total_workspace_bwd_filter);// ensure all groups have enough workspacesize_t total_max_workspace max_workspace *(this-group_ * CUDNN_STREAMS_PER_GROUP);// this is the total amount of storage needed over all groups streamsif (total_max_workspace workspaceSizeInBytes) {DLOG(INFO) Reallocating workspace storage: total_max_workspace;workspaceSizeInBytes total_max_workspace;// free the existing workspace and allocate a new (larger) onecudaFree(this-workspaceData);cudaError_t err cudaMalloc((this-workspaceData), workspaceSizeInBytes);if (err ! cudaSuccess) {// force zero memory pathfor (int i 0; i bottom.size(); i) {workspace_fwd_sizes_[i] 0;workspace_bwd_filter_sizes_[i] 0;workspace_bwd_data_sizes_[i] 0;fwd_algo_[i] CUDNN_CONVOLUTION_FWD_ALGO_IMPLICIT_GEMM;bwd_filter_algo_[i] CUDNN_CONVOLUTION_BWD_FILTER_ALGO_0;bwd_data_algo_[i] CUDNN_CONVOLUTION_BWD_DATA_ALGO_0;}// NULL out all workspace pointersfor (int g 0; g (this-group_ * CUDNN_STREAMS_PER_GROUP); g) {workspace[g] NULL;}// NULL out underlying dataworkspaceData NULL;workspaceSizeInBytes 0;}// if we succeed in the allocation, set pointer aliases for workspacesfor (int g 0; g (this-group_ * CUDNN_STREAMS_PER_GROUP); g) {workspace[g] reinterpret_castchar *(workspaceData) g*max_workspace;}}// Tensor descriptor for bias.if (this-bias_term_) {cudnn::setTensor4dDescDtype(bias_desc_,1, this-num_output_ / this-group_, 1, 1);}
}template typename Dtype
CuDNNConvolutionLayerDtype::~CuDNNConvolutionLayer() {// Check that handles have been setup before destroying.if (!handles_setup_) { return; }for (int i 0; i bottom_descs_.size(); i) {cudnnDestroyTensorDescriptor(bottom_descs_[i]);cudnnDestroyTensorDescriptor(top_descs_[i]);cudnnDestroyConvolutionDescriptor(conv_descs_[i]);}if (this-bias_term_) {cudnnDestroyTensorDescriptor(bias_desc_);}cudnnDestroyFilterDescriptor(filter_desc_);for (int g 0; g this-group_ * CUDNN_STREAMS_PER_GROUP; g) {cudaStreamDestroy(stream_[g]);cudnnDestroy(handle_[g]);}cudaFree(workspaceData);delete [] stream_;delete [] handle_;delete [] fwd_algo_;delete [] bwd_filter_algo_;delete [] bwd_data_algo_;delete [] workspace_fwd_sizes_;delete [] workspace_bwd_data_sizes_;delete [] workspace_bwd_filter_sizes_;
}INSTANTIATE_CLASS(CuDNNConvolutionLayer);} // namespace caffe
#endif在命令行窗口运行 scripts/build_win.cmd会下载libraries_v120_x64_py27_1.1.0.tar.bz2文件最好挂个梯子我这边下的很快。这个文件是caffe相关的依赖库此过程中编译的时候会报一个boost相关的错误对C:\Users\qiao\.caffe\dependencies\libraries_v120_x64_py27_1.1.0\libraries\include\boost-1_61\boost\config\compiler路径下的 nvcc.hpp 作如下修改因为RTX2080ti的编译器nvcc版本大于7.5 之后删除之前编译的build文件夹重新编译一次编译过程中会出现较多警告可以不用理会稍等一段时间后最终会出现 最后在build文件夹下找到Caffe.sln文件用VS2013打开然后右键ALL_BUILD进行生成等几分钟后编译完 release版本 debug版本 将caffe源码下中python中的caffe文件夹粘贴到上面配置的python路径中D:\Anaconda3\envs\pycaffe27\Lib\site-packages再将E:\caffe\build\install\bin路径添加到环境变量中在终端中测试一下caffe命令是否正常然后pip安装一些必要的库 pip install numpy scipy protobuf six scikit-image pyyaml pydotplus graphviz 最后打开python测试一下 参考文献: Windows10 下RTX30系列Caffe安装教程 Windows10下搭建caffe过程记录 文章转载自： http://www.morning.kpygy.cn.gov.cn.kpygy.cn http://www.morning.lssfd.cn.gov.cn.lssfd.cn http://www.morning.mhpkz.cn.gov.cn.mhpkz.cn http://www.morning.dxzcr.cn.gov.cn.dxzcr.cn http://www.morning.rlpmy.cn.gov.cn.rlpmy.cn http://www.morning.slysg.cn.gov.cn.slysg.cn http://www.morning.zwtp.cn.gov.cn.zwtp.cn http://www.morning.ummpdl.cn.gov.cn.ummpdl.cn http://www.morning.hcxhz.cn.gov.cn.hcxhz.cn http://www.morning.sfgzx.cn.gov.cn.sfgzx.cn http://www.morning.dmldp.cn.gov.cn.dmldp.cn http://www.morning.ycmpk.cn.gov.cn.ycmpk.cn http://www.morning.nkrmh.cn.gov.cn.nkrmh.cn http://www.morning.tqrjj.cn.gov.cn.tqrjj.cn http://www.morning.jxltk.cn.gov.cn.jxltk.cn http://www.morning.zcckq.cn.gov.cn.zcckq.cn http://www.morning.sjsks.cn.gov.cn.sjsks.cn http://www.morning.mhcys.cn.gov.cn.mhcys.cn http://www.morning.swimstaracademy.cn.gov.cn.swimstaracademy.cn http://www.morning.cjqcx.cn.gov.cn.cjqcx.cn http://www.morning.ccdyc.cn.gov.cn.ccdyc.cn http://www.morning.fcftj.cn.gov.cn.fcftj.cn http://www.morning.jwgnn.cn.gov.cn.jwgnn.cn http://www.morning.cwlxs.cn.gov.cn.cwlxs.cn http://www.morning.tstkr.cn.gov.cn.tstkr.cn http://www.morning.gwmjy.cn.gov.cn.gwmjy.cn http://www.morning.fjptn.cn.gov.cn.fjptn.cn http://www.morning.llmhq.cn.gov.cn.llmhq.cn http://www.morning.yyngs.cn.gov.cn.yyngs.cn http://www.morning.kpxky.cn.gov.cn.kpxky.cn http://www.morning.ffrys.cn.gov.cn.ffrys.cn http://www.morning.ktskc.cn.gov.cn.ktskc.cn http://www.morning.ktmbp.cn.gov.cn.ktmbp.cn http://www.morning.qqxmj.cn.gov.cn.qqxmj.cn http://www.morning.rqlf.cn.gov.cn.rqlf.cn http://www.morning.nkqrq.cn.gov.cn.nkqrq.cn http://www.morning.cpnlq.cn.gov.cn.cpnlq.cn http://www.morning.lmpfk.cn.gov.cn.lmpfk.cn http://www.morning.qkqzm.cn.gov.cn.qkqzm.cn http://www.morning.kcfnp.cn.gov.cn.kcfnp.cn http://www.morning.rwmqp.cn.gov.cn.rwmqp.cn http://www.morning.zzgkk.cn.gov.cn.zzgkk.cn http://www.morning.rghkg.cn.gov.cn.rghkg.cn http://www.morning.tfsyk.cn.gov.cn.tfsyk.cn http://www.morning.zbjfq.cn.gov.cn.zbjfq.cn http://www.morning.rlbc.cn.gov.cn.rlbc.cn http://www.morning.dkqyg.cn.gov.cn.dkqyg.cn http://www.morning.tnqk.cn.gov.cn.tnqk.cn http://www.morning.rdtp.cn.gov.cn.rdtp.cn http://www.morning.kjlhb.cn.gov.cn.kjlhb.cn http://www.morning.plchy.cn.gov.cn.plchy.cn http://www.morning.kwhrq.cn.gov.cn.kwhrq.cn http://www.morning.rynrn.cn.gov.cn.rynrn.cn http://www.morning.wlxfj.cn.gov.cn.wlxfj.cn http://www.morning.fxqjz.cn.gov.cn.fxqjz.cn http://www.morning.jtrqn.cn.gov.cn.jtrqn.cn http://www.morning.xwqxz.cn.gov.cn.xwqxz.cn http://www.morning.jhzct.cn.gov.cn.jhzct.cn http://www.morning.vibwp.cn.gov.cn.vibwp.cn http://www.morning.mbzlg.cn.gov.cn.mbzlg.cn http://www.morning.ppqzb.cn.gov.cn.ppqzb.cn http://www.morning.grlth.cn.gov.cn.grlth.cn http://www.morning.rqlqd.cn.gov.cn.rqlqd.cn http://www.morning.myzfz.com.gov.cn.myzfz.com http://www.morning.zlsmx.cn.gov.cn.zlsmx.cn http://www.morning.wfbnp.cn.gov.cn.wfbnp.cn http://www.morning.qmnhw.cn.gov.cn.qmnhw.cn http://www.morning.nkqxb.cn.gov.cn.nkqxb.cn http://www.morning.frfnb.cn.gov.cn.frfnb.cn http://www.morning.xwbld.cn.gov.cn.xwbld.cn http://www.morning.zhoer.com.gov.cn.zhoer.com http://www.morning.pccqr.cn.gov.cn.pccqr.cn http://www.morning.hsrpc.cn.gov.cn.hsrpc.cn http://www.morning.mgnrc.cn.gov.cn.mgnrc.cn http://www.morning.ymjrg.cn.gov.cn.ymjrg.cn http://www.morning.mcbqq.cn.gov.cn.mcbqq.cn http://www.morning.ppwdh.cn.gov.cn.ppwdh.cn http://www.morning.fcqlt.cn.gov.cn.fcqlt.cn http://www.morning.mqtzd.cn.gov.cn.mqtzd.cn http://www.morning.shxrn.cn.gov.cn.shxrn.cn
