cudnn_cnn_infer.h中定义的conv模式如下 typedef enum { CUDNN_CONVOLUTION = 0, CUDNN_CROSS_CORRELATION = 1 } cudnnConvolutionMode_t; 4、cudnnTransformNCHWtype 定义是否需要transform 5、设置各个执行参数 while(argc){...argc--;...} 6、transform格式转换 doTest cudnnHandle_t: 定义cudnn操作句柄 ...
CUDNN( Deep Neural Network library)是NVDIA的针对于神经网络场景的开发的高性能函数库,GPU开发人员无需与CUDA的底层API直接打交道,直接调用CUDNN提供的函数库即可实现神经网络中的一些高性能计算,其主要提供了如下计算 Convolution forward and backward, including cross-correlation Matrix multiplication Pooling forward...
cudnnTensorDescriptor_t bottom, cudnnFilterDescriptor_t filter,intpad_h,intpad_w,intstride_h,intstride_w){#ifCUDNN_VERSION_MIN(6, 0, 0)CUDNN_CHECK(cudnnSetConvolution2dDescriptor(*conv, pad_h, pad_w, stride_h, stride_w,1,1, CUDNN_CROSS_CORRELATION, dataType<Dtype>::type));#else...
CUDNN_ATTR_CONVOLUTION_MODE CUDNN_CROSS_CORRELATION CUDNN_ATTR_CONVOLUTION_COMP_TYPE For ConvolutionFwdCUDNN_DATA_HALF,CUDNN_DATA_INT32, andCUDNN_DATA_FLOAT For ConvolutionBwDataand ConvolutionBwFilter Only CUDNN_DATA_FLOAT CUDNN_ATTR_CONVOLUTION_SPATIAL_DIMS 2 or 3 CUDNN_ATTR_OPERATION_CONVOLUT...
Overview NVIDIA cuDNN provides highly tuned implementations of operations arising frequently in DNN applications: Convolution forward and backward, including cross-correlation Matrix multiplication Pooling forward and backward Softmax forward and backward...
pad_h,pad_w,stride_h,stride_w,1,1,CUDNN_CROSS_CORRELATION));^./include/caffe/util/cudnn.hpp:17:28:note:indefinitionofmacro ‘CUDNN_CHECK’ cudnnStatus_t status=condition;\^In file includedfrom./include/caffe/util/cudnn.hpp:5:0,from./include/caffe/util/device...
/*mode=*/CUDNN_CROSS_CORRELATION,// CUDNN_CONVOLUTION /*computeType=*/CUDNN_DATA_FLOAT)); // 计算卷积后图像的维数 intbatch_size{0},channels{0},height{0},width{0}; checkCUDNN(cudnnGetConvolution2dForwardOutputDim(convolution_descriptor, ...
/*mode=*/CUDNN_CROSS_CORRELATION, // CUDNN_CONVOLUTION /*computeType=*/CUDNN_DATA_FLOAT)); // 计算卷积后图像的维数 int batch_size{ 0 }, channels{ 0 }, height{ 0 }, width{ 0 }; checkCUDNN(cudnnGetConvolution2dForwardOutputDim(convolution_descriptor, ...
dataType<Dtype>::type)); #else CUDNN_CHECK(cudnnSetConvolution2dDescriptor(*conv, pad_h, pad_w, stride_h, stride_w, 1, 1, CUDNN_CROSS_CORRELATION)); #endif } 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14.
pad_h, pad_w, stride_h, stride_w, 1, 1, CUDNN_CROSS_CORRELATION)); ^ ./include/caffe/util/cudnn.hpp:12:28: note: in definition of macro ‘CUDNN_CHECK’ cudnnStatus_t status = condition; \ ^ ./include/caffe/util/cudnn.hpp:105:70: note: (if you use ‘-fpermissive’, G++...