cuDNN v5.1 (Jan 20, 2017), for CUDA 8.0

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These Licensed Deliverables are a * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT * 1995), consisting of "commercial computer software" and "commercial * computer software documentation" as such terms are used in 48 * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government * only as a commercial end item. Consistent with 48 C.F.R.12.212 and * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all * U.S. Government End Users acquire the Licensed Deliverables with * only those rights set forth herein. * * Any use of the Licensed Deliverables in individual and commercial * software must include, in the user documentation and internal * comments to the code, the above Disclaimer and U.S. Government End * Users Notice. */ /* cudnn : Neural Networks Library */ #if !defined(CUDNN_H_) #define CUDNN_H_ #define CUDNN_MAJOR 5 #define CUDNN_MINOR 1 #define CUDNN_PATCHLEVEL 10 #define CUDNN_VERSION (CUDNN_MAJOR * 1000 + CUDNN_MINOR * 100 + CUDNN_PATCHLEVEL) #include "driver_types.h" #include <cuda_runtime.h> #ifndef CUDNNWINAPI #ifdef _WIN32 #define CUDNNWINAPI __stdcall #else #define CUDNNWINAPI #endif #endif #if defined (__cplusplus) extern "C" { #endif struct cudnnContext; typedef struct cudnnContext *cudnnHandle_t; size_t CUDNNWINAPI cudnnGetVersion(void); /* * CUDNN return codes */ typedef enum { CUDNN_STATUS_SUCCESS = 0, CUDNN_STATUS_NOT_INITIALIZED = 1, CUDNN_STATUS_ALLOC_FAILED = 2, CUDNN_STATUS_BAD_PARAM = 3, CUDNN_STATUS_INTERNAL_ERROR = 4, CUDNN_STATUS_INVALID_VALUE = 5, CUDNN_STATUS_ARCH_MISMATCH = 6, CUDNN_STATUS_MAPPING_ERROR = 7, CUDNN_STATUS_EXECUTION_FAILED = 8, CUDNN_STATUS_NOT_SUPPORTED = 9, CUDNN_STATUS_LICENSE_ERROR = 10 } cudnnStatus_t; // human-readable error messages const char * CUDNNWINAPI cudnnGetErrorString(cudnnStatus_t status); cudnnStatus_t CUDNNWINAPI cudnnCreate (cudnnHandle_t *handle); cudnnStatus_t CUDNNWINAPI cudnnDestroy (cudnnHandle_t handle); cudnnStatus_t CUDNNWINAPI cudnnSetStream (cudnnHandle_t handle, cudaStream_t streamId); cudnnStatus_t CUDNNWINAPI cudnnGetStream (cudnnHandle_t handle, cudaStream_t *streamId); /* Data structures to represent Image/Filter and the Neural Network Layer */ typedef struct cudnnTensorStruct* cudnnTensorDescriptor_t; typedef struct cudnnConvolutionStruct* cudnnConvolutionDescriptor_t; typedef struct cudnnPoolingStruct* cudnnPoolingDescriptor_t; typedef struct cudnnFilterStruct* cudnnFilterDescriptor_t; typedef struct cudnnLRNStruct* cudnnLRNDescriptor_t; typedef struct cudnnActivationStruct* cudnnActivationDescriptor_t; typedef struct cudnnSpatialTransformerStruct* cudnnSpatialTransformerDescriptor_t; typedef struct cudnnOpTensorStruct* cudnnOpTensorDescriptor_t; /* * CUDNN data type */ typedef enum { CUDNN_DATA_FLOAT = 0, CUDNN_DATA_DOUBLE = 1, CUDNN_DATA_HALF = 2, } cudnnDataType_t; /* * CUDNN propagate Nan */ typedef enum{ CUDNN_NOT_PROPAGATE_NAN = 0, CUDNN_PROPAGATE_NAN = 1, } cudnnNanPropagation_t; /* Maximum supported number of tensor dimensions */ #define CUDNN_DIM_MAX 8 /* Create an instance of a generic Tensor descriptor */ cudnnStatus_t CUDNNWINAPI cudnnCreateTensorDescriptor( cudnnTensorDescriptor_t *tensorDesc ); typedef enum { CUDNN_TENSOR_NCHW = 0, /* row major (wStride = 1, hStride = w) */ CUDNN_TENSOR_NHWC = 1 /* feature maps interleaved ( cStride = 1 )*/ } cudnnTensorFormat_t; cudnnStatus_t CUDNNWINAPI cudnnSetTensor4dDescriptor( cudnnTensorDescriptor_t tensorDesc, cudnnTensorFormat_t format, cudnnDataType_t dataType, // image data type int n, // number of inputs (batch size) int c, // number of input feature maps int h, // height of input section int w ); // width of input section cudnnStatus_t CUDNNWINAPI cudnnSetTensor4dDescriptorEx( cudnnTensorDescriptor_t tensorDesc, cudnnDataType_t dataType, // image data type int n, // number of inputs (batch size) int c, // number of input feature maps int h, // height of input section int w, // width of input section int nStride, int cStride, int hStride, int wStride ); cudnnStatus_t CUDNNWINAPI cudnnGetTensor4dDescriptor( const cudnnTensorDescriptor_t tensorDesc, cudnnDataType_t *dataType, // image data type int *n, // number of inputs (batch size) int *c, // number of input feature maps int *h, // height of input section int *w, // width of input section int *nStride, int *cStride, int *hStride,