深度学习python安装包

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  • 2022-03-01 20:32
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用于深度学习的python完整安装包 包括python3.5.3 cudnn5.1 下载该资源的朋友额外还需要下载cuda_8.0.44_win10 由于这个文件很大所以没有放进来。这里面的cudnn5.1是量身为cuda8.0准备的
python3.5.3 cudnn5.1.rar
内容介绍
/* * Copyright 1993-2015 NVIDIA Corporation. All rights reserved. * * NOTICE TO LICENSEE: * * This source code and/or documentation ("Licensed Deliverables") are * subject to NVIDIA intellectual property rights under U.S. and * international Copyright laws. * * These Licensed Deliverables contained herein is PROPRIETARY and * CONFIDENTIAL to NVIDIA and is being provided under the terms and * conditions of a form of NVIDIA software license agreement by and * between NVIDIA and Licensee ("License Agreement") or electronically * accepted by Licensee. Notwithstanding any terms or conditions to * the contrary in the License Agreement, reproduction or disclosure * of the Licensed Deliverables to any third party without the express * written consent of NVIDIA is prohibited. * * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. IT IS * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND. * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY, * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE. * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE * OF THESE LICENSED DELIVERABLES. * * U.S. Government End Users. 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,
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