541 lines
27 KiB
C
541 lines
27 KiB
C
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/*
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* Copyright 1993-2020 NVIDIA Corporation. All rights reserved.
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*
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* NOTICE TO LICENSEE:
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*
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* This source code and/or documentation ("Licensed Deliverables") are
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* subject to NVIDIA intellectual property rights under U.S. and
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* international Copyright laws.
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*
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* These Licensed Deliverables contained herein is PROPRIETARY and
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* CONFIDENTIAL to NVIDIA and is being provided under the terms and
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* conditions of a form of NVIDIA software license agreement by and
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* between NVIDIA and Licensee ("License Agreement") or electronically
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* accepted by Licensee. Notwithstanding any terms or conditions to
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* the contrary in the License Agreement, reproduction or disclosure
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* of the Licensed Deliverables to any third party without the express
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* written consent of NVIDIA is prohibited.
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*
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* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
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* LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
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* SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. IT IS
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* PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
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* NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
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* DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
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* NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
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* NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
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* LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
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* SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
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* DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
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* WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
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* ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
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* OF THESE LICENSED DELIVERABLES.
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*
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* U.S. Government End Users. These Licensed Deliverables are a
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* "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
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* 1995), consisting of "commercial computer software" and "commercial
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* computer software documentation" as such terms are used in 48
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* C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
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* only as a commercial end item. Consistent with 48 C.F.R.12.212 and
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* 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
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* U.S. Government End Users acquire the Licensed Deliverables with
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* only those rights set forth herein.
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*
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* Any use of the Licensed Deliverables in individual and commercial
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* software must include, in the user documentation and internal
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* comments to the code, the above Disclaimer and U.S. Government End
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* Users Notice.
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*/
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/* cudnn_adv_train : cuDNN's advanced and experimental features.
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*/
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#if !defined(CUDNN_ADV_TRAIN_H_)
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#define CUDNN_ADV_TRAIN_H_
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#include <cuda_runtime.h>
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#include <stdint.h>
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#include "cudnn_version.h"
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#include "cudnn_ops_infer.h"
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#include "cudnn_ops_train.h"
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#include "cudnn_adv_infer.h"
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/* These version numbers are autogenerated, do not edit manually. */
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#define CUDNN_ADV_TRAIN_MAJOR 8
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#define CUDNN_ADV_TRAIN_MINOR 1
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#define CUDNN_ADV_TRAIN_PATCH 0
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#if (CUDNN_ADV_TRAIN_MAJOR != CUDNN_MAJOR) || (CUDNN_ADV_TRAIN_MINOR != CUDNN_MINOR) || \
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(CUDNN_ADV_TRAIN_PATCH != CUDNN_PATCHLEVEL)
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#error Version mismatch in cuDNN ADV TRAIN!!!
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#endif
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#if defined(__cplusplus)
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extern "C" {
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#endif
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typedef enum {
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CUDNN_WGRAD_MODE_ADD = 0, /* add partial gradients to wgrad output buffers */
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CUDNN_WGRAD_MODE_SET = 1, /* write partial gradients to wgrad output buffers */
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} cudnnWgradMode_t;
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CUDNN_DEPRECATED cudnnStatus_t CUDNNWINAPI
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cudnnRNNForwardTraining(cudnnHandle_t handle,
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const cudnnRNNDescriptor_t rnnDesc,
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const int seqLength,
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const cudnnTensorDescriptor_t *xDesc,
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const void *x,
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const cudnnTensorDescriptor_t hxDesc,
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const void *hx,
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const cudnnTensorDescriptor_t cxDesc,
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const void *cx,
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const cudnnFilterDescriptor_t wDesc,
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const void *w,
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const cudnnTensorDescriptor_t *yDesc,
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void *y,
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const cudnnTensorDescriptor_t hyDesc,
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void *hy,
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const cudnnTensorDescriptor_t cyDesc,
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void *cy,
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void *workSpace,
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size_t workSpaceSizeInBytes,
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void *reserveSpace,
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size_t reserveSpaceSizeInBytes);
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CUDNN_DEPRECATED cudnnStatus_t CUDNNWINAPI
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cudnnRNNBackwardData(cudnnHandle_t handle,
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const cudnnRNNDescriptor_t rnnDesc,
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const int seqLength,
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const cudnnTensorDescriptor_t *yDesc,
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const void *y,
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const cudnnTensorDescriptor_t *dyDesc,
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const void *dy,
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const cudnnTensorDescriptor_t dhyDesc,
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const void *dhy,
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const cudnnTensorDescriptor_t dcyDesc,
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const void *dcy,
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const cudnnFilterDescriptor_t wDesc,
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const void *w,
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const cudnnTensorDescriptor_t hxDesc,
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const void *hx,
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const cudnnTensorDescriptor_t cxDesc,
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const void *cx,
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const cudnnTensorDescriptor_t *dxDesc,
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void *dx,
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const cudnnTensorDescriptor_t dhxDesc,
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void *dhx,
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const cudnnTensorDescriptor_t dcxDesc,
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void *dcx,
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void *workSpace,
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size_t workSpaceSizeInBytes,
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void *reserveSpace,
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size_t reserveSpaceSizeInBytes);
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cudnnStatus_t CUDNNWINAPI
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cudnnRNNBackwardData_v8(cudnnHandle_t handle,
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cudnnRNNDescriptor_t rnnDesc,
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const int32_t devSeqLengths[],
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cudnnRNNDataDescriptor_t yDesc,
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const void *y,
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const void *dy,
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cudnnRNNDataDescriptor_t xDesc,
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void *dx,
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cudnnTensorDescriptor_t hDesc,
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const void *hx,
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const void *dhy,
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void *dhx,
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cudnnTensorDescriptor_t cDesc,
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const void *cx,
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const void *dcy,
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void *dcx,
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size_t weightSpaceSize,
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const void *weightSpace,
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size_t workSpaceSize,
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void *workSpace,
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size_t reserveSpaceSize,
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void *reserveSpace);
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CUDNN_DEPRECATED cudnnStatus_t CUDNNWINAPI
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cudnnRNNBackwardWeights(cudnnHandle_t handle,
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const cudnnRNNDescriptor_t rnnDesc,
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const int seqLength,
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const cudnnTensorDescriptor_t *xDesc,
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const void *x,
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const cudnnTensorDescriptor_t hxDesc,
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const void *hx,
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const cudnnTensorDescriptor_t *yDesc,
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const void *y,
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const void *workSpace,
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size_t workSpaceSizeInBytes,
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const cudnnFilterDescriptor_t dwDesc,
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void *dw,
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const void *reserveSpace,
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size_t reserveSpaceSizeInBytes);
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cudnnStatus_t CUDNNWINAPI
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cudnnRNNBackwardWeights_v8(cudnnHandle_t handle,
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cudnnRNNDescriptor_t rnnDesc,
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cudnnWgradMode_t addGrad,
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const int32_t devSeqLengths[],
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cudnnRNNDataDescriptor_t xDesc,
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const void *x,
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cudnnTensorDescriptor_t hDesc,
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const void *hx,
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cudnnRNNDataDescriptor_t yDesc,
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const void *y,
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size_t weightSpaceSize,
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void *dweightSpace,
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size_t workSpaceSize,
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void *workSpace,
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size_t reserveSpaceSize,
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void *reserveSpace);
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/* RNN EX API */
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CUDNN_DEPRECATED cudnnStatus_t CUDNNWINAPI
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cudnnRNNForwardTrainingEx(cudnnHandle_t handle,
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const cudnnRNNDescriptor_t rnnDesc,
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const cudnnRNNDataDescriptor_t xDesc,
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const void *x,
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const cudnnTensorDescriptor_t hxDesc,
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const void *hx,
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const cudnnTensorDescriptor_t cxDesc,
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const void *cx,
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const cudnnFilterDescriptor_t wDesc,
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const void *w,
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const cudnnRNNDataDescriptor_t yDesc,
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void *y,
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const cudnnTensorDescriptor_t hyDesc,
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void *hy,
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const cudnnTensorDescriptor_t cyDesc,
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void *cy,
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const cudnnRNNDataDescriptor_t kDesc, /* reserved, should pass NULL */
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const void *keys, /* reserved, should pass NULL */
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const cudnnRNNDataDescriptor_t cDesc, /* reserved, should pass NULL */
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void *cAttn, /* reserved, should pass NULL */
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const cudnnRNNDataDescriptor_t iDesc, /* reserved, should pass NULL */
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void *iAttn, /* reserved, should pass NULL */
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const cudnnRNNDataDescriptor_t qDesc, /* reserved, should pass NULL */
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void *queries, /* reserved, should pass NULL */
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void *workSpace,
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size_t workSpaceSizeInBytes,
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void *reserveSpace,
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size_t reserveSpaceSizeInBytes);
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CUDNN_DEPRECATED cudnnStatus_t CUDNNWINAPI
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cudnnRNNBackwardDataEx(cudnnHandle_t handle,
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const cudnnRNNDescriptor_t rnnDesc,
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const cudnnRNNDataDescriptor_t yDesc,
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const void *y,
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const cudnnRNNDataDescriptor_t dyDesc,
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const void *dy,
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const cudnnRNNDataDescriptor_t dcDesc, /* reserved, should pass NULL */
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const void *dcAttn, /* reserved, should pass NULL */
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const cudnnTensorDescriptor_t dhyDesc,
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const void *dhy,
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const cudnnTensorDescriptor_t dcyDesc,
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const void *dcy,
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const cudnnFilterDescriptor_t wDesc,
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const void *w,
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const cudnnTensorDescriptor_t hxDesc,
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const void *hx,
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const cudnnTensorDescriptor_t cxDesc,
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const void *cx,
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const cudnnRNNDataDescriptor_t dxDesc,
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void *dx,
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const cudnnTensorDescriptor_t dhxDesc,
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void *dhx,
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const cudnnTensorDescriptor_t dcxDesc,
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void *dcx,
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const cudnnRNNDataDescriptor_t dkDesc, /* reserved, should pass NULL */
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void *dkeys, /* reserved, should pass NULL */
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void *workSpace,
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size_t workSpaceSizeInBytes,
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void *reserveSpace,
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size_t reserveSpaceSizeInBytes);
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CUDNN_DEPRECATED cudnnStatus_t CUDNNWINAPI
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cudnnRNNBackwardWeightsEx(cudnnHandle_t handle,
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const cudnnRNNDescriptor_t rnnDesc,
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const cudnnRNNDataDescriptor_t xDesc,
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const void *x,
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const cudnnTensorDescriptor_t hxDesc,
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const void *hx,
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const cudnnRNNDataDescriptor_t yDesc,
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const void *y,
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void *workSpace,
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size_t workSpaceSizeInBytes,
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const cudnnFilterDescriptor_t dwDesc,
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void *dw,
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void *reserveSpace,
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size_t reserveSpaceSizeInBytes);
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/* RNN FIND API */
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CUDNN_DEPRECATED cudnnStatus_t CUDNNWINAPI
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cudnnGetRNNForwardTrainingAlgorithmMaxCount(cudnnHandle_t handle, const cudnnRNNDescriptor_t rnnDesc, int *count);
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CUDNN_DEPRECATED cudnnStatus_t CUDNNWINAPI
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cudnnFindRNNForwardTrainingAlgorithmEx(cudnnHandle_t handle,
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const cudnnRNNDescriptor_t rnnDesc,
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const int seqLength,
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const cudnnTensorDescriptor_t *xDesc,
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const void *x,
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const cudnnTensorDescriptor_t hxDesc,
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const void *hx,
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const cudnnTensorDescriptor_t cxDesc,
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const void *cx,
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const cudnnFilterDescriptor_t wDesc,
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const void *w,
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const cudnnTensorDescriptor_t *yDesc,
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void *y,
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const cudnnTensorDescriptor_t hyDesc,
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void *hy,
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const cudnnTensorDescriptor_t cyDesc,
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void *cy,
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const float findIntensity,
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const int requestedAlgoCount,
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int *returnedAlgoCount,
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cudnnAlgorithmPerformance_t *perfResults,
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void *workspace,
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size_t workSpaceSizeInBytes,
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void *reserveSpace,
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size_t reserveSpaceSizeInBytes);
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|
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CUDNN_DEPRECATED cudnnStatus_t CUDNNWINAPI
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cudnnGetRNNBackwardDataAlgorithmMaxCount(cudnnHandle_t handle, const cudnnRNNDescriptor_t rnnDesc, int *count);
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CUDNN_DEPRECATED cudnnStatus_t CUDNNWINAPI
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cudnnFindRNNBackwardDataAlgorithmEx(cudnnHandle_t handle,
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const cudnnRNNDescriptor_t rnnDesc,
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const int seqLength,
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const cudnnTensorDescriptor_t *yDesc,
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const void *y,
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const cudnnTensorDescriptor_t *dyDesc,
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const void *dy,
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const cudnnTensorDescriptor_t dhyDesc,
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const void *dhy,
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const cudnnTensorDescriptor_t dcyDesc,
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const void *dcy,
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const cudnnFilterDescriptor_t wDesc,
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const void *w,
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const cudnnTensorDescriptor_t hxDesc,
|
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|
const void *hx,
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|
const cudnnTensorDescriptor_t cxDesc,
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|
const void *cx,
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|
const cudnnTensorDescriptor_t *dxDesc,
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|
void *dx,
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const cudnnTensorDescriptor_t dhxDesc,
|
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|
void *dhx,
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const cudnnTensorDescriptor_t dcxDesc,
|
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|
void *dcx,
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|
const float findIntensity,
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|
const int requestedAlgoCount,
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int *returnedAlgoCount,
|
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|
cudnnAlgorithmPerformance_t *perfResults,
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|
void *workspace,
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|
size_t workSpaceSizeInBytes,
|
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|
void *reserveSpace,
|
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|
size_t reserveSpaceSizeInBytes);
|
||
|
|
||
|
CUDNN_DEPRECATED cudnnStatus_t CUDNNWINAPI
|
||
|
cudnnGetRNNBackwardWeightsAlgorithmMaxCount(cudnnHandle_t handle, const cudnnRNNDescriptor_t rnnDesc, int *count);
|
||
|
|
||
|
CUDNN_DEPRECATED cudnnStatus_t CUDNNWINAPI
|
||
|
cudnnFindRNNBackwardWeightsAlgorithmEx(cudnnHandle_t handle,
|
||
|
const cudnnRNNDescriptor_t rnnDesc,
|
||
|
const int seqLength,
|
||
|
const cudnnTensorDescriptor_t *xDesc,
|
||
|
const void *x,
|
||
|
const cudnnTensorDescriptor_t hxDesc,
|
||
|
const void *hx,
|
||
|
const cudnnTensorDescriptor_t *yDesc,
|
||
|
const void *y,
|
||
|
const float findIntensity,
|
||
|
const int requestedAlgoCount,
|
||
|
int *returnedAlgoCount,
|
||
|
cudnnAlgorithmPerformance_t *perfResults,
|
||
|
const void *workspace,
|
||
|
size_t workSpaceSizeInBytes,
|
||
|
const cudnnFilterDescriptor_t dwDesc,
|
||
|
void *dw,
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||
|
const void *reserveSpace,
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||
|
size_t reserveSpaceSizeInBytes);
|
||
|
|
||
|
cudnnStatus_t CUDNNWINAPI
|
||
|
cudnnMultiHeadAttnBackwardData(cudnnHandle_t handle,
|
||
|
const cudnnAttnDescriptor_t attnDesc,
|
||
|
const int loWinIdx[],
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const int hiWinIdx[],
|
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|
const int devSeqLengthsDQDO[],
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||
|
const int devSeqLengthsDKDV[],
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||
|
const cudnnSeqDataDescriptor_t doDesc,
|
||
|
const void *dout,
|
||
|
const cudnnSeqDataDescriptor_t dqDesc,
|
||
|
void *dqueries,
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||
|
const void *queries,
|
||
|
const cudnnSeqDataDescriptor_t dkDesc,
|
||
|
void *dkeys,
|
||
|
const void *keys,
|
||
|
const cudnnSeqDataDescriptor_t dvDesc,
|
||
|
void *dvalues,
|
||
|
const void *values,
|
||
|
size_t weightSizeInBytes,
|
||
|
const void *weights,
|
||
|
size_t workSpaceSizeInBytes,
|
||
|
void *workSpace,
|
||
|
size_t reserveSpaceSizeInBytes,
|
||
|
void *reserveSpace);
|
||
|
|
||
|
cudnnStatus_t CUDNNWINAPI
|
||
|
cudnnMultiHeadAttnBackwardWeights(cudnnHandle_t handle,
|
||
|
const cudnnAttnDescriptor_t attnDesc,
|
||
|
cudnnWgradMode_t addGrad,
|
||
|
const cudnnSeqDataDescriptor_t qDesc,
|
||
|
const void *queries,
|
||
|
const cudnnSeqDataDescriptor_t kDesc,
|
||
|
const void *keys,
|
||
|
const cudnnSeqDataDescriptor_t vDesc,
|
||
|
const void *values,
|
||
|
const cudnnSeqDataDescriptor_t doDesc,
|
||
|
const void *dout,
|
||
|
size_t weightSizeInBytes,
|
||
|
const void *weights,
|
||
|
void *dweights,
|
||
|
size_t workSpaceSizeInBytes,
|
||
|
void *workSpace,
|
||
|
size_t reserveSpaceSizeInBytes,
|
||
|
void *reserveSpace);
|
||
|
|
||
|
/*
|
||
|
* CTC (Connectionist Temporal Classification) loss descriptor create/destory/set/get functions
|
||
|
*/
|
||
|
/* Input normalization mode for loss function */
|
||
|
typedef enum {
|
||
|
CUDNN_LOSS_NORMALIZATION_NONE = 0,
|
||
|
CUDNN_LOSS_NORMALIZATION_SOFTMAX = 1,
|
||
|
} cudnnLossNormalizationMode_t;
|
||
|
|
||
|
cudnnStatus_t CUDNNWINAPI
|
||
|
cudnnCreateCTCLossDescriptor(cudnnCTCLossDescriptor_t *ctcLossDesc);
|
||
|
|
||
|
cudnnStatus_t CUDNNWINAPI
|
||
|
cudnnSetCTCLossDescriptor(cudnnCTCLossDescriptor_t ctcLossDesc, cudnnDataType_t compType);
|
||
|
|
||
|
cudnnStatus_t CUDNNWINAPI
|
||
|
cudnnSetCTCLossDescriptorEx(cudnnCTCLossDescriptor_t ctcLossDesc,
|
||
|
cudnnDataType_t compType,
|
||
|
cudnnLossNormalizationMode_t normMode,
|
||
|
cudnnNanPropagation_t gradMode);
|
||
|
|
||
|
cudnnStatus_t CUDNNWINAPI
|
||
|
cudnnSetCTCLossDescriptor_v8(cudnnCTCLossDescriptor_t ctcLossDesc,
|
||
|
cudnnDataType_t compType,
|
||
|
cudnnLossNormalizationMode_t normMode,
|
||
|
cudnnNanPropagation_t gradMode,
|
||
|
int maxLabelLength);
|
||
|
|
||
|
cudnnStatus_t CUDNNWINAPI
|
||
|
cudnnGetCTCLossDescriptor(cudnnCTCLossDescriptor_t ctcLossDesc, cudnnDataType_t *compType);
|
||
|
|
||
|
cudnnStatus_t CUDNNWINAPI
|
||
|
cudnnGetCTCLossDescriptorEx(cudnnCTCLossDescriptor_t ctcLossDesc,
|
||
|
cudnnDataType_t *compType,
|
||
|
cudnnLossNormalizationMode_t *normMode,
|
||
|
cudnnNanPropagation_t *gradMode);
|
||
|
|
||
|
cudnnStatus_t CUDNNWINAPI
|
||
|
cudnnGetCTCLossDescriptor_v8(cudnnCTCLossDescriptor_t ctcLossDesc,
|
||
|
cudnnDataType_t *compType,
|
||
|
cudnnLossNormalizationMode_t *normMode,
|
||
|
cudnnNanPropagation_t *gradMode,
|
||
|
int *maxLabelLength);
|
||
|
|
||
|
cudnnStatus_t CUDNNWINAPI
|
||
|
cudnnDestroyCTCLossDescriptor(cudnnCTCLossDescriptor_t ctcLossDesc);
|
||
|
|
||
|
/* return the ctc costs and gradients, given the probabilities and labels */
|
||
|
cudnnStatus_t CUDNNWINAPI
|
||
|
cudnnCTCLoss(
|
||
|
cudnnHandle_t handle,
|
||
|
const cudnnTensorDescriptor_t
|
||
|
probsDesc, /* Tensor descriptor for probabilities, the dimensions are T,N,A (T is the timing steps, N is the
|
||
|
mini batch size, A is the alphabet size) */
|
||
|
const void *probs, /* probabilities after softmax, in GPU memory */
|
||
|
const int hostLabels[], /* labels, in CPU memory */
|
||
|
const int hostLabelLengths[], /* the length of each label, in CPU memory */
|
||
|
const int hostInputLengths[], /* the lengths of timing steps in each batch, in CPU memory */
|
||
|
void *costs, /* the returned costs of CTC, in GPU memory */
|
||
|
const cudnnTensorDescriptor_t gradientsDesc, /* Tensor descriptor for gradients, the dimensions are T,N,A */
|
||
|
void *gradients, /* the returned CTC gradients, in GPU memory, to compute costs only, set it to NULL */
|
||
|
cudnnCTCLossAlgo_t algo, /* algorithm selected, supported now 0 and 1 */
|
||
|
cudnnCTCLossDescriptor_t ctcLossDesc,
|
||
|
void *workspace, /* pointer to the workspace, in GPU memory */
|
||
|
size_t workSpaceSizeInBytes); /* size of the workspace */
|
||
|
|
||
|
/* return the ctc costs and gradients, given the probabilities and labels */
|
||
|
cudnnStatus_t CUDNNWINAPI
|
||
|
cudnnCTCLoss_v8(
|
||
|
cudnnHandle_t handle,
|
||
|
cudnnCTCLossAlgo_t algo, /* algorithm selected, supported now 0 and 1 */
|
||
|
cudnnCTCLossDescriptor_t ctcLossDesc,
|
||
|
const cudnnTensorDescriptor_t
|
||
|
probsDesc, /* Tensor descriptor for probabilities, the dimensions are T,N,A (T is the timing steps, N is the
|
||
|
mini batch size, A is the alphabet size) */
|
||
|
const void *probs, /* probabilities after softmax, in GPU memory */
|
||
|
const int labels[], /* labels, in GPU memory */
|
||
|
const int labelLengths[], /* the length of each label, in GPU memory */
|
||
|
const int inputLengths[], /* the lengths of timing steps in each batch, in GPU memory */
|
||
|
void *costs, /* the returned costs of CTC, in GPU memory */
|
||
|
const cudnnTensorDescriptor_t gradientsDesc, /* Tensor descriptor for gradients, the dimensions are T,N,A */
|
||
|
void *gradients, /* the returned CTC gradients, in GPU memory, to compute costs only, set it to NULL */
|
||
|
size_t workSpaceSizeInBytes, /* size of the workspace */
|
||
|
void *workspace); /* pointer to the workspace, in GPU memory */
|
||
|
|
||
|
/* return the workspace size needed for ctc */
|
||
|
cudnnStatus_t CUDNNWINAPI
|
||
|
cudnnGetCTCLossWorkspaceSize(
|
||
|
cudnnHandle_t handle,
|
||
|
const cudnnTensorDescriptor_t probsDesc, /* Tensor descriptor for probabilities, the dimensions are T,N,A (T is the
|
||
|
timing steps, N is the mini batch size, A is the alphabet size) */
|
||
|
const cudnnTensorDescriptor_t gradientsDesc, /* Tensor descriptor for gradients, the
|
||
|
dimensions are T,N,A. To compute costs
|
||
|
only, set it to NULL */
|
||
|
const int *labels, /* labels, in CPU memory */
|
||
|
const int *labelLengths, /* the length of each label, in CPU memory */
|
||
|
const int *inputLengths, /* the lengths of timing steps in each batch, in CPU memory */
|
||
|
cudnnCTCLossAlgo_t algo, /* algorithm selected, supported now 0 and 1 */
|
||
|
cudnnCTCLossDescriptor_t ctcLossDesc,
|
||
|
size_t *sizeInBytes); /* pointer to the returned workspace size */
|
||
|
|
||
|
/* return the workspace size needed for ctc */
|
||
|
cudnnStatus_t CUDNNWINAPI
|
||
|
cudnnGetCTCLossWorkspaceSize_v8(
|
||
|
cudnnHandle_t handle,
|
||
|
cudnnCTCLossAlgo_t algo, /* algorithm selected, supported now 0 and 1 */
|
||
|
cudnnCTCLossDescriptor_t ctcLossDesc,
|
||
|
const cudnnTensorDescriptor_t probsDesc, /* Tensor descriptor for probabilities, the dimensions are T,N,A (T is the
|
||
|
timing steps, N is the mini batch size, A is the alphabet size) */
|
||
|
const cudnnTensorDescriptor_t gradientsDesc, /* Tensor descriptor for gradients, the
|
||
|
dimensions are T,N,A. To compute costs
|
||
|
only, set it to NULL */
|
||
|
size_t *sizeInBytes); /* pointer to the returned workspace size */
|
||
|
|
||
|
/*
|
||
|
* \brief Cross-library version checker.
|
||
|
* This function is implemented differently in each sub-library. Each sublib
|
||
|
* checks whether its own version matches that of its dependencies.
|
||
|
* \returns CUDNN_STATUS_SUCCESS if the version check passes,
|
||
|
* CUDNN_STATUS_VERSION_MISMATCH if the versions are inconsistent.
|
||
|
*/
|
||
|
cudnnStatus_t CUDNNWINAPI
|
||
|
cudnnAdvTrainVersionCheck(void);
|
||
|
|
||
|
#if defined(__cplusplus)
|
||
|
}
|
||
|
#endif
|
||
|
|
||
|
#endif /* CUDNN_ADV_TRAIN_H_ */
|