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Merge pull request BVLC#5972 from icyblade/icyblade-patch-1
add support for cuDNN v7
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docs/installation.md

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@@ -42,14 +42,14 @@ Optional dependencies:
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* [OpenCV](http://opencv.org/) >= 2.4 including 3.0
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* IO libraries: `lmdb`, `leveldb` (note: leveldb requires `snappy`)
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* cuDNN for GPU acceleration (v6)
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* cuDNN for GPU acceleration (v7)
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Pycaffe and Matcaffe interfaces have their own natural needs.
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* For Python Caffe: `Python 2.7` or `Python 3.3+`, `numpy (>= 1.7)`, boost-provided `boost.python`
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* For MATLAB Caffe: MATLAB with the `mex` compiler.
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**cuDNN Caffe**: for fastest operation Caffe is accelerated by drop-in integration of [NVIDIA cuDNN](https://developer.nvidia.com/cudnn). To speed up your Caffe models, install cuDNN then uncomment the `USE_CUDNN := 1` flag in `Makefile.config` when installing Caffe. Acceleration is automatic. The current version is cuDNN v6; older versions are supported in older Caffe.
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**cuDNN Caffe**: for fastest operation Caffe is accelerated by drop-in integration of [NVIDIA cuDNN](https://developer.nvidia.com/cudnn). To speed up your Caffe models, install cuDNN then uncomment the `USE_CUDNN := 1` flag in `Makefile.config` when installing Caffe. Acceleration is automatic. The current version is cuDNN v7; older versions are supported in older Caffe.
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**CPU-only Caffe**: for cold-brewed CPU-only Caffe uncomment the `CPU_ONLY := 1` flag in `Makefile.config` to configure and build Caffe without CUDA. This is helpful for cloud or cluster deployment.
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include/caffe/util/cudnn.hpp

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@@ -44,6 +44,12 @@ inline const char* cudnnGetErrorString(cudnnStatus_t status) {
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#if CUDNN_VERSION_MIN(6, 0, 0)
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case CUDNN_STATUS_RUNTIME_PREREQUISITE_MISSING:
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return "CUDNN_STATUS_RUNTIME_PREREQUISITE_MISSING";
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#endif
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#if CUDNN_VERSION_MIN(7, 0, 0)
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case CUDNN_STATUS_RUNTIME_IN_PROGRESS:
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return "CUDNN_STATUS_RUNTIME_IN_PROGRESS";
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case CUDNN_STATUS_RUNTIME_FP_OVERFLOW:
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return "CUDNN_STATUS_RUNTIME_FP_OVERFLOW";
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#endif
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}
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return "Unknown cudnn status";

scripts/travis/install-deps.sh

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@@ -106,7 +106,7 @@ if $WITH_CUDA ; then
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ln -s /usr/local/cuda-$CUDA_VERSION /usr/local/cuda
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if $WITH_CUDNN ; then
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apt-get install -y --no-install-recommends libcudnn6-dev
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apt-get install -y --no-install-recommends libcudnn7-dev
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fi
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fi
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