CuSPARSE support · Issue #5193 · tensorflow/tensorflow
For some machine learning /algorithm problems, we require to multiply matrices with vectors. In some cases - especially those associated with large graph analytics, the matrices are sparse. Given the major limitation with GPUs is the limited GPU memory, representing the matrix in sparse format is vital. To this end, the CUSPARSE libraries (http://docs.nvidia.com/cuda/cusparse/) provide a suitable
examples/distributed.md at master · tensorflow/examples · GitHub
Distributed TensorFlow This document shows how to create a cluster of TensorFlow servers, and how to distribute a computation graph across that cluster. We assume that you are familiar with the basic concepts of writing low level TensorFlow programs. Hello distributed TensorFlow! To see a simple TensorFlow cluster in action, execute the following: # Start a TensorFlow server as a single-process "c
[Windows] Tensorflow GPU fails to find CUDA. · Issue #5968 · tensorflow/tensorflow
NOTE: Only file GitHub issues for bugs and feature requests. All other topics will be closed. For bugs or installation issues, please provide the following information. The more information you provide, the more easily we will be able to offer help and advice. What related GitHub issues or StackOverflow threads have you found by searching the web for your problem? NONE (Tensorflow for Windows is v
![[Windows] Tensorflow GPU fails to find CUDA. · Issue #5968 · tensorflow/tensorflow](https://cdn-ak-scissors.b.st-hatena.com/image/square/7bf597e6823c009c9ab8fd03d75b520ef591cc6f/height=288;version=1;width=512/https%3A%2F%2Fopengraph.githubassets.com%2F6037a1b876413fa86a6204993ac9ac87a5560c81f66b5fb555e5f7048c7e0422%2Ftensorflow%2Ftensorflow%2Fissues%2F5968)
tensorflow/README.md at master · tensorflow/tensorflow · GitHub
Dismiss Join GitHub today GitHub is home to over 36 million developers working together to host and review code, manage projects, and build software together. Sign up TensorFlow CMake build CMAKE build is deprecated for TensorFlow. Please use bazel to build TF for all platforms. For details, see the TensorFlow install guide. This directory contains CMake files for building TensorFlow on Microsoft
tensorflow/tensorflow/tools/docker at master · tensorflow/tensorflow · GitHub
WARNING: THESE IMAGES ARE DEPRECATED. TensorFlow's Dockerfiles are now located in tensorflow/tools/dockerfiles/. However, these Dockerfiles are still used to build TensorFlow's official Docker images while the internal infrastructure for the newer Dockerfiles is being developed. This directory will eventually be removed. Using TensorFlow via Docker This directory contains Dockerfiles to make it ea
GitHub - tensorflow/haskell: Haskell bindings for TensorFlow
import Control.Monad (replicateM, replicateM_) import System.Random (randomIO) import Test.HUnit (assertBool) import qualified TensorFlow.Core as TF import qualified TensorFlow.GenOps.Core as TF import qualified TensorFlow.Minimize as TF import qualified TensorFlow.Ops as TF hiding (initializedVariable) import qualified TensorFlow.Variable as TF main :: IO () main = do -- Generate data where `y =
models/slim at master · tensorflow/models · GitHub
README.md TensorFlow-Slim image classification library TF-slim is a new lightweight high-level API of TensorFlow ( tensorflow.contrib.slim ) for defining, training and evaluating complex models. This directory contains code for training and evaluating several widely used Convolutional Neural Network (CNN) image classification models using TF-slim. It contains scripts that will allow you to train m
tensorflow/tensorflow/contrib/makefile at master · tensorflow/tensorflow · GitHub
TensorFlow Makefile The recommended way to build TensorFlow from source is using the Bazel open-source build system. Sometimes this isn't possible. For example, if you are building for iOS, you currently need to use the Makefile. The build system may not have the RAM or processing power to support Bazel. Bazel or its dependencies may not be available. You may want to cross-compile for an unsupport
tensorflow/tensorflow/contrib/makefile at v0.10.0 · tensorflow/tensorflow
The recommended way to build TensorFlow from source is using the Bazel open-source build system. Sometimes this isn't possible. The build system may not have the RAM or processing power to support Bazel. Bazel or its dependencies may not be available. You may want to cross-compile for an unsupported target system. This experimental project supplies a Makefile automatically derived from the depende
tensorflow/tensorflow/contrib/pi_examples at master · tensorflow/tensorflow · GitHub
TensorFlow Raspberry Pi Examples This folder contains examples of how to build applications for the Raspberry Pi using TensorFlow. Building the Examples Follow the Raspberry Pi section of the instructions at tensorflow/contrib/makefile to compile a static library containing the core TensorFlow code. Install libjpeg, so we can load image files: sudo apt-get install -y libjpeg-dev To download the ex
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tensorflow/RELEASE.md at r0.12 · tensorflow/tensorflow
tensorflow anaconda : pip install fails in newly created python 2.7 environment · Issue #3324 · tensorflow/tensorflow
GitHub - tensorflow/deepmath: Experiments towards neural network theorem proving
Error building from source · Issue #5143 · tensorflow/tensorflow
tensorflow/tensorflow/tools/docker at r0.11 · tensorflow/tensorflow
models/README.md at master · tensorflow/models
GitHub - tensorflow/rust: Rust language bindings for TensorFlow
Wheel not supported installation problem: GPU Ubuntu 64 bit · Issue #3079 · tensorflow/tensorflow
TensorBoard: Embedding Visualization
Building TensorFlow for iOS failed on macOS Sierra and xCode 8.0 · Issue #4640 · tensorflow/tensorflow
