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Check out the latest superpixel benchmark — Superpixel Benchmark (2016) — and let me know your opinion! @david_stutz

TAG»TENSORFLOW«

ARTICLE

A Note on Extending Tensorflow, PyTorch and Theano for Deep Learning on Custom DataStructures

Many recent deep learning frameworks such as Tensorflow, PyTorch, Theano or Torch are based on dense tensors. However, deep learning on non-tensor data structures is also interesting – especially for sparse, three-dimensional data. This article summarizes some of my experiences regarding deep learning on custom data structures in the mentioned libraries.

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SERIES»Working with Ubuntu«

Building Tensorflow in an NFS-mounted $HOME, CUDA 8.0 Without Manual Driver Installation

This blog series collects useful insights for working with Ubuntu. In this article, I describe how to avoid building problems when building Tensorflow on an NFS-mounted $HOME directory and how to install CUDA 8.0 without a manual driver installation.

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ARTICLE

Inspecting Tensorflow’s Tensors using C++ and Bazel

Currently it is difficult to successfully link C++ projects with Tensorflow. However, to compile and run smaller code snippets based on Tensorflow, it might be convenient to put the code inside the tensorflow code base and compile an individual executable using Bazel.

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24thFEBRUARY2017

SNIPPET

A simple implementation of batch normalization in Tensorflow. Note that the implementation is meant for training — i.e. for testing on individual samples, the mean and variance should be fixed in advance. Also note that tf.nn.moments is replaced by a custom method for computing mean and variance to avoid the problem described here.

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23thFEBRUARY2017

SNIPPET

In specific cases, tf.nn.moments cannot be run on the GPU (see here). This is problematic when training (convolutional) neural networks where moments are part of the computation graph (e.g. for normalization). This snippet is a simple work around, computing mean and variance along the provided dimensions manually.

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16thFEBRUARY2017

SNIPPET

Slightly adapted example for adding new operations in Tensorflow taken from the official documentation. The files should be copied to tensorflow/core/user_ops. The new operation is compiled using bazel build -c opt //tensorflow/core/user_ops:zero_out.so from the Tensorflow root. The generated .so file can usually be found by searching bazel-bin. This code does not include the corresponding gradient function yet.

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ARTICLE

Implementing Tensorflow Operations in C++ — Including Gradients

In this article, I discuss a simple Tensorflow operation implemented in C++. While the example mostly builds upon the official documentation, it includes trainable parameters and the gradient computation is implemented in C++, as well. As such, the example is slightly more complex compared to the simple ZeroOut operation discussed in the documentation.

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ARTICLE

Upgrading CUDA and Installing CuDNN for Caffe and Tensorflow

Recently, I started working with Tensorflow — a deep learning library developed by Google. Unfortunately, Tensorflow did not work with the installed Version of CUDA. Therefore, I decided to upgrade to CUDA 8.0 and also install CuDNN. This article describes the installation process.

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