All posts in: C/C++

Today, 1th of June Google brain team committed new code in public.
There are some interesting points:
1) High level APIs will be presented as a separate SwiftPM package under github.com/tensorflow.

High level APIs were added earlier purely to explore the programming model, not to be usable by anyone. Having high level APIs be part of the stdlib module conveys a wrong message for beta testers, and it has been confusing ever since our open source release.

2) Supporting Python code is one of priority:

  • Improved Python diagnostics related to member access.
  • Improved Python C API functions for binary arithmetic operations.

3) Improved cross-device sends and receives support.

4) Lots of work done around supporting generic @dynamicCallable methods.

5) Deprecated a.dot(b) and to matmul(a, b).

Kraken as height level API for TensorFlow.

Since today Kraken is high – level API and brain system for the most powerful deep – learning framework TensorFlow.

TensorFlow is the fastest growing solution for neural networks. Written on C++ language it shows huge performance on CPU and GPU hardware. Kraken could help us to build deep learning architecture at real time and test them in different ways and on different servers.

Using TensorFlow library as core of our Neural Network you can get lot’s of benefits as:

  • Many dimansion Pooling layer;
  • Many dimansion Normalization layer;
  • Many dimansion Convolution layer;
  • Densely-connected layer;
  • Many dimansion Pooling layer;
  • RNN and LSTM solutions;
  • Optimizer;

From today our tool is incredible powerful and strong.

Each machine learning task is related with big amount of data. Analyzing a network is a complex and confusing task. To resolve that issue, Google announced launch of visualization tools called TensorBoard.

Currently that is the most useful source-code tool. Unfortunately that tool works only with TensorFlow library from the box. There is no way to feed it with json or xml logs.

Deepening  into a self-written neural network you can’t avoid any data-visualization task. For that reason you can use Tensorboard from C/C++/Java or Swift application.

How to do that, I will describe further.

Read More