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LSTM implementation on Caffe

License: Other

CMake 0.33% Makefile 0.73% Shell 0.36% C++ 82.38% MATLAB 1.05% M 0.01% Python 8.59% Cuda 5.05% Protocol Buffer 1.51%

caffe-lstm's Introduction

LSTM Implementation in Caffe

  • This is my personal implementation of LSTM in Caffe with minimal modifications.
  • The official Caffe is going to support LSTM/RNN (not my code).
  • See the following link for the details LSTM Pull Request

Example

An example code is in /examples/lstm_sequence/.
In this code, LSTM network is trained to generate a predefined sequence without any inputs.
This experiment was introduced by Clockwork RNN.
Four different LSTM networks and shell scripts(.sh) for training are provided.
Each script generates a log file containing the predicted sequence and the true sequence.
You can use plot_result.m to visualize the result.
The result of four LSTM networks will be as follows:

  • 1-layer LSTM with 15 hidden units for short sequence Diagram
  • 1-layer LSTM with 50 hidden units for long sequence Diagram
  • 3-layer deep LSTM with 7 hidden units for short sequence Diagram
  • 3-layer deep LSTM with 23 hidden units for long sequence Diagram

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