Yet Another Deep Learning Lab. Ultra light Deep Learning framework based on Theano
Project description
Yadll
Yet another deep learning lab.
This is an ultra light deep learning framework written in Python and based on Theano. It allows you to very quickly start building Deep Learning models and play with toy examples.
If you are looking for a light deep learning API I would recommend using Lasagne or keras instead of yadll, both are mature, well documented and contributed projects.
Read the documentation at Read the doc
Its main features are:
Layers:
Input Layer
Dropout Layer
Pool Layer
Conv Layer:
ConvPool Layer
Dense Layer:
Logistic Regression
Dropconnect
Unsupervised Layer:
Autoencoder (denoising autoencoder)
Restricted Boltzmann Machine
RNN
LSTM
GRU
Optimisation:
Sgd
Momentum
Nesterov momentum
Adagrad
Adadelta
Rmsprop
Adam
Adamax
Hyperparameters grid search
Installation
git clone git@github.com:pchavanne/yadll.git
cd yadll
pip install -e .
Example
Different networks tested on mnist:
Logisitic Regression
Multi Layer Perceptron
MLP with dropout
MLP with dropconnect
Conv Pool
LeNet-5
Autoencoder
Denoising Autoencoder
Gaussian Denoising Autoencoder
Contractive Denoising Autoencoder
Stacked Denoising Autoencoder
Restricted Boltzmann Machine
Deep Belief Network
Recurrent Neural Networks
Long Short-Term Memory
Gated Recurrent unit
get the list of available networks:
python mnist_dl.py --network_list
trainning a model for example lenet5:
python mnist_dl.py lenet5
grid search on the hyperparameters:
python hp_grid_search.py
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