tinynn is a lightweight deep learning framework written in Python3 (for learning purposes).
pip3 install tinynn
git clone https://github.com/borgwang/tinynn.git
cd tinynn/examples
# MNIST classification
python3 mnist/run.py
# a toy regression task
python3 nn_paint/run.py
# reinforcement learning demo (gym environment required)
python3 rl/run.py
# define a model
net = Net([Dense(50), ReLU(), Dense(100), ReLU(), Dense(10)])
model = Model(net=net, loss=MSE(), optimizer=Adam(lr))
# train
for batch in iterator(train_x, train_y):
preds = model.forward(batch.inputs)
loss, grads = model.backward(preds, batch.targets)
model.apply_grads(grads)
Please follow the Google Python Style Guide for Python coding style.
MIT