Pretty Tensor allows the developer to wrap TensorFlow operations, to quickly chain any number of layers to define neural networks.
The following is a simple example of the Pretty Tensor capabilities. We wrap a standard TensorFlow object, pretty, into a library compatible object, then we feed it through three fully connected layers, to finally output a softmax distribution:
pretty = tf.placeholder([None, 784], tf.float32)
softmax = (prettytensor.wrap(examples)
.fully_connected(256, tf.nn.relu)
.fully_connected(128, tf.sigmoid)
.fully_connected(64, tf.tanh)
.softmax(10))
The Pretty Tensor installation is very simple; just use the pip installer:
sudo pip install prettytensor
