Deep Learning with TensorFlow

Pretty Tensor

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