Deep Learning with TensorFlow - Second Edition

PrettyTensor

PrettyTensor allows the developer to wrap TensorFlow operations to quickly chain any number of layers to define neural networks. Coming up is simple example of Pretty Tensor's capabilities: we wrap a standard TensorFlow object, pretty, into a library-compatible object; then we feed it through three fully connected layers, and we 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 PrettyTensor installation is very simple. You can just use the pip installer:

sudo pip install prettytensor

Chaining layers

PrettyTensor has three modes of operation that ...