Sonnet is a library built on top of TensorFlow for building complex neural networks.
Sonnet can be installed from pip, with or without GPU support.
This installation is compatible with Linux/Mac OS X and Python 2.7 and 3.{4,5,6}. The version of TensorFlow installed must be at least 1.2. Installing Sonnet supports the virtualenv installation mode of TensorFlow, as well as the native pip install.
To install sonnet, run:
$ pip install dm-sonnet
Sonnet will work with both the CPU and GPU version of tensorflow, but to allow for that it does not list Tensorflow as a requirement, so you need to install Tensorflow separately if you haven't already done so.
The following code constructs a Linear module and connects it to multiple inputs. The variables (i.e., the weights and biases of the linear transformation) are automatically shared.
import sonnet as snt
# Provide your own functions to generate data Tensors.
train_data = get_training_data()
test_data = get_test_data()
# Construct the module, providing any configuration necessary.
linear_regression_module = snt.Linear(output_size=FLAGS.output_size)
# Connect the module to some inputs, any number of times.
train_predictions = linear_regression_module(train_data)
test_predictions = linear_regression_module(test_data)
Check out the full documentation page here.