A High Level Glance¶
DataFlow is a library to load data efficiently in Python. Apart from DataFlow, native TF operators can be used for data loading as well. They will eventually be wrapped under the same interface and go through prefetching.
You can use any TF-based symbolic function library to define a model, including a small set of models within tensorpack.
ModelDescis an interface to connect symbolic graph to tensorpack trainers.
tensorpack trainers manage the training loops for you. They also include data parallel logic for multi-GPU or distributed training. At the same time, you have the power of customization through callbacks.
Callbacks are like
tf.train.SessionRunHook, or plugins. During training, everything you want to do other than the main iterations can be defined through callbacks and easily reused.