A tower is a component of a deep neural network that is itself structured as a neural network. Towers may process separate inputs independently before their outputs are combined, or they may interact through cross-connections in architectures such as encoder-decoder systems.
A component of a deep neural network that is itself a deep neural network. In some cases, each tower reads from an independent data source, and those towers stay independent until their output is combined in a final layer. In other cases, (for example, in the encoder and decoder tower of many Transformers), towers have cross-connections to each other.