Combiners are part of the model that take all the outputs of the different input features and combine them in a single representation that is passed to the outputs. You can specify which one to use in the combiner section of the configuration. Different combiners implement different combination logic, but the default one concat just concatenates all outputs of input feature encoders and optionally passes the concatenation through fully connected layers, with the output of the last layer being forwarded to the outputs decoders.

|Input      |
|Feature 1  +-+
+-----------+ |            +---------+
+-----------+ | +------+   |Fully    |
|...        +--->Concat+--->Connected+->
+-----------+ | +------+   |Layers   |
+-----------+ |            +---------+
|Input      +-+
|Feature N  |

For the sake of simplicity you can imagine the both inputs and outputs are vectors in most of the cases, but there are reduce_input and reduce_output parameters to specify to change the default behavior.