Formulation classes checking for single input/output layers in multiple places

[jezsadler]

The neural network formulations have checks that they're given graphs with single inputs and outputs, but these checks are implemented inconsistently in different places.

• the ReluPartitionFormulation checks for single input and output in its '_build_formulation' private method, but that's only ever called by the OmltBlock's 'build_formulation' method, which first checks for single input and output, so the checks in the private method are never hit.
• the FullSpaceNetworkFormulation also checks for single input/output on initialization. Maybe the other formulations should also do this, instead of waiting until a check or build time? Or is the expectation that users would have a partially-built network, initialize a formulation on it, and then finalize the network and build?
• maybe this validation should be in the base class rather than implemented in each of the different formulations?