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attendant objects.  Also fixed a minor bug in the loss layer.

rather than a compile time constant.  This also removes it from the input layer
interface since the DNN core infers its value at runtime, meaning users that
define their own input layers don't need to specify it anymore.

interface.

- Made layer() recurse into repeat objects so that the index given to layer()
  does what you would expect.
- Added an operator<< for network objects that prints the network architecture.

objects.  Then made the relevant parts of the code use these functions.

than adding them.  This way, the gradient buffer can be used as scratch space
during the loss computation.

that contain a different number of samples than their input tensors.