In instances where a neuron doesn't factor into the loss (e.g., a component of the loss is disabled for a specific experiment, resulting in a neuron or set of neurons being unused), autograd returns None for the unused connections. This results in a crash at the line:

param.grad *= 1./float(args['psuedo_batch_loop']*args['batch_size']

With the error:

TypeError: unsupported operand type(s) for *=: 'NoneType' and 'float'

This can be remedied by inserting:
if param.grad is not None:
prior to the line in question, but I'm unsure of any upstream consequences.