gistfile1.py

class GSNCost(Cost):
    def __init__(self, costs):
        """Costs is a list a (int, float, Cost) tuples
        int : layer index to apply on
        float : coefficient for cost
        Cost : actual reconstruction cost for that layer
        """
        self.costs = costs
        
    def expr(self, model, data):
        """
        data is a list of the same length as costs.
        Each element is either a Theano tuple like or None.
        The order for data is the same as the order for costs (ie
        the first component of the data list becomes the layer described
        in the first cost tuple in self.costs)
        """
        indices = [c[0] for c in self.costs]
        
        # pass sparse list to model
        output = model.reconstruct(zip(indices, data))
        
        # output is of an identical format to data, except no elements are None
        
        cost = 0.0 # except actually make it a Theano tensor
        for cost_idx, _, coeff, cost_obj in enumerate(self.costs):
            if data[cost_idx] is not None:
                cost += coeff * cost_obj(data[cost_idx], output[cost_idx])
        return cost
        
    def get_data_spec(self, model):
        # what should go here??
  

You would need to know in advance (when the GSNCost object is built) which costs you will include. It is not something that can depend on the data only.

Assuming you have a sparse list of indices to include in self.cost_indices, you could do something like:

    def get_data_specs(self, model):
        spaces = []
        sources = []
        for cost_idx, _, coeff, cost_obj in enumerate(self.costs):
            if cost_idx in self.cost_indices:
                space, source = cost_obj.get_data_specs(model)
                spaces.append(space)
                sources.append(source)
            else:
                spaces.append(NullSpace())
                sources.append('')
        return (CompositeSpace(spaces), tuple(sources))

The else part is not necessary if, instead of checking for if data[...] is not None in self.expr, you check for if cost_idx in self.cost_indices.