human
Solve the following python programming problem given the following code:
def make_thunk(self, node, storage_map, _, _2) : 
    super (CuIFFTOp, self).make_thunk (node, storage_map, _, _2) 
    from theano.misc.pycuda_utils import to_gpuarray 
    inputs = [storage_map [v] for v in node.inputs] 
    outputs = [self [v] for v in node.outputs] 
    plan_input_shape = [None] 
    plan = [None] 
    def thunk() : 
        input_shape = inputs [0] [0].shape 
        output_shape = list (input_shape [: (- 1)]) 
        output_shape [(- 1)] = ((output_shape [(- 1)] - 1) * 2) 
        output_shape = tuple (output_shape) 
        z = outputs [0] 
        if ((z [0] is None) or (z [0].shape != output_shape)) : 
            z [0] = CudaNdarray.zeros (output_shape) 
input_pycuda = to_gpuarray (inputs [0] [0]) 
        output_pycuda = to_gpuarray (z [0]) 
        if ((plan [0] is None) or (plan_input_shape [0] != input_shape)) : 
            plan_input_shape [0] = input_shape 
            plan [0] = fft.Plan (output_shape [1 :], np.complex64, np.float32, batch = output_shape [0]) 
fft.ifft (input_pycuda, output_pycuda, plan [0]) 
thunk.inputs = inputs 
    thunk.outputs = outputs 
    thunk.lazy = False 
    return thunk 

    
    

    Fix the buggy line: outputs = [self [v] for v in node.outputs]
assistant
#Here is Python code to fix the buggy line: outputs = [self [v] for v in node.

outputs = [storage_map [v] for v in node.outputs]