human
Solve the following python programming problem given the following code:
def _e_step(psamples, W_list, b_list, n_steps = 100, eps = 1e-05) : 
    "
    Performs 'n_steps' of mean-field inference (used to compute positive phase
    statistics)

    Parameters
    ----------
    psamples : array-like object of theano shared variables
        State of each layer of the DBM (during the inference process).
        psamples[0] points to the input
    n_steps :  integer
        Number of iterations of mean-field to perform
    " 
    depth = len (psamples) 
    def mf_iteration(* psamples) : 
        new_psamples = [p for p in psamples] 
        for i in xrange (1, depth, 2) : 
            new_psamples [i] = hi_given (psamples, i, W_list, b_list) 
for i in xrange (2, depth, 2) : 
            new_psamples [i] = hi_given (psamples, i, W_list, b_list) 
score = 0.0 
        for i in xrange (1, depth) : 
            score = T.maximum (T.mean (abs ((new_psamples [i] - psamples [i]))), score) 
return (new_psamples, theano.scan_module.until ((score < eps))) 
(new_psamples, updates) = scan (psamples, outputs_info = psamples, n_steps = n_steps) 
    return [x [(- 1)] for x in new_psamples] 

    
    

    Fix the buggy line: (new_psamples, updates) = scan (psamples, outputs_info = psamples, n_steps = n_steps)
assistant
#Here is Python program to fix the buggy line: (new_psamples, updates) = scan (psamples, outputs_info = psamples, n_steps = n_steps)
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(new_psamples, updates) = scan (def mf_iteration(, outputs_info = psamples, n_steps = n_steps)