# mpl.params[(si + 1) * sh:(sh + 1) * so + (si + 1) * sh] = t2.reshape((so * (sh + 1),))
# compute cost
print('* Cost Function: ' + str(mpl.cost_function(mpl.params)) + ' ' + str(2.10095))
print('Diff: ' + str(mpl.cost_function(mpl.params) - 2.10095))
print('')
# compute regularized cost
print('* Regularized Cost Function: ' + str(mpl.cost_function(mpl.params)) + ' ' + str(2.25231))
print('Diff: ' + str(mpl.cost_function(mpl.params) - 2.25231))
print('')
print('* Gradient Checking')
# g = mpl.usual_grad(mpl.params) # mpl.gradient(mpl.params, 0)
g = mpl.gradient(mpl.params)
num = mpl.numerical_gradient(mpl.params)
gr = mpl.gradient(mpl.params)
numr = mpl.numerical_gradient(mpl.params)
grad = pd.DataFrame({'ag': g, 'anum': num, 'bgr': gr, 'bnumr': numr})
print(grad.head(10))
print('')
print('* Difference Should be Small:')
print(' Dif: ' + str(sum(grad['ag'] - grad['anum'])))
print('rDif: ' + str(sum(grad['bgr'] - grad['bnumr'])))
print('')
if file_option['run_real']:
