SVAR from statsmodel.tsa: if len(A_guess) != n_masked_a: TypeError: object of type 'int' has no len()

I am using the following code to conduct a SVAR estimation but it keeps crashing, always the same kind of error:

len(A_guess) != n_masked_a: TypeError: object of type 'int' has no len().

CAN ANYONE HELP?

`data_q = pd.DataFrame({'GDP': GDP,
                       'CPI': CPI_q, 
                       'Interest_rate': Interest_rate_q, 
                       'Unemployment_rate': Unemployment_rate_q, 
                       'Yearly_inflation': Yearly_inflation_q}).dropna()

#SVAR model
A = np.array([
    [1, 0, 0, 0],
    ['E', 1, 0, 0],
    ['E', 'E', 1, 0],
    ['E', 'E', 'E', 1]
])
B = np.array([
    [1, 0, 0, 0],
    ['E', 1, 0, 0],
    ['E', 'E', 1, 0],
    ['E', 'E', 'E', 1]
])

endogenous_vars = ['GDP', 'Interest_rate', 'Unemployment_rate', 'Yearly_inflation']
exogenous_vars=["CPI"]

svar_model = SVAR(data_q[endogenous_vars], svar_type='AB', A=A, B=B)
svar_results = svar_model.fit(2)
print(svar_results.summary(), '\n')

irf_svar = svar_results.irf(10)
irf_svar.plot(orth=True)
plt.show()`

I tried to use the optional parameteres A_guess myself and trying to only using A or B, also using NAN and NONE instead of 'E'.