ValueError: NaN, inf or invalid value detected in endog, estimation infeasible. in GLM model

Question

I am using statsmodel GLM for linear prediction. This is the code that I set exog and endog

X_train = claim_data_x.iloc[:,5:].values
Y_train = claim_data_x.loc[:,'LOSS_AMOUNT'].values
num_claims = claim_data_x.loc[:,'CLAIM_FREQ'].values
X_test = claim_data_y.iloc[:,5:].values

While creating model no any error raise:

glm_model = sm.GLM(endog=Y_train, exog=X_train, family= sm.families.Gamma(link=sm.families.links.log()), offset = np.log(num_claims))

But while fitting train data to see the summary output I face with error:

glm_model.fit().summary(xname = list(data_x.iloc[:,6:].columns))

ValueError: NaN, inf or invalid value detected in endog, estimation infeasible.

Can anyone have any idea?