model.fit_generator

def generator():
    while 1:
        global cnt
        cnt += 1
        print("cnt: ",cnt)
        x = X_train[(cnt-1)*batch_size:(cnt)*batch_size,:]
        y = Y_train[(cnt-1)*batch_size:(cnt)*batch_size,:]
        yield x,y

def val():
    while 1:
        global cnt1
        cnt1 += 1
        print("\n cnt1 :",cnt1)
        x = X_test[(cnt1-1)*6:(cnt1)*6,:]
        y = Y_test[(cnt1-1)*6:(cnt1)*6,:]
        yield X_test,Y_test        
   

model.fit_generator(generator(),epochs=1000,
                    steps_per_epoch=1,#len(x_train)//(batch_size),
                   validation_data=val(),#(X_test,Y_test),#validation_split=0.1,
                    validation_steps = 1,
                   callbacks = [ endEpochHookCB ,reduce_lr, early_stopping])