Inverse Probability Treatment Weighting in CIMTx in R

Question

I am trying to implement inverse probability treatment weighting with multinomial logistic regression using CIMTx package in R. However, I get an error that reads Error in pred_ps[, i] : subscript out of bounds when I use the following code, which uses the default settings for two treatments. How do I fix the error?

set.seed(1)
#load data
data <- data_sim(
  sample_size = 1000,
  n_trt = 2,
  x = "rnorm(0,1)",   #List of covariates
  lp_y = rep("x1",2), #linear effects in the outcome generating model
  nlp_y = NULL,       #nonlinear effects in the outcome generating model
  align = TRUE,       #predictors in treatment assignment model and outcome generating model are the same
  tau = c(0,0),     #outcome event probabilities (equal outcome event probability across three treatment groups)
  delta = c(0),     #ratio of units (equal sample sizes for each group)
  psi = 1             #sparsity of covariate overlap (moderate covariate overlap)
)
#Run IPTW with multinomial logistic regression
iptw_multi_res <- ce_estimate(y = data$y, x = data$covariates , w = data$w,
                               method = "IPTW-Multinomial", estimand = "ATE")
summary(iptw_multi_res)