gqs() can't handle sample from model where params are 0-length containers

Summary:

When generating quantities from a model that contains the ? operator in the parameter section, gqs will complain that that given parameter does not exist.
It seems that ? is not implemented in gqs()

Description:

First described here: https://discourse.mc-stan.org/t/generated-quantities-for-0-dim-vectors-matrices/11514/5

Reproducible Steps:

Here’s a minimal example that illustrates my problem (I'm on the rstan development branch):

m <- stan_model(model_code =
data {
  int<lower = 0, upper = 1> flag;
}
parameters { 
  real y; 
  vector[flag ? 1 : 0] phi;
}
model {
  if ( flag == 1 ) {
    phi ~ normal(10, 0.1);
    y ~ normal(phi, 1);
  } else if (flag == 0) {
    y ~ normal(0, 1);
    }
}')

f <- sampling(m, data =  list( flag =  1 ))
f

## 4 chains, each with iter=2000; warmup=1000; thin=1; 
## post-warmup draws per chain=1000, total post-warmup draws=4000.
## 
##       mean se_mean   sd  2.5%   25%   50%   75% 97.5% n_eff Rhat
## y     0.02    0.03 1.03 -1.99 -0.68  0.02  0.72  1.98  1175    1
## lp__ -0.53    0.02 0.75 -2.58 -0.68 -0.24 -0.06  0.00  1445    1
## 
## Samples were drawn using NUTS(diag_e) at Tue Oct 22 10:11:18 2019.
## For each parameter, n_eff is a crude measure of effective sample size,
## and Rhat is the potential scale reduction factor on split chains (at 
## convergence, Rhat=1).

So far, so good: When flag = 0, phi is a null-dimensional vector and not included in the output – nor in the as.matrix(f)

gqs part:

First, model is compiled with vector[flag ? 1 : 0] phi; commented out. Flag will be always 0:

mc <-'
data {
  int<lower = 0, upper = 1> flag;
}
parameters {
  real y;
  //  vector[flag ? 1 : 0] phi;
}
generated quantities {
    real y_rep;
    y_rep = normal_rng(y, 1);
}'

m2 <- stan_model(model_code = mc)

f2 <- rstan::gqs(m2, draws = as.matrix(f), data =  list( flag =  0))

## Inference for Stan model: 17e2d78e13de006222877a7663a21f94.
## 1 chains, each with iter=4000; warmup=0; thin=1; 
## post-warmup draws per chain=4000, total post-warmup draws=4000.
## 
##       mean se_mean   sd  2.5%   25%  50%  75% 97.5% n_eff Rhat
## y_rep 0.02    0.04 1.46 -2.83 -0.96 0.02 1.03  2.87  1641    1
## 
## Samples were drawn using  at Tue Oct 22 10:11:25 2019.
## For each parameter, n_eff is a crude measure of effective sample size,
## and Rhat is the potential scale reduction factor on split chains (at 
## convergence, Rhat=1).

This works because phi was commented out by hand.

Now, vector[flag ? 1 : 0] phi; is left in model, flag is still flag = 0

mc <-'
data {
  int<lower = 0, upper = 1> flag;
}
parameters {
  real y;
  vector[flag ? 1 : 0] phi;
}
generated quantities {
    real y_rep;
    y_rep = normal_rng(y, 1);
}

m2 <- stan_model(model_code = mc)`

Problem:

Now let’s call gqs(), with flag = 0

f2 <- rstan::gqs(m2, draws = as.matrix(f), data = list( flag = 0))
This returns:
Exception: Variable phi missing (in 'model49802b31ca9a_ea9a19bd60c8bdb46970b36a506c1c97' at line 7)

The summary indicates that nothing gets evaluated.

Also, it seems that the Exception always shows up when the ? operator is used, such as in
vector[flag ? 1 : 0] phi;

RStan Version:

rstan from development branch, version 2.19.9

R Version:

R version 3.6.1 (2019-07-05)

Operating System:

Ubuntu 18.04.3 LTS

Start by reproducing the failure through rstan::gqs() with the provided Stan model containing vector[flag ? 1 : 0] phi and flag = 0. Compare this with the commented-out-parameter case and trace how gqs() supplies draws for zero-length containers. Done means generated quantities run without the “Variable phi missing” exception while preserving the existing output behavior.