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Update docs and tests for Stan 2.32 syntax changes
Address this kind of warning:
Declaration of arrays by placing brackets after a variable name is deprecated and
will be removed in Stan 2.32.0. Instead use the array keyword before the
type. This can be changed automatically using the auto-format flag to
stanc
Documentation and tests must be updated.
I just ran into this as well, while trying to get started with stan/pystan using the documentation at https://pystan.readthedocs.io/en/latest/ This is what is there now:
import stan
schools_code = """
data {
int<lower=0> J; // number of schools
real y[J]; // estimated treatment effects
real<lower=0> sigma[J]; // standard error of effect estimates
}
parameters {
real mu; // population treatment effect
real<lower=0> tau; // standard deviation in treatment effects
vector[J] eta; // unscaled deviation from mu by school
}
transformed parameters {
vector[J] theta = mu + tau * eta; // school treatment effects
}
model {
target += normal_lpdf(eta | 0, 1); // prior log-density
target += normal_lpdf(y | theta, sigma); // log-likelihood
}
"""
schools_data = {"J": 8,
"y": [28, 8, -3, 7, -1, 1, 18, 12],
"sigma": [15, 10, 16, 11, 9, 11, 10, 18]}
posterior = stan.build(schools_code, data=schools_data)
fit = posterior.sample(num_chains=4, num_samples=1000)
eta = fit["eta"] # array with shape (8, 4000)
df = fit.to_frame() # pandas `DataFrame, requires pandas
Running the above, we get the following messages from the stan.build function:
Messages from stanc:
Warning in '/tmp/httpstan_yl4pxs0i/model_zzhabz4t.stan', line 4, column 2: Declaration
of arrays by placing brackets after a variable name is deprecated and
will be removed in Stan 2.32.0. Instead use the array keyword before the
type. This can be changed automatically using the auto-format flag to
stanc
Warning in '/tmp/httpstan_yl4pxs0i/model_zzhabz4t.stan', line 5, column 2: Declaration
of arrays by placing brackets after a variable name is deprecated and
will be removed in Stan 2.32.0. Instead use the array keyword before the
type. This can be changed automatically using the auto-format flag to
stanc
Warning: The parameter tau has no priors. This means either no prior is
provided, or the prior(s) depend on data variables. In the later case,
this may be a false positive.
Warning: The parameter mu has no priors. This means either no prior is
provided, or the prior(s) depend on data variables. In the later case,
this may be a false positive.
Then posterior.sample fails with:
---------------------------------------------------------------------------
RuntimeError Traceback (most recent call last)
Cell In [3], line 1
----> 1 fit = posterior.sample(num_chains=4, num_samples=1000)
File ~/.local/lib/python3.10/site-packages/stan/model.py:89, in Model.sample(self, num_chains, **kwargs)
61 def sample(self, *, num_chains=4, **kwargs) -> stan.fit.Fit:
62 """Draw samples from the model.
63
64 Parameters in ``kwargs`` will be passed to the default sample function.
(...)
87
88 """
---> 89 return self.hmc_nuts_diag_e_adapt(num_chains=num_chains, **kwargs)
File ~/.local/lib/python3.10/site-packages/stan/model.py:108, in Model.hmc_nuts_diag_e_adapt(self, num_chains, **kwargs)
92 """Draw samples from the model using ``stan::services::sample::hmc_nuts_diag_e_adapt``.
93
94 Parameters in ``kwargs`` will be passed to the (Python wrapper of)
(...)
105
106 """
107 function = "stan::services::sample::hmc_nuts_diag_e_adapt"
--> 108 return self._create_fit(function=function, num_chains=num_chains, **kwargs)
File ~/.local/lib/python3.10/site-packages/stan/model.py:312, in Model._create_fit(self, function, num_chains, **kwargs)
309 return fit
311 try:
--> 312 return asyncio.run(go())
313 except KeyboardInterrupt:
314 return
File /usr/local/lib/python3.10/asyncio/runners.py:44, in run(main, debug)
42 if debug is not None:
43 loop.set_debug(debug)
---> 44 return loop.run_until_complete(main)
45 finally:
46 try:
File /usr/local/lib/python3.10/asyncio/base_events.py:646, in BaseEventLoop.run_until_complete(self, future)
643 if not future.done():
644 raise RuntimeError('Event loop stopped before Future completed.')
--> 646 return future.result()
File ~/.local/lib/python3.10/site-packages/stan/model.py:236, in Model._create_fit.<locals>.go()
234 sampling_output.write_line("<info>Sampling:</info> <error>Initialization failed.</error>")
235 raise RuntimeError("Initialization failed.")
--> 236 raise RuntimeError(message)
238 resp = await client.get(f"/{fit_name}")
239 if resp.status != 200:
RuntimeError: Exception during call to services function: `BrokenProcessPool('A child process terminated abruptly, the process pool is not usable anymore')`, traceback: `[' File "/home/knappa/.local/lib/python3.10/site-packages/httpstan/services_stub.py", line 112, in call\n future = asyncio.get_running_loop().run_in_executor(executor, lazy_function_wrapper_partial) # type: ignore\n', ' File "/usr/local/lib/python3.10/asyncio/base_events.py", line 818, in run_in_executor\n executor.submit(func, *args), loop=self)\n', ' File "/usr/local/lib/python3.10/concurrent/futures/process.py", line 715, in submit\n raise BrokenProcessPool(self._broken)\n']`
This is on a debian box, running pystan 3.5.0, installed through pip.
This looks like a different issue. Warnings should not stop sample from succeeding. Can you create a new issue? You shouldn't be encountering problems on Debian 11.
For the issue proper, this is what CmdStanPy uses:
data {
int<lower=0> J; // number of schools
array[J] real y; // estimated treatment effect (school j)
array[J] real<lower=0> sigma; // std err of effect estimate (school j)
}
parameters {
real mu;
array[J] real theta;
real<lower=0> tau;
}
model {
theta ~ normal(mu, tau);
y ~ normal(theta, sigma);
}