Correct way to use MPI with cmdstanpy

Modeling
2

damn - we don’t yet have the correct invocation needed to run MPI - cf discussion in this issue:

the implementation should be really pretty simple - PR’s welcome!

if you’re running reduce_sum without MPI, there’s some documentation here:
https://cmdstanpy.readthedocs.io/en/latest/sample.html#example-high-level-parallelization-with-reduce-sum

it can be the entire process including model compilation - or you can compile the model and pass in the exe file location - here’s an example script to run a single chain per node on a cluster:

# Use CmdStanPy to run one chain
# Required args:
# - cmdstanpath
# - model_exe
# - seed
# - chain_id
# - output_dir
# - data_file

import os
import sys

from cmdstanpy import CmdStanModel, set_cmdstan_path, cmdstan_path

useage = """\
run_chain.py <cmdstan_path> <model_exe> <seed> <chain_id> <output_dir> (<data_path>)\
"""

def main():
    if (len(sys.argv) < 5):
        print("missing arguments")
        print(useage)
        sys.exit(1)
    a_cmdstan_path = sys.argv[1]
    a_model_exe = sys.argv[2]
    a_seed = int(sys.argv[3])
    a_chain_id = int(sys.argv[4])
    a_output_dir = sys.argv[5]
    a_data_file = None
    if (len(sys.argv) > 5):
        a_data_file = sys.argv[6]

    set_cmdstan_path(a_cmdstan_path)
    mod = CmdStanModel(exe_file=a_model_exe)
    fit = mod.sample(chains=1, chain_ids=[a_chain_id], seed=a_seed, output_dir=a_output_dir, data=a_data_file)
    print(fit)

if __name__ == "__main__":
    main()