remove deep_copy from generated code and parser warnings

[bob-carpenter]

Summary:

The deep_copy function is applied to right-hand sides of assignments to avoid aliasing. However, all of our array slicing makes a copy itself, so this isn't necessary.

Also, if we don't use deep_copy anywhere else in the code base, we can remove the deep_copy function too (I'm not sure if this is defined in this repo or in stan-dev/math; if the latter, we'll need a new issue).

Reproducible Steps:

You can test this with:

parameters {
  real<lower = 0, upper = 1> foo;
}
generated quantities {
  vector[3] a = [1, 2, 3]';
  a[2:3] += a[1:2];
}

and get the right answer in the current setup which forgot to include the deep_copy,

Current Output:

      mean
a[1]  1.00
a[2]  3.00 
a[3]  5.00

Expected Output:

This is correct, so we don't need the deep_copy. Here's the generated C++ to validate there's no deep copy happening:

// Code generated by Stan version 2.18.0

#include <stan/model/model_header.hpp>

namespace foo_model_namespace {

using std::istream;
using std::string;
using std::stringstream;
using std::vector;
using stan::io::dump;
using stan::math::lgamma;
using stan::model::prob_grad;
using namespace stan::math;

static int current_statement_begin__;

stan::io::program_reader prog_reader__() {
    stan::io::program_reader reader;
    reader.add_event(0, 0, "start", "/Users/carp/temp2/foo.stan");
    reader.add_event(8, 6, "end", "/Users/carp/temp2/foo.stan");
    return reader;
}

class foo_model : public prob_grad {
private:
    int a;
public:
    foo_model(stan::io::var_context& context__,
        std::ostream* pstream__ = 0)
        : prob_grad(0) {
        ctor_body(context__, 0, pstream__);
    }

    foo_model(stan::io::var_context& context__,
        unsigned int random_seed__,
        std::ostream* pstream__ = 0)
        : prob_grad(0) {
        ctor_body(context__, random_seed__, pstream__);
    }

    void ctor_body(stan::io::var_context& context__,
                   unsigned int random_seed__,
                   std::ostream* pstream__) {
        typedef double local_scalar_t__;

        boost::ecuyer1988 base_rng__ =
          stan::services::util::create_rng(random_seed__, 0);
        (void) base_rng__;  // suppress unused var warning

        current_statement_begin__ = -1;

        static const char* function__ = "foo_model_namespace::foo_model";
        (void) function__;  // dummy to suppress unused var warning
        size_t pos__;
        (void) pos__;  // dummy to suppress unused var warning
        std::vector<int> vals_i__;
        std::vector<double> vals_r__;
        local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());
        (void) DUMMY_VAR__;  // suppress unused var warning

        // initialize member variables
        try {

            // validate, data variables
            // initialize data variables
            current_statement_begin__ = 2;
            a = int(0);
            stan::math::fill(a, std::numeric_limits<int>::min());

            {
            current_statement_begin__ = 4;
            validate_non_negative_index("b", "2", 2);
            vector<local_scalar_t__> b(2);
            stan::math::initialize(b, DUMMY_VAR__);
            stan::math::fill(b,DUMMY_VAR__);
            stan::math::assign(b,static_cast<std::vector<double> >(stan::math::array_builder<double >().add(3).add(4.0).array()));


            }

            // validate transformed data
            current_statement_begin__ = 2;

            // validate, set parameter ranges
            num_params_r__ = 0U;
            param_ranges_i__.clear();
        } catch (const std::exception& e) {
            stan::lang::rethrow_located(e, current_statement_begin__, prog_reader__());
            // Next line prevents compiler griping about no return
            throw std::runtime_error("*** IF YOU SEE THIS, PLEASE REPORT A BUG ***");
        }
    }

    ~foo_model() { }


    void transform_inits(const stan::io::var_context& context__,
                         std::vector<int>& params_i__,
                         std::vector<double>& params_r__,
                         std::ostream* pstream__) const {
        stan::io::writer<double> writer__(params_r__,params_i__);
        size_t pos__;
        (void) pos__; // dummy call to supress warning
        std::vector<double> vals_r__;
        std::vector<int> vals_i__;

        params_r__ = writer__.data_r();
        params_i__ = writer__.data_i();
    }

    void transform_inits(const stan::io::var_context& context,
                         Eigen::Matrix<double,Eigen::Dynamic,1>& params_r,
                         std::ostream* pstream__) const {
      std::vector<double> params_r_vec;
      std::vector<int> params_i_vec;
      transform_inits(context, params_i_vec, params_r_vec, pstream__);
      params_r.resize(params_r_vec.size());
      for (int i = 0; i < params_r.size(); ++i)
        params_r(i) = params_r_vec[i];
    }


    template <bool propto__, bool jacobian__, typename T__>
    T__ log_prob(vector<T__>& params_r__,
                 vector<int>& params_i__,
                 std::ostream* pstream__ = 0) const {

        typedef T__ local_scalar_t__;

        local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());
        (void) DUMMY_VAR__;  // suppress unused var warning

        T__ lp__(0.0);
        stan::math::accumulator<T__> lp_accum__;

        try {
            // model parameters
            stan::io::reader<local_scalar_t__> in__(params_r__,params_i__);


            // transformed parameters



            // validate transformed parameters

            const char* function__ = "validate transformed params";
            (void) function__;  // dummy to suppress unused var warning

            // model body

        } catch (const std::exception& e) {
            stan::lang::rethrow_located(e, current_statement_begin__, prog_reader__());
            // Next line prevents compiler griping about no return
            throw std::runtime_error("*** IF YOU SEE THIS, PLEASE REPORT A BUG ***");
        }

        lp_accum__.add(lp__);
        return lp_accum__.sum();

    } // log_prob()

    template <bool propto, bool jacobian, typename T_>
    T_ log_prob(Eigen::Matrix<T_,Eigen::Dynamic,1>& params_r,
               std::ostream* pstream = 0) const {
      std::vector<T_> vec_params_r;
      vec_params_r.reserve(params_r.size());
      for (int i = 0; i < params_r.size(); ++i)
        vec_params_r.push_back(params_r(i));
      std::vector<int> vec_params_i;
      return log_prob<propto,jacobian,T_>(vec_params_r, vec_params_i, pstream);
    }


    void get_param_names(std::vector<std::string>& names__) const {
        names__.resize(0);
    }


    void get_dims(std::vector<std::vector<size_t> >& dimss__) const {
        dimss__.resize(0);
        std::vector<size_t> dims__;
    }

    template <typename RNG>
    void write_array(RNG& base_rng__,
                     std::vector<double>& params_r__,
                     std::vector<int>& params_i__,
                     std::vector<double>& vars__,
                     bool include_tparams__ = true,
                     bool include_gqs__ = true,
                     std::ostream* pstream__ = 0) const {
        typedef double local_scalar_t__;

        vars__.resize(0);
        stan::io::reader<local_scalar_t__> in__(params_r__,params_i__);
        static const char* function__ = "foo_model_namespace::write_array";
        (void) function__;  // dummy to suppress unused var warning
        // read-transform, write parameters

        // declare and define transformed parameters
        double lp__ = 0.0;
        (void) lp__;  // dummy to suppress unused var warning
        stan::math::accumulator<double> lp_accum__;

        local_scalar_t__ DUMMY_VAR__(std::numeric_limits<double>::quiet_NaN());
        (void) DUMMY_VAR__;  // suppress unused var warning

        try {



            // validate transformed parameters

            // write transformed parameters
            if (include_tparams__) {
            }
            if (!include_gqs__) return;
            // declare and define generated quantities



            // validate generated quantities

            // write generated quantities
        } catch (const std::exception& e) {
            stan::lang::rethrow_located(e, current_statement_begin__, prog_reader__());
            // Next line prevents compiler griping about no return
            throw std::runtime_error("*** IF YOU SEE THIS, PLEASE REPORT A BUG ***");
        }
    }

    template <typename RNG>
    void write_array(RNG& base_rng,
                     Eigen::Matrix<double,Eigen::Dynamic,1>& params_r,
                     Eigen::Matrix<double,Eigen::Dynamic,1>& vars,
                     bool include_tparams = true,
                     bool include_gqs = true,
                     std::ostream* pstream = 0) const {
      std::vector<double> params_r_vec(params_r.size());
      for (int i = 0; i < params_r.size(); ++i)
        params_r_vec[i] = params_r(i);
      std::vector<double> vars_vec;
      std::vector<int> params_i_vec;
      write_array(base_rng,params_r_vec,params_i_vec,vars_vec,include_tparams,include_gqs,pstream);
      vars.resize(vars_vec.size());
      for (int i = 0; i < vars.size(); ++i)
        vars(i) = vars_vec[i];
    }

    static std::string model_name() {
        return "foo_model";
    }


    void constrained_param_names(std::vector<std::string>& param_names__,
                                 bool include_tparams__ = true,
                                 bool include_gqs__ = true) const {
        std::stringstream param_name_stream__;

        if (!include_gqs__ && !include_tparams__) return;

        if (include_tparams__) {
        }


        if (!include_gqs__) return;
    }


    void unconstrained_param_names(std::vector<std::string>& param_names__,
                                   bool include_tparams__ = true,
                                   bool include_gqs__ = true) const {
        std::stringstream param_name_stream__;

        if (!include_gqs__ && !include_tparams__) return;

        if (include_tparams__) {
        }


        if (!include_gqs__) return;
    }

}; // model

}

typedef foo_model_namespace::foo_model stan_model;

Current Version:

v2.18.0