structured writer - compiler error

src/stan/mcmc/hmc/base_hmc.hpp

@@ -3,7 +3,7 @@
 
 #include <stan/callbacks/logger.hpp>
 #include <stan/callbacks/writer.hpp>
-#include <stan/callbacks/json_writer.hpp>
+#include <stan/callbacks/structured_writer.hpp>
 #include <stan/mcmc/base_mcmc.hpp>
 #include <stan/mcmc/hmc/hamiltonians/ps_point.hpp>
 #include <boost/random/uniform_01.hpp>
@@ -67,13 +67,12 @@ class base_hmc : public base_mcmc {
   /**
    * write stepsize and elements of mass matrix as a JSON object
    */
-  template <typename Stream, typename Deleter = std::default_delete<Stream>>
-  void write_sampler_state_json(
-      callbacks::json_writer<Stream, Deleter>& json_writer) {
-    json_writer.begin_record();
-    json_writer.write("stepsize", get_nominal_stepsize());
-    json_writer.write("inv_metric", z_.inv_e_metric_);
-    json_writer.end_record();
+  void write_sampler_state_struct(
+      callbacks::structured_writer& struct_writer) {
+    struct_writer.begin_record();
+    struct_writer.write("stepsize", get_nominal_stepsize());
+    struct_writer.write("inv_metric", z_.inv_e_metric_);
+    struct_writer.end_record();
   }
 
   void get_sampler_diagnostic_names(std::vector<std::string>& model_names,

src/stan/services/sample/fixed_param.hpp

@@ -2,16 +2,16 @@
 #define STAN_SERVICES_SAMPLE_FIXED_PARAM_HPP
 
 #include <stan/callbacks/interrupt.hpp>
-#include <stan/callbacks/json_writer.hpp>
 #include <stan/callbacks/logger.hpp>
+#include <stan/callbacks/structured_writer.hpp>
 #include <stan/callbacks/writer.hpp>
 #include <stan/math/prim.hpp>
 #include <stan/mcmc/fixed_param_sampler.hpp>
 #include <stan/services/error_codes.hpp>
-#include <stan/services/util/mcmc_writer.hpp>
-#include <stan/services/util/generate_transitions.hpp>
 #include <stan/services/util/create_rng.hpp>
+#include <stan/services/util/generate_transitions.hpp>
 #include <stan/services/util/initialize.hpp>
+#include <stan/services/util/mcmc_writer.hpp>
 #include <chrono>
 #include <vector>
 #include <iostream>
@@ -65,8 +65,8 @@ int fixed_param(Model& model, const stan::io::var_context& init,
   }
 
   stan::mcmc::fixed_param_sampler sampler;
-  callbacks::json_writer<std::ofstream> dummy_metric_writer;
-  services::util::mcmc_writer<std::ofstream> writer(
+  callbacks::structured_writer dummy_metric_writer;
+  services::util::mcmc_writer writer(
       sample_writer, diagnostic_writer, dummy_metric_writer, logger);
   Eigen::VectorXd cont_params(cont_vector.size());
   for (size_t i = 0; i < cont_vector.size(); i++)
@@ -140,8 +140,8 @@ int fixed_param(Model& model, const std::size_t num_chains,
   }
   std::vector<boost::ecuyer1988> rngs;
   std::vector<Eigen::VectorXd> cont_vectors;
-  std::vector<callbacks::json_writer<std::ofstream>> dummy_metric_writers;
-  std::vector<util::mcmc_writer<std::ofstream>> writers;
+  std::vector<callbacks::structured_writer> dummy_metric_writers;
+  std::vector<util::mcmc_writer> writers;
   std::vector<stan::mcmc::sample> samples;
   std::vector<stan::mcmc::fixed_param_sampler> samplers(num_chains);
   rngs.reserve(num_chains);
@@ -157,7 +157,7 @@ int fixed_param(Model& model, const std::size_t num_chains,
         Eigen::Map<Eigen::VectorXd>(cont_vector.data(), cont_vector.size()));
     samples.emplace_back(cont_vectors[i], 0, 0);
     dummy_metric_writers.emplace_back(
-        stan::callbacks::json_writer<std::ofstream>());
+        stan::callbacks::structured_writer());
     writers.emplace_back(sample_writers[i], diagnostic_writers[i],
                          dummy_metric_writers[i], logger);
     // Headers

src/stan/services/sample/hmc_nuts_dense_e_adapt.hpp

@@ -3,17 +3,16 @@
 
 #include <stan/callbacks/interrupt.hpp>
 #include <stan/callbacks/logger.hpp>
+#include <stan/callbacks/structured_writer.hpp>
 #include <stan/callbacks/writer.hpp>
-#include <stan/callbacks/json_writer.hpp>
 #include <stan/io/var_context.hpp>
 #include <stan/math/prim.hpp>
 #include <stan/mcmc/hmc/nuts/adapt_dense_e_nuts.hpp>
 #include <stan/services/error_codes.hpp>
-#include <stan/services/util/run_adaptive_sampler.hpp>
 #include <stan/services/util/create_rng.hpp>
 #include <stan/services/util/initialize.hpp>
 #include <stan/services/util/inv_metric.hpp>
-#include <iostream>
+#include <stan/services/util/run_adaptive_sampler.hpp>
 #include <vector>
 
 namespace stan {
@@ -26,8 +25,6 @@ namespace sample {
  * stepsize and inverse metric.
  *
  * @tparam Model Model class
- * @tparam Stream A type with with a valid `operator<<(std::string)`
- * @tparam Deleter A class with a valid `operator()` method for deleting the
  * @param[in] model Input model (with data already instantiated)
  * @param[in] init var context for initialization
  * @param[in] init_inv_metric var context exposing an initial dense
@@ -58,8 +55,7 @@ namespace sample {
  * @param[in,out] metric_writer Writer for tuning params
  * @return error_codes::OK if successful
  */
-template <class Model, typename Stream,
-          typename Deleter = std::default_delete<Stream>>
+template <class Model>
 int hmc_nuts_dense_e_adapt(
     Model& model, const stan::io::var_context& init,
     const stan::io::var_context& init_inv_metric, unsigned int random_seed,
@@ -70,7 +66,7 @@ int hmc_nuts_dense_e_adapt(
     unsigned int window, callbacks::interrupt& interrupt,
     callbacks::logger& logger, callbacks::writer& init_writer,
     callbacks::writer& sample_writer, callbacks::writer& diagnostic_writer,
-    callbacks::json_writer<Stream, Deleter>& metric_writer) {
+    callbacks::structured_writer& metric_writer) {
   boost::ecuyer1988 rng = util::create_rng(random_seed, chain);
 
   std::vector<double> cont_vector;
@@ -117,8 +113,6 @@ int hmc_nuts_dense_e_adapt(
  * with a pre-specified dense metric.
  *
  * @tparam Model Model class
- * @tparam Stream A type with with a valid `operator<<(std::string)`
- * @tparam Deleter A class with a valid `operator()` method for deleting the
  * @param[in] model Input model (with data already instantiated)
  * @param[in] init var context for initialization
  * @param[in] init_inv_metric var context exposing an initial dense
@@ -159,7 +153,7 @@ int hmc_nuts_dense_e_adapt(
     unsigned int window, callbacks::interrupt& interrupt,
     callbacks::logger& logger, callbacks::writer& init_writer,
     callbacks::writer& sample_writer, callbacks::writer& diagnostic_writer) {
-  callbacks::json_writer<std::ofstream> dummy_metric_writer;
+  callbacks::structured_writer dummy_metric_writer;
   return hmc_nuts_dense_e_adapt(
       model, init, init_inv_metric, random_seed, chain, init_radius, num_warmup,
       num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter,
@@ -174,8 +168,6 @@ int hmc_nuts_dense_e_adapt(
  * parameters stepsize and inverse metric.
  *
  * @tparam Model Model class
- * @tparam Stream A type with with a valid `operator<<(std::string)`
- * @tparam Deleter A class with a valid `operator()` method for deleting the
  * @param[in] model Input model (with data already instantiated)
  * @param[in] init var context for initialization
  * @param[in] random_seed random seed for the random number generator
@@ -204,8 +196,7 @@ int hmc_nuts_dense_e_adapt(
  * @param[in,out] metric_writer Writer for tuning params
  * @return error_codes::OK if successful
  */
-template <class Model, typename Stream,
-          typename Deleter = std::default_delete<Stream>>
+template <class Model>
 int hmc_nuts_dense_e_adapt(
     Model& model, const stan::io::var_context& init, unsigned int random_seed,
     unsigned int chain, double init_radius, int num_warmup, int num_samples,
@@ -215,7 +206,7 @@ int hmc_nuts_dense_e_adapt(
     unsigned int window, callbacks::interrupt& interrupt,
     callbacks::logger& logger, callbacks::writer& init_writer,
     callbacks::writer& sample_writer, callbacks::writer& diagnostic_writer,
-    callbacks::json_writer<Stream, Deleter>& metric_writer) {
+    callbacks::structured_writer& metric_writer) {
   stan::io::dump dmp
       = util::create_unit_e_dense_inv_metric(model.num_params_r());
   stan::io::var_context& unit_e_metric = dmp;
@@ -272,7 +263,7 @@ int hmc_nuts_dense_e_adapt(
   stan::io::dump dmp
       = util::create_unit_e_dense_inv_metric(model.num_params_r());
   stan::io::var_context& unit_e_metric = dmp;
-  callbacks::json_writer<std::ofstream> dummy_metric_writer;
+  callbacks::structured_writer dummy_metric_writer;
   return hmc_nuts_dense_e_adapt(
       model, init, unit_e_metric, random_seed, chain, init_radius, num_warmup,
       num_samples, num_thin, save_warmup, refresh, stepsize, stepsize_jitter,
@@ -287,15 +278,14 @@ int hmc_nuts_dense_e_adapt(
  * stepsize and inverse metric.
  *
  * @tparam Model Model class
- * @tparam Stream A type with with a valid `operator<<(std::string)`
- * @tparam Deleter A class with a valid `operator()` method for deleting the
  * @tparam InitContextPtr A pointer with underlying type derived from
  `stan::io::var_context`
  * @tparam InitInvContextPtr A pointer with underlying type derived from
  `stan::io::var_context`
+ * @tparam InitWriter A type derived from `stan::callbacks::writer`
  * @tparam SamplerWriter A type derived from `stan::callbacks::writer`
  * @tparam DiagnosticWriter A type derived from `stan::callbacks::writer`
- * @tparam InitWriter A type derived from `stan::callbacks::writer`
+ * @tparam MetricWriter A type derived from `stan::callbacks::structured_writer`
  * @param[in] model Input model (with data already instantiated)
  * @param[in] num_chains The number of chains to run in parallel. `init`,
  * `init_inv_metric`, `init_writer`, `sample_writer`, and `diagnostic_writer`
@@ -337,7 +327,7 @@ int hmc_nuts_dense_e_adapt(
  */
 template <class Model, typename InitContextPtr, typename InitInvContextPtr,
           typename InitWriter, typename SampleWriter, typename DiagnosticWriter,
-          typename Stream, typename Deleter = std::default_delete<Stream>>
+          typename MetricWriter>
 int hmc_nuts_dense_e_adapt(
     Model& model, size_t num_chains, const std::vector<InitContextPtr>& init,
     const std::vector<InitInvContextPtr>& init_inv_metric,
@@ -350,7 +340,7 @@ int hmc_nuts_dense_e_adapt(
     std::vector<InitWriter>& init_writer,
     std::vector<SampleWriter>& sample_writer,
     std::vector<DiagnosticWriter>& diagnostic_writer,
-    std::vector<callbacks::json_writer<Stream, Deleter>>& metric_writer) {
+    std::vector<MetricWriter>& metric_writer) {
   if (num_chains == 1) {
     return hmc_nuts_dense_e_adapt(
         model, *init[0], *init_inv_metric[0], random_seed, init_chain_id,
@@ -471,11 +461,11 @@ int hmc_nuts_dense_e_adapt(
     std::vector<InitWriter>& init_writer,
     std::vector<SampleWriter>& sample_writer,
     std::vector<DiagnosticWriter>& diagnostic_writer) {
-  std::vector<callbacks::json_writer<std::ofstream>> dummy_metric_writer;
+  std::vector<stan::callbacks::structured_writer> dummy_metric_writer;
   dummy_metric_writer.reserve(num_chains);
   for (size_t i = 0; i < num_chains; ++i) {
     dummy_metric_writer.emplace_back(
-        stan::callbacks::json_writer<std::ofstream>());
+        stan::callbacks::structured_writer());
   }
   if (num_chains == 1) {
     return hmc_nuts_dense_e_adapt(
@@ -504,6 +494,7 @@ int hmc_nuts_dense_e_adapt(
  * @tparam InitWriter A type derived from `stan::callbacks::writer`
  * @tparam SamplerWriter A type derived from `stan::callbacks::writer`
  * @tparam DiagnosticWriter A type derived from `stan::callbacks::writer`
+ * @tparam MetricWriter A type derived from `stan::callbacks::structured_writer`
  * @param[in] model Input model (with data already instantiated)
  * @param[in] num_chains The number of chains to run in parallel. `init`,
  * `init_writer`, `sample_writer`, and `diagnostic_writer` must be the same
@@ -541,8 +532,7 @@ int hmc_nuts_dense_e_adapt(
  * @return error_codes::OK if successful
  */
 template <class Model, typename InitContextPtr, typename InitWriter,
-          typename SampleWriter, typename DiagnosticWriter, typename Stream,
-          typename Deleter = std::default_delete<Stream>>
+          typename SampleWriter, typename DiagnosticWriter, typename MetricWriter>
 int hmc_nuts_dense_e_adapt(
     Model& model, size_t num_chains, const std::vector<InitContextPtr>& init,
     unsigned int random_seed, unsigned int init_chain_id, double init_radius,
@@ -554,7 +544,7 @@ int hmc_nuts_dense_e_adapt(
     std::vector<InitWriter>& init_writer,
     std::vector<SampleWriter>& sample_writer,
     std::vector<DiagnosticWriter>& diagnostic_writer,
-    std::vector<callbacks::json_writer<Stream, Deleter>>& metric_writer) {
+    std::vector<MetricWriter>& metric_writer) {
   std::vector<std::unique_ptr<stan::io::dump>> unit_e_metric;
   unit_e_metric.reserve(num_chains);
   for (size_t i = 0; i < num_chains; ++i) {
@@ -641,11 +631,11 @@ int hmc_nuts_dense_e_adapt(
     unit_e_metric.emplace_back(std::make_unique<stan::io::dump>(
         util::create_unit_e_dense_inv_metric(model.num_params_r())));
   }
-  std::vector<callbacks::json_writer<std::ofstream>> dummy_metric_writer;
+  std::vector<callbacks::structured_writer> dummy_metric_writer;
   dummy_metric_writer.reserve(num_chains);
   for (size_t i = 0; i < num_chains; ++i) {
     dummy_metric_writer.emplace_back(
-        stan::callbacks::json_writer<std::ofstream>());
+        stan::callbacks::structured_writer());
   }
   if (num_chains == 1) {
     return hmc_nuts_dense_e_adapt(