Include n_tune, n_draws and t_sampling in SamplerReport

pymc3/backends/report.py

@@ -15,6 +15,7 @@
 from collections import namedtuple
 import logging
 import enum
+import typing
 from ..util import is_transformed_name, get_untransformed_name
 
 
@@ -51,11 +52,15 @@ class WarningType(enum.Enum):
 
 
 class SamplerReport:
+    """This object bundles warnings, convergence statistics and metadata of a sampling run."""
     def __init__(self):
         self._chain_warnings = {}
         self._global_warnings = []
         self._ess = None
         self._rhat = None
+        self._n_tune = None
+        self._n_draws = None
+        self._t_sampling = None
 
     @property
     def _warnings(self):
@@ -68,6 +73,25 @@ def ok(self):
         return all(_LEVELS[warn.level] < _LEVELS['warn']
                    for warn in self._warnings)
 
+    @property
+    def n_tune(self) -> typing.Optional[int]:
+        """Number of tune iterations."""
+        return self._n_tune
+
+    @property
+    def n_draws(self) -> typing.Optional[int]:
+        """Number of draw iterations."""
+        return self._n_draws
+
+    @property
+    def t_sampling(self) -> typing.Optional[float]:
+        """
+        Number of seconds that the sampling procedure took.
+
+        (Includes parallelization overhead.)
+        """
+        return self._t_sampling
+
     def raise_ok(self, level='error'):
         errors = [warn for warn in self._warnings
                   if _LEVELS[warn.level] >= _LEVELS[level]]
@@ -151,7 +175,8 @@ def _add_warnings(self, warnings, chain=None):
         warn_list.extend(warnings)
 
     def _log_summary(self):
-
+        if self._n_tune is not None and self._n_draws is not None and self._t_sampling is not None:
+            logger.info(f'Sampling {self.n_tune} tune and {self.n_draws} draw iterations took {self.t_sampling:.0f} seconds.')
         def log_warning(warn):
             level = _LEVELS[warn.level]
             logger.log(level, warn.message)

pymc3/sampling.py

@@ -24,6 +24,7 @@
 from copy import copy
 import pickle
 import logging
+import time
 import warnings
 
 import numpy as np
@@ -486,6 +487,7 @@ def sample(
     )
 
     parallel = cores > 1 and chains > 1 and not has_population_samplers
+    t_start = time.time()
     if parallel:
         _log.info("Multiprocess sampling ({} chains in {} jobs)".format(chains, cores))
         _print_step_hierarchy(step)
@@ -533,6 +535,9 @@ def sample(
 
     discard = tune if discard_tuned_samples else 0
     trace = trace[discard:]
+    trace.report._n_tune = tune
+    trace.report._n_draws = draws
+    trace.report._t_sampling = time.time() - t_start
 
     if compute_convergence_checks:
         if draws - tune < 100: