Require explicit kwargs in internal sampling functions

Author: michaelosthege

pymc/sampling/mcmc.py

@@ -21,7 +21,6 @@
 import warnings
 
 from collections import defaultdict
-from copy import copy
 from typing import Iterator, List, Optional, Sequence, Tuple, Union
 
 import numpy as np
@@ -654,6 +653,7 @@ def _check_start_shape(model, start: PointType):
 
 
 def _sample_many(
+    *,
     draws: int,
     chains: int,
     start: Sequence[PointType],
@@ -754,10 +754,16 @@ def _sample(
     """
     skip_first = kwargs.get("skip_first", 0)
 
-    trace = copy(trace)
-
     sampling_gen = _iter_sample(
-        draws, step, start, trace, chain, tune, model, random_seed, callback
+        draws=draws,
+        step=step,
+        start=start,
+        trace=trace,
+        chain=chain,
+        tune=tune,
+        model=model,
+        random_seed=random_seed,
+        callback=callback,
     )
     _pbar_data = {"chain": chain, "divergences": 0}
     _desc = "Sampling chain {chain:d}, {divergences:,d} divergences"
@@ -832,12 +838,23 @@ def iter_sample(
         for trace in iter_sample(500, step):
             ...
     """
-    sampling = _iter_sample(draws, step, start, trace, chain, tune, model, random_seed, callback)
+    sampling = _iter_sample(
+        draws=draws,
+        step=step,
+        start=start,
+        trace=trace,
+        chain=chain,
+        tune=tune,
+        model=model,
+        random_seed=random_seed,
+        callback=callback,
+    )
     for i, (strace, _) in enumerate(sampling):
         yield MultiTrace([strace[: i + 1]])
 
 
 def _iter_sample(
+    *,
     draws: int,
     step,
     start: PointType,
@@ -934,6 +951,7 @@ def _iter_sample(
 
 
 def _mp_sample(
+    *,
     draws: int,
     tune: int,
     step,

pymc/sampling/population.py

@@ -48,6 +48,7 @@
 
 
 def _sample_population(
+    *,
     draws: int,
     chains: int,
     start: Sequence[PointType],
@@ -86,10 +87,10 @@ def _sample_population(
         Contains samples of all chains
     """
     sampling = _prepare_iter_population(
-        draws,
-        step,
-        start,
-        parallelize,
+        draws=draws,
+        step=step,
+        start=start,
+        parallelize=parallelize,
         tune=tune,
         model=model,
         random_seed=random_seed,
@@ -259,6 +260,7 @@ def step(self, tune_stop: bool, population) -> List[Tuple[PointType, StatsType]]
 
 
 def _prepare_iter_population(
+    *,
     draws: int,
     step,
     start: Sequence[PointType],
@@ -344,11 +346,19 @@ def _prepare_iter_population(
 
     # Because the preparations above are expensive, the actual iterator is
     # in another method. This way the progbar will not be disturbed.
-    return _iter_population(draws, tune, popstep, steppers, traces, population)
+    return _iter_population(
+        draws=draws, tune=tune, popstep=popstep, steppers=steppers, traces=traces, points=population
+    )
 
 
 def _iter_population(
-    draws: int, tune: int, popstep: PopulationStepper, steppers, traces: Sequence[BaseTrace], points
+    *,
+    draws: int,
+    tune: int,
+    popstep: PopulationStepper,
+    steppers,
+    traces: Sequence[BaseTrace],
+    points,
 ) -> Iterator[Sequence[BaseTrace]]:
     """Iterate a ``PopulationStepper``.