diff --git a/pymc3/sampling.py b/pymc3/sampling.py
index c595655e51..31931d167b 100644
--- a/pymc3/sampling.py
+++ b/pymc3/sampling.py
@@ -252,9 +252,9 @@ def sample(
draws=1000,
step=None,
init="auto",
- n_init=200000,
+ n_init=200_000,
start=None,
- trace=None,
+ trace: Optional[Union[BaseTrace, List[str]]] = None,
chain_idx=0,
chains=None,
cores=None,
@@ -296,10 +296,9 @@ def sample(
Defaults to ``trace.point(-1))`` if there is a trace provided and model.initial_point if not
(defaults to empty dict). Initialization methods for NUTS (see ``init`` keyword) can
overwrite the default.
- trace : backend, list, or MultiTrace
- This should be a backend instance, a list of variables to track, or a MultiTrace object
- with past values. If a MultiTrace object is given, it must contain samples for the chain
- number ``chain``. If None or a list of variables, the NDArray backend is used.
+ trace : backend or list
+ This should be a backend instance, or a list of variables to track.
+ If None or a list of variables, the NDArray backend is used.
chain_idx : int
Chain number used to store sample in backend. If ``chains`` is greater than one, chain
numbers will start here.
@@ -813,7 +812,7 @@ def _sample(
start,
draws: int,
step=None,
- trace=None,
+ trace: Optional[Union[BaseTrace, List[str]]] = None,
tune=None,
model: Optional[Model] = None,
callback=None,
@@ -839,10 +838,9 @@ def _sample(
The number of samples to draw
step : function
Step function
- trace : backend, list, or MultiTrace
- This should be a backend instance, a list of variables to track, or a MultiTrace object
- with past values. If a MultiTrace object is given, it must contain samples for the chain
- number ``chain``. If None or a list of variables, the NDArray backend is used.
+ trace : backend or list
+ This should be a backend instance, or a list of variables to track.
+ If None or a list of variables, the NDArray backend is used.
tune : int, optional
Number of iterations to tune, if applicable (defaults to None)
model : Model (optional if in ``with`` context)
@@ -899,10 +897,9 @@ def iter_sample(
start : dict
Starting point in parameter space (or partial point). Defaults to trace.point(-1)) if
there is a trace provided and model.initial_point if not (defaults to empty dict)
- trace : backend, list, or MultiTrace
- This should be a backend instance, a list of variables to track, or a MultiTrace object
- with past values. If a MultiTrace object is given, it must contain samples for the chain
- number ``chain``. If None or a list of variables, the NDArray backend is used.
+ trace : backend or list
+ This should be a backend instance, or a list of variables to track.
+ If None or a list of variables, the NDArray backend is used.
chain : int, optional
Chain number used to store sample in backend. If ``cores`` is greater than one, chain numbers
will start here.
@@ -939,7 +936,7 @@ def _iter_sample(
draws,
step,
start=None,
- trace=None,
+ trace: Optional[Union[BaseTrace, List[str]]] = None,
chain=0,
tune=None,
model=None,
@@ -955,12 +952,10 @@ def _iter_sample(
step : function
Step function
start : dict, optional
- Starting point in parameter space (or partial point). Defaults to trace.point(-1)) if
- there is a trace provided and model.initial_point if not (defaults to empty dict)
- trace : backend, list, MultiTrace, or None
- This should be a backend instance, a list of variables to track, or a MultiTrace object
- with past values. If a MultiTrace object is given, it must contain samples for the chain
- number ``chain``. If None or a list of variables, the NDArray backend is used.
+ Starting point in parameter space (or partial point). Defaults to model.initial_point if not (defaults to empty dict)
+ trace : backend or list
+ This should be a backend instance, or a list of variables to track.
+ If None or a list of variables, the NDArray backend is used.
chain : int, optional
Chain number used to store sample in backend. If ``cores`` is greater than one, chain numbers
will start here.
@@ -986,12 +981,9 @@ def _iter_sample(
if start is None:
start = {}
- strace = _choose_backend(trace, chain, model=model)
+ strace = _choose_backend(trace, model=model)
- if len(strace) > 0:
- model.update_start_vals(start, strace.point(-1))
- else:
- model.update_start_vals(start, model.initial_point)
+ model.update_start_vals(start, model.initial_point)
try:
step = CompoundStep(step)
@@ -1258,7 +1250,7 @@ def _prepare_iter_population(
# 5. a PopulationStepper is configured for parallelized stepping
# 1. prepare a BaseTrace for each chain
- traces = [_choose_backend(None, chain, model=model) for chain in chains]
+ traces = [_choose_backend(None, model=model) for chain in chains]
for c, strace in enumerate(traces):
# initialize the trace size and variable transforms
if len(strace) > 0:
@@ -1361,30 +1353,29 @@ def _iter_population(draws, tune, popstep, steppers, traces, points):
steppers[c].report._finalize(strace)
-def _choose_backend(trace, chain, **kwds) -> Backend:
+def _choose_backend(trace: Optional[Union[BaseTrace, List[str]]], **kwds) -> Backend:
"""Selects or creates a NDArray trace backend for a particular chain.
Parameters
----------
- trace : BaseTrace, list, MultiTrace, or None
- This should be a BaseTrace, list of variables to track,
- or a MultiTrace object with past values.
- If a MultiTrace object is given, it must contain samples for the chain number ``chain``.
+ trace : BaseTrace, list, or None
+ This should be a BaseTrace, or list of variables to track.
If None or a list of variables, the NDArray backend is used.
- chain : int
- Number of the chain of interest.
**kwds :
keyword arguments to forward to the backend creation
Returns
-------
trace : BaseTrace
- A trace object for the selected chain
+ The incoming, or a brand new trace object.
"""
+ if isinstance(trace, BaseTrace) and len(trace) > 0:
+ raise ValueError("Continuation of traces is no longer supported.")
+ if isinstance(trace, MultiTrace):
+ raise ValueError("Starting from existing MultiTrace objects is no longer supported.")
+
if isinstance(trace, BaseTrace):
return trace
- if isinstance(trace, MultiTrace):
- return trace._straces[chain]
if trace is None:
return NDArray(**kwds)
@@ -1401,7 +1392,7 @@ def _mp_sample(
random_seed: list,
start: list,
progressbar=True,
- trace=None,
+ trace: Optional[Union[BaseTrace, List[str]]] = None,
model=None,
callback=None,
discard_tuned_samples=True,
@@ -1430,10 +1421,9 @@ def _mp_sample(
Starting points for each chain.
progressbar : bool
Whether or not to display a progress bar in the command line.
- trace : BaseTrace, list, MultiTrace or None
- This should be a backend instance, a list of variables to track, or a MultiTrace object
- with past values. If a MultiTrace object is given, it must contain samples for the chain
- number ``chain``. If None or a list of variables, the NDArray backend is used.
+ trace : BaseTrace, list, or None
+ This should be a backend instance, or a list of variables to track
+ If None or a list of variables, the NDArray backend is used.
model : Model (optional if in ``with`` context)
callback : Callable
A function which gets called for every sample from the trace of a chain. The function is
@@ -1455,10 +1445,10 @@ def _mp_sample(
traces = []
for idx in range(chain, chain + chains):
if trace is not None:
- strace = _choose_backend(copy(trace), idx, model=model)
+ strace = _choose_backend(copy(trace), model=model)
else:
- strace = _choose_backend(None, idx, model=model)
- # for user supply start value, fill-in missing value if the supplied
+ strace = _choose_backend(None, model=model)
+ # for user supplied start value, fill-in missing value if the supplied
# dict does not contain all parameters
model.update_start_vals(start[idx - chain], model.initial_point)
if step.generates_stats and strace.supports_sampler_stats:
diff --git a/pymc3/tests/test_examples.py b/pymc3/tests/test_examples.py
index f44add09ee..256def0857 100644
--- a/pymc3/tests/test_examples.py
+++ b/pymc3/tests/test_examples.py
@@ -350,6 +350,9 @@ def build_models(self):
return model, coarse_models
+ @pytest.mark.skip(
+ reason="MLDA needs to be refactored to no longer depend on trace continuation. See #5021."
+ )
def test_run(self):
model, coarse_models = self.build_models()
diff --git a/pymc3/tests/test_sampling.py b/pymc3/tests/test_sampling.py
index 04767ae9b6..f6aa77aaef 100644
--- a/pymc3/tests/test_sampling.py
+++ b/pymc3/tests/test_sampling.py
@@ -32,6 +32,7 @@
import pymc3 as pm
from pymc3.aesaraf import compile_rv_inplace
+from pymc3.backends.base import MultiTrace
from pymc3.backends.ndarray import NDArray
from pymc3.exceptions import IncorrectArgumentsError, SamplingError
from pymc3.tests.helpers import SeededTest
@@ -438,14 +439,30 @@ def test_constant_named(self):
class TestChooseBackend:
def test_choose_backend_none(self):
with mock.patch("pymc3.sampling.NDArray") as nd:
- pm.sampling._choose_backend(None, "chain")
+ pm.sampling._choose_backend(None)
assert nd.called
def test_choose_backend_list_of_variables(self):
with mock.patch("pymc3.sampling.NDArray") as nd:
- pm.sampling._choose_backend(["var1", "var2"], "chain")
+ pm.sampling._choose_backend(["var1", "var2"])
nd.assert_called_with(vars=["var1", "var2"])
+ def test_errors_and_warnings(self):
+ with pm.Model():
+ A = pm.Normal("A")
+ B = pm.Uniform("B")
+ strace = pm.sampling.NDArray(vars=[A, B])
+ strace.setup(10, 0)
+
+ with pytest.raises(ValueError, match="from existing MultiTrace"):
+ pm.sampling._choose_backend(trace=MultiTrace([strace]))
+
+ strace.record({"A": 2, "B_interval__": 0.1})
+ assert len(strace) == 1
+ with pytest.raises(ValueError, match="Continuation of traces"):
+ pm.sampling._choose_backend(trace=strace)
+ pass
+
class TestSamplePPC(SeededTest):
def test_normal_scalar(self):
diff --git a/pymc3/tests/test_step.py b/pymc3/tests/test_step.py
index 1d79491536..bcd3fee9d5 100644
--- a/pymc3/tests/test_step.py
+++ b/pymc3/tests/test_step.py
@@ -579,11 +579,12 @@ def test_step_continuous(self):
HamiltonianMC(scaling=C, is_cov=True, blocked=False),
]
),
- MLDA(
- coarse_models=[model_coarse],
- base_S=C,
- base_proposal_dist=MultivariateNormalProposal,
- ),
+ # NOTE: The MLDA uses the trace continuation which was removed.
+ # MLDA(
+ # coarse_models=[model_coarse],
+ # base_S=C,
+ # base_proposal_dist=MultivariateNormalProposal,
+ # ),
)
for step in steps:
idata = sample(
@@ -1038,6 +1039,9 @@ def test_sampler_stats(self):
assert (trace.model_logp == model_logp_).all()
+@pytest.mark.skip(
+ reason="MLDA needs to be refactored to no longer depend on trace continuation. See #5021."
+)
class TestMLDA:
steppers = [MLDA]