Remove deprecated Distribution kwargs

pymc/distributions/distribution.py

@@ -97,19 +97,6 @@ class DistributionMeta(ABCMeta):
     """
 
     def __new__(cls, name, bases, clsdict):
-        # Forcefully deprecate old v3 `Distribution`s
-        if "random" in clsdict:
-
-            def _random(*args, **kwargs):
-                warnings.warn(
-                    "The old `Distribution.random` interface is deprecated.",
-                    FutureWarning,
-                    stacklevel=2,
-                )
-                return clsdict["random"](*args, **kwargs)
-
-            clsdict["random"] = _random
-
         rv_op = clsdict.setdefault("rv_op", None)
         rv_type = clsdict.setdefault("rv_type", None)
 
@@ -206,13 +193,6 @@ def support_point(op, rv, *dist_params):
         return new_cls
 
 
-def _make_nice_attr_error(oldcode: str, newcode: str):
-    def fn(*args, **kwargs):
-        raise AttributeError(f"The `{oldcode}` method was removed. Instead use `{newcode}`.`")
-
-    return fn
-
-
 class _class_or_instancemethod(classmethod):
     """Allow a method to be called both as a classmethod and an instancemethod,
     giving priority to the instancemethod.
@@ -510,14 +490,6 @@ def __new__(
                 "for a standalone distribution."
             )
 
-        if "testval" in kwargs:
-            initval = kwargs.pop("testval")
-            warnings.warn(
-                "The `testval` argument is deprecated; use `initval`.",
-                FutureWarning,
-                stacklevel=2,
-            )
-
         if not isinstance(name, string_types):
             raise TypeError(f"Name needs to be a string but got: {name}")
 
@@ -551,10 +523,6 @@ def __new__(
         rv_out._repr_latex_ = types.MethodType(
             functools.partial(str_for_dist, formatting="latex"), rv_out
         )
-
-        rv_out.logp = _make_nice_attr_error("rv.logp(x)", "pm.logp(rv, x)")
-        rv_out.logcdf = _make_nice_attr_error("rv.logcdf(x)", "pm.logcdf(rv, x)")
-        rv_out.random = _make_nice_attr_error("rv.random()", "pm.draw(rv)")
         return rv_out
 
     @classmethod
@@ -582,15 +550,6 @@ def dist(
         rv : TensorVariable
             The created random variable tensor.
         """
-        if "testval" in kwargs:
-            kwargs.pop("testval")
-            warnings.warn(
-                "The `.dist(testval=...)` argument is deprecated and has no effect. "
-                "Initial values for sampling/optimization can be specified with `initval` in a modelcontext. "
-                "For using PyTensor's test value features, you must assign the `.tag.test_value` yourself.",
-                FutureWarning,
-                stacklevel=2,
-            )
         if "initval" in kwargs:
             raise TypeError(
                 "Unexpected keyword argument `initval`. "
@@ -617,9 +576,6 @@ def dist(
         create_size = find_size(shape=shape, size=size, ndim_supp=ndim_supp)
         rv_out = cls.rv_op(*dist_params, size=create_size, **kwargs)
 
-        rv_out.logp = _make_nice_attr_error("rv.logp(x)", "pm.logp(rv, x)")
-        rv_out.logcdf = _make_nice_attr_error("rv.logcdf(x)", "pm.logcdf(rv, x)")
-        rv_out.random = _make_nice_attr_error("rv.random()", "pm.draw(rv)")
         _add_future_warning_tag(rv_out)
         return rv_out
 

tests/distributions/test_distribution.py

@@ -84,31 +84,6 @@ def test_issue_4499(self):
         npt.assert_almost_equal(m.compile_logp()({"x": np.ones(10)}), 0 * 10)
 
 
-@pytest.mark.parametrize(
-    "method,newcode",
-    [
-        ("logp", r"pm.logp\(rv, x\)"),
-        ("logcdf", r"pm.logcdf\(rv, x\)"),
-        ("random", r"pm.draw\(rv\)"),
-    ],
-)
-def test_logp_gives_migration_instructions(method, newcode):
-    rv = pm.Normal.dist()
-    f = getattr(rv, method)
-    with pytest.raises(AttributeError, match=rf"use `{newcode}`"):
-        f()
-
-    # A dim-induced resize of the rv created by the `.dist()` API,
-    # happening in Distribution.__new__ would make us loose the monkeypatches.
-    # So this triggers it to test if the monkeypatch still works.
-    with pm.Model(coords={"year": [2019, 2021, 2022]}):
-        rv = pm.Normal("n", dims="year")
-        f = getattr(rv, method)
-        with pytest.raises(AttributeError, match=rf"use `{newcode}`"):
-            f()
-    pass
-
-
 def test_all_distributions_have_support_points():
     import pymc.distributions as dist_module
 

tests/model/test_core.py

@@ -660,8 +660,8 @@ def test_initial_point():
 
     b_initval = np.array(0.3, dtype=pytensor.config.floatX)
 
-    with pytest.warns(FutureWarning), model:
-        b = pm.Uniform("b", testval=b_initval)
+    with model:
+        b = pm.Uniform("b", initval=b_initval)
 
     b_initval_trans = model.rvs_to_transforms[b].forward(b_initval, *b.owner.inputs).eval()
 

tests/test_initial_point.py

@@ -13,7 +13,6 @@
 #   limitations under the License.
 import cloudpickle
 import numpy as np
-import numpy.testing as npt
 import pytensor
 import pytensor.tensor as pt
 import pytest
@@ -34,34 +33,6 @@ def transform_back(rv, transformed, model) -> np.ndarray:
     return model.rvs_to_transforms[rv].backward(transformed, *rv.owner.inputs).eval()
 
 
-class TestInitvalAssignment:
-    def test_dist_warnings_and_errors(self):
-        with pytest.warns(FutureWarning, match="argument is deprecated and has no effect"):
-            rv = pm.Exponential.dist(lam=1, testval=0.5)
-        assert not hasattr(rv.tag, "test_value")
-
-        with pytest.raises(TypeError, match="Unexpected keyword argument `initval`."):
-            pm.Normal.dist(1, 2, initval=None)
-        pass
-
-    def test_new_warnings(self):
-        with pm.Model() as pmodel:
-            with pytest.warns(FutureWarning, match="`testval` argument is deprecated"):
-                rv = pm.Uniform("u", 0, 1, testval=0.75)
-                initial_point = pmodel.initial_point(random_seed=0)
-                npt.assert_allclose(
-                    initial_point["u_interval__"], transform_fwd(rv, 0.75, model=pmodel)
-                )
-                assert not hasattr(rv.tag, "test_value")
-        pass
-
-    def test_valid_string_strategy(self):
-        with pm.Model() as pmodel:
-            pm.Uniform("x", 0, 1, size=2, initval="unknown")
-            with pytest.raises(ValueError, match="Invalid string strategy: unknown"):
-                pmodel.initial_point(random_seed=0)
-
-
 class TestInitvalEvaluation:
     def test_make_initial_point_fns_per_chain_checks_kwargs(self):
         with pm.Model() as pmodel: