Reap deprecated mvn argument to GPyTorchPosterior (#2255)

Summary:

All internal calls to this have been updated to use `distribution` instead, including in subclasses (`HigherOrderGPPosterior`, `GaussianMixturePosterior`, `MultiTaskGPPosterior`, `FullyBayesianPosterior`)

Differential Revision: D55092855

Author: esantorella

botorch/posteriors/gpytorch.py

@@ -10,8 +10,6 @@
 
 from __future__ import annotations
 
-import warnings
-
 from contextlib import ExitStack
 from typing import Optional, Tuple, TYPE_CHECKING, Union
 
@@ -39,32 +37,13 @@ class GPyTorchPosterior(TorchPosterior):
 
     distribution: MultivariateNormal
 
-    def __init__(
-        self,
-        distribution: Optional[MultivariateNormal] = None,
-        mvn: Optional[MultivariateNormal] = None,
-    ) -> None:
+    def __init__(self, distribution: MultivariateNormal) -> None:
         r"""A posterior based on GPyTorch's multi-variate Normal distributions.
 
         Args:
             distribution: A GPyTorch MultivariateNormal (single-output case) or
                 MultitaskMultivariateNormal (multi-output case).
-            mvn: Deprecated.
         """
-        if mvn is not None:
-            if distribution is not None:
-                raise RuntimeError(
-                    "Got both a `distribution` and an `mvn` argument. "
-                    "Use the `distribution` only."
-                )
-            warnings.warn(
-                "The `mvn` argument of `GPyTorchPosterior`s has been renamed to "
-                "`distribution` and will be removed in a future version.",
-                DeprecationWarning,
-            )
-            distribution = mvn
-        if distribution is None:
-            raise RuntimeError("GPyTorchPosterior must have a distribution specified.")
         super().__init__(distribution=distribution)
         self._is_mt = isinstance(distribution, MultitaskMultivariateNormal)
 

test/posteriors/test_gpytorch.py

@@ -12,7 +12,7 @@
 import torch
 from botorch.exceptions import BotorchTensorDimensionError
 from botorch.posteriors.gpytorch import GPyTorchPosterior, scalarize_posterior
-from botorch.utils.testing import _get_test_posterior, BotorchTestCase, MockPosterior
+from botorch.utils.testing import _get_test_posterior, BotorchTestCase
 from gpytorch import settings as gpt_settings
 from gpytorch.distributions import MultitaskMultivariateNormal, MultivariateNormal
 from linear_operator.operators import to_linear_operator
@@ -25,18 +25,7 @@
 
 
 class TestGPyTorchPosterior(BotorchTestCase):
-    def test_GPyTorchPosterior(self):
-        # Test init & mvn property.
-        mock_mvn = MockPosterior()
-        with self.assertWarnsRegex(DeprecationWarning, "The `mvn` argument of"):
-            posterior = GPyTorchPosterior(mvn=mock_mvn)
-        self.assertIs(posterior.mvn, mock_mvn)
-        self.assertIs(posterior.distribution, mock_mvn)
-        with self.assertRaisesRegex(RuntimeError, "Got both a `distribution`"):
-            GPyTorchPosterior(mvn=mock_mvn, distribution=mock_mvn)
-        with self.assertRaisesRegex(RuntimeError, "GPyTorchPosterior must have"):
-            GPyTorchPosterior()
-
+    def test_GPyTorchPosterior(self) -> None:
         for dtype in (torch.float, torch.double):
             n = 3
             mean = torch.rand(n, dtype=dtype, device=self.device)