Remove FixedNoiseDataset (pytorch#2626)

Summary:

This was deprecated and marked for removal in v0.11.

Reviewed By: esantorella

Differential Revision: D66003588

botorch/utils/datasets.py

@@ -8,7 +8,6 @@
 
 from __future__ import annotations
 
-import warnings
 from typing import Any
 
 import torch
@@ -149,39 +148,6 @@ def __eq__(self, other: Any) -> bool:
         )
 
 
-class FixedNoiseDataset(SupervisedDataset):
-    r"""A SupervisedDataset with an additional field `Yvar` that stipulates
-    observations variances so that `Y[i] ~ N(f(X[i]), Yvar[i])`.
-
-    NOTE: This is deprecated. Use `SupervisedDataset` instead.
-    Will be removed in a future release (~v0.11).
-    """
-
-    def __init__(
-        self,
-        X: BotorchContainer | Tensor,
-        Y: BotorchContainer | Tensor,
-        Yvar: BotorchContainer | Tensor,
-        feature_names: list[str],
-        outcome_names: list[str],
-        validate_init: bool = True,
-    ) -> None:
-        r"""Initialize a `FixedNoiseDataset` -- deprecated!"""
-        warnings.warn(
-            "`FixedNoiseDataset` is deprecated. Use `SupervisedDataset` instead.",
-            DeprecationWarning,
-            stacklevel=2,
-        )
-        super().__init__(
-            X=X,
-            Y=Y,
-            feature_names=feature_names,
-            outcome_names=outcome_names,
-            Yvar=Yvar,
-            validate_init=validate_init,
-        )
-
-
 class RankingDataset(SupervisedDataset):
     r"""A SupervisedDataset whose labelled pairs `(x, y)` consist of m-ary combinations
     `x ∈ Z^{m}` of elements from a ground set `Z = (z_1, ...)` and ranking vectors

test/utils/test_datasets.py

@@ -10,7 +10,6 @@
 from botorch.utils.containers import DenseContainer, SliceContainer
 from botorch.utils.datasets import (
     ContextualDataset,
-    FixedNoiseDataset,
     MultiTaskDataset,
     RankingDataset,
     SupervisedDataset,
@@ -129,7 +128,7 @@ def test_fixedNoise(self):
         Yvar = rand(3, 1)
         feature_names = ["x1", "x2"]
         outcome_names = ["y"]
-        dataset = FixedNoiseDataset(
+        dataset = SupervisedDataset(
             X=X,
             Y=Y,
             Yvar=Yvar,
@@ -142,17 +141,6 @@ def test_fixedNoise(self):
         self.assertEqual(dataset.feature_names, feature_names)
         self.assertEqual(dataset.outcome_names, outcome_names)
 
-        with self.assertRaisesRegex(
-            ValueError, "`Y` and `Yvar`"
-        ), self.assertWarnsRegex(DeprecationWarning, "SupervisedDataset"):
-            FixedNoiseDataset(
-                X=X,
-                Y=Y,
-                Yvar=Yvar.squeeze(),
-                feature_names=feature_names,
-                outcome_names=outcome_names,
-            )
-
     def test_ranking(self):
         # Test `_validate`
         X_val = rand(16, 2)