Remove deprecated args from base MCSampler

Summary: These have been deprecated since 0.8.0, time to let them go.

Differential Revision: D54280379

botorch/sampling/base.py

@@ -10,9 +10,8 @@
 
 from __future__ import annotations
 
-import warnings
 from abc import ABC, abstractmethod
-from typing import Any, Optional, Tuple
+from typing import Optional, Tuple
 
 import torch
 from botorch.exceptions.errors import InputDataError
@@ -49,45 +48,20 @@ def __init__(
  self,
  sample_shape: torch.Size,
  seed: Optional[int] = None,
- **kwargs: Any,
  ) -> None:
  r"""Abstract base class for samplers.
 
  Args:
  sample_shape: The `sample_shape` of the samples to generate. The full shape
  of the samples is given by `posterior._extended_shape(sample_shape)`.
  seed: An optional seed to use for sampling.
- **kwargs: Catch-all for deprecated kwargs.
  """
  super().__init__()
  if not isinstance(sample_shape, torch.Size):
- if isinstance(sample_shape, int):
- sample_shape = torch.Size([sample_shape])
- warnings.warn(
- "The first positional argument of samplers, `num_samples`, has "
- "been deprecated and replaced with `sample_shape`, which expects "
- "a `torch.Size` object.",
- DeprecationWarning,
- )
- else:
- raise InputDataError(
- "Expected `sample_shape` to be a `torch.Size` object, "
- f"got {sample_shape}."
- )
- for k, v in kwargs.items():
- if k == "resample":
- if v is True:
- raise RuntimeError(KWARG_ERR_MSG.format(k, "StochasticSampler"))
- else:
- warnings.warn(KWARGS_DEPRECATED_MSG.format(k), DeprecationWarning)
- elif k == "collapse_batch_dims":
- if v is False:
- raise RuntimeError(KWARG_ERR_MSG.format(k, "ForkedRNGSampler"))
- else:
- warnings.warn(KWARGS_DEPRECATED_MSG.format(k), DeprecationWarning)
- else:
- raise RuntimeError(f"Recevied an unknown argument {k}: {v}.")
-
+ raise InputDataError(
+ "Expected `sample_shape` to be a `torch.Size` object, "
+ f"got {sample_shape}."
+ )
  self.sample_shape = sample_shape
  self.seed = seed if seed is not None else torch.randint(0, 1000000, (1,)).item()
  self.register_buffer("base_samples", None)

test/sampling/test_base.py

@@ -36,21 +36,9 @@ def test_init(self):
  # Default seed.
  sampler = NonAbstractSampler(sample_shape=torch.Size([4]))
  self.assertIsInstance(sampler.seed, int)
- # Deprecated args & error handling.
- with self.assertWarnsRegex(DeprecationWarning, "positional argument"):
- NonAbstractSampler(4)
+ # Error handling.
  with self.assertRaisesRegex(InputDataError, "sample_shape"):
  NonAbstractSampler(4.5)
- with self.assertWarnsRegex(DeprecationWarning, "resample"):
- NonAbstractSampler(sample_shape=torch.Size([4]), resample=False)
- with self.assertRaisesRegex(RuntimeError, "StochasticSampler"):
- NonAbstractSampler(sample_shape=torch.Size([4]), resample=True)
- with self.assertWarnsRegex(DeprecationWarning, "collapse_batch"):
- NonAbstractSampler(sample_shape=torch.Size([4]), collapse_batch_dims=True)
- with self.assertRaisesRegex(RuntimeError, "ForkedRNGSampler"):
- NonAbstractSampler(sample_shape=torch.Size([4]), collapse_batch_dims=False)
- with self.assertRaisesRegex(RuntimeError, "unknown argument"):
- NonAbstractSampler(sample_shape=torch.Size([4]), dummy_arg=True)
 
  def test_batch_range(self):
  posterior = MockPosterior()