Typos fixes. (#3030)

Summary:
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## Motivation

I optimized the "optimziation"s.
### Have you read the [Contributing Guidelines on pull requests](https://github.com/meta-pytorch/botorch/blob/main/CONTRIBUTING.md#pull-requests)?

Yes

Pull Request resolved: #3030

Test Plan:
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## Related PRs

(If this PR adds or changes functionality, please take some time to update the docs at https://github.com/meta-pytorch/botorch, and link to your PR here.)

Reviewed By: esantorella, SebastianAment

Differential Revision: D83569812

Pulled By: Balandat

fbshipit-source-id: b1047cff9a06c3de8a392d6b27881d15570544c3

Author: kedikutusu

botorch/optim/initializers.py

@@ -255,7 +255,7 @@ def gen_batch_initial_conditions(
     generator: Callable[[int, int, int | None], Tensor] | None = None,
     fixed_X_fantasies: Tensor | None = None,
 ) -> Tensor:
-    r"""Generate a batch of initial conditions for random-restart optimziation.
+    r"""Generate a batch of initial conditions for random-restart optimization.
 
     TODO: Support t-batches of initial conditions.
 

botorch/optim/parameter_constraints.py

@@ -51,7 +51,7 @@ def make_scipy_bounds(
     lower_bounds: float | Tensor | None = None,
     upper_bounds: float | Tensor | None = None,
 ) -> Bounds | None:
-    r"""Creates a scipy Bounds object for optimziation
+    r"""Creates a scipy Bounds object for optimization
 
     Args:
         X: `... x d` tensor

botorch/optim/utils/timeout.py

@@ -36,7 +36,7 @@ def minimize_with_timeout(
 
     This method calls scipy.optimize.minimize with all arguments forwarded
     verbatim. The only difference is that if provided a `timeout_sec` argument,
-    it will automatically stop the optimziation after the timeout is reached.
+    it will automatically stop the optimization after the timeout is reached.
 
     Internally, this is achieved by automatically constructing a wrapper callback
     method that is injected to the scipy.optimize.minimize call and that keeps