From b9c6dbd19d78ff4b6155d6595f3deddffede4c67 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Sat, 3 Aug 2024 08:14:33 +0000
Subject: [PATCH] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 docs/user_guide/neuroevolution.md              |  3 +--
 src/evotorch/algorithms/functional/__init__.py |  3 +--
 src/evotorch/core.py                           |  8 ++++----
 src/evotorch/decorators.py                     | 18 ++++++------------
 src/evotorch/distributions.py                  |  3 +--
 5 files changed, 13 insertions(+), 22 deletions(-)

diff --git a/docs/user_guide/neuroevolution.md b/docs/user_guide/neuroevolution.md
index 60aa86a9..d0c36203 100644
--- a/docs/user_guide/neuroevolution.md
+++ b/docs/user_guide/neuroevolution.md
@@ -293,8 +293,7 @@ class CustomNE(NEProblem):
     def _network_constants(self):
         return {"d": self._d}  # Pass self._d as 'd' to networks at instantiation
 
-    def _evaluate_network(self, network: torch.nn.Module):
-        ...
+    def _evaluate_network(self, network: torch.nn.Module): ...
 ```
 
 which then allows, for example, the use of the variable `d` in the string representation of the network
diff --git a/src/evotorch/algorithms/functional/__init__.py b/src/evotorch/algorithms/functional/__init__.py
index 25ab4683..71723e24 100644
--- a/src/evotorch/algorithms/functional/__init__.py
+++ b/src/evotorch/algorithms/functional/__init__.py
@@ -256,8 +256,7 @@ def f(x: torch.Tensor) -> torch.Tensor:
 
 
 class MyProblem(Problem):
-    def __init__(self):
-        ...
+    def __init__(self): ...
 
     def _evaluate_batch(self, batch: SolutionBatch):
         # Stateful batch evaluation code goes here
diff --git a/src/evotorch/core.py b/src/evotorch/core.py
index f44d0efc..e2b4324f 100644
--- a/src/evotorch/core.py
+++ b/src/evotorch/core.py
@@ -610,8 +610,9 @@ def __init__(self):
                 # for initializing solutions
             )
 
-        def _evaluate_batch(self, solutions: SolutionBatch):
-            ...  # code to compute and fill the fitnesses goes here
+        def _evaluate_batch(
+            self, solutions: SolutionBatch
+        ): ...  # code to compute and fill the fitnesses goes here
 
         def _fill(self, values: torch.Tensor):
             # `values` is an empty tensor of shape (n, m) where n is the number
@@ -749,8 +750,7 @@ def _evaluate_batch(self, solutions: SolutionBatch):
     from evotorch.logging import StdOutLogger
 
 
-    def f(x: torch.Tensor) -> torch.Tensor:
-        ...
+    def f(x: torch.Tensor) -> torch.Tensor: ...
 
 
     prob = Problem("min", f, solution_length=..., dtype=torch.float32)
diff --git a/src/evotorch/decorators.py b/src/evotorch/decorators.py
index 796ad215..d8e40c04 100644
--- a/src/evotorch/decorators.py
+++ b/src/evotorch/decorators.py
@@ -254,8 +254,7 @@ def f(x: torch.Tensor) -> torch.Tensor:
 
 
     @on_device("cuda")
-    def f(x: torch.Tensor) -> torch.Tensor:
-        ...
+    def f(x: torch.Tensor) -> torch.Tensor: ...
 
 
     problem = Problem(
@@ -306,8 +305,7 @@ def _evaluate_batch(self, solutions: SolutionBatch):
 
     ```python
     @on_device("cpu")
-    def f(x: torch.Tensor) -> torch.Tensor:
-        ...
+    def f(x: torch.Tensor) -> torch.Tensor: ...
 
 
     print(f.device)  # Prints: torch.device("cpu")
@@ -499,8 +497,7 @@ def f(x: torch.Tensor) -> torch.Tensor:
 
 
     @on_aux_device
-    def f(x: torch.Tensor) -> torch.Tensor:
-        ...
+    def f(x: torch.Tensor) -> torch.Tensor: ...
 
 
     problem = Problem(
@@ -632,8 +629,7 @@ def expects_ndim(  # noqa: C901
 
 
     @expects_ndim(2, 1)
-    def f(a: torch.Tensor, b: torch.Tensor) -> torch.Tensor:
-        ...
+    def f(a: torch.Tensor, b: torch.Tensor) -> torch.Tensor: ...
     ```
 
     Once decorated like this, the function `f` will gain the following
@@ -663,8 +659,7 @@ def f(a: torch.Tensor, b: torch.Tensor) -> torch.Tensor:
 
     ```python
     @expects_ndim(2, 1, randomness="error")
-    def f(a: torch.Tensor, b: torch.Tensor) -> torch.Tensor:
-        ...
+    def f(a: torch.Tensor, b: torch.Tensor) -> torch.Tensor: ...
     ```
 
     If `randomness` is set as "error", then, when there is batching, any
@@ -941,8 +936,7 @@ def fitness(decision_values: torch.Tensor) -> torch.Tensor:
 
     ```python
     @rowwise(randomness="error")
-    def f(x: torch.Tensor) -> torch.Tensor:
-        ...
+    def f(x: torch.Tensor) -> torch.Tensor: ...
     ```
 
     If `randomness` is set as "error", then, when there is batching, any
diff --git a/src/evotorch/distributions.py b/src/evotorch/distributions.py
index 5af92141..2636a3e8 100644
--- a/src/evotorch/distributions.py
+++ b/src/evotorch/distributions.py
@@ -1395,8 +1395,7 @@ def make_functional_grad_estimator(
     )
 
 
-    def f(x: torch.Tensor) -> torch.Tensor:
-        ...
+    def f(x: torch.Tensor) -> torch.Tensor: ...
 
 
     fgrad = make_functional_grad_estimator(