isort, black, flake8 formatting

Signed-off-by: kta-intel <[email protected]>

.pre-commit-config.yaml

@@ -2,7 +2,7 @@
 minimum_pre_commit_version: 3.3.3
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.4.0
+    rev: v5.0.0
     hooks:
       - id: end-of-file-fixer
         files: \.py$
@@ -21,7 +21,7 @@ repos:
       - id: trailing-whitespace
         files: \.py$
   - repo: https://github.com/PyCQA/autoflake
-    rev: v2.2.0
+    rev: v2.3.1
     hooks:
       - id: autoflake
         args:

openfl_contrib/__version__.py

@@ -1,4 +1,4 @@
 # Copyright (C) 2024 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 """openfl-contrib version information."""
-__version__ = '0.1.0'
+__version__ = "0.1.0"

openfl_contrib/interface/aggregation_functions/__init__.py

@@ -3,4 +3,6 @@
 
 """Aggregation functions package."""
 
-from openfl_contrib.interface.aggregation_functions.custom_weighted_average import CustomWeightedAverage
+from openfl_contrib.interface.aggregation_functions.custom_weighted_average import (
+    CustomWeightedAverage,
+)

openfl_contrib/interface/aggregation_functions/custom_weighted_average.py

@@ -4,7 +4,6 @@
 """Custom Federated averaging module."""
 
 import numpy as np
-
 from openfl.interface.aggregation_functions.core import AggregationFunction
 
 
@@ -41,7 +40,5 @@ def call(self, local_tensors, *_) -> np.ndarray:
         tensors, weights = zip(*[(x.tensor, x.weight) for x in local_tensors])
 
         total_weight = sum(weights)
-        weighted_sum = np.sum(
-            [tensor * weight for tensor, weight in zip(tensors, weights)], axis=0
-        )
+        weighted_sum = np.sum([tensor * weight for tensor, weight in zip(tensors, weights)], axis=0)
         return weighted_sum / total_weight

openfl_contrib/pipelines/skc_pipeline.py

@@ -7,11 +7,9 @@
 import gzip as gz
 
 import numpy as np
+from openfl.pipelines.pipeline import TransformationPipeline, Transformer
 from sklearn import cluster
 
-from openfl.pipelines.pipeline import TransformationPipeline
-from openfl.pipelines.pipeline import Transformer
-
 
 class SparsityTransformer(Transformer):
     """A transformer class to sparsify input data."""

shell/format.sh

@@ -6,8 +6,8 @@ base_dir=$(dirname $(dirname $0))
 # Run the pre-commit checks
 pre-commit run --all-files
 
-isort --sp "${base_dir}/pyproject.toml" openfl
+isort --sp "${base_dir}/pyproject.toml" openfl_contrib
 
-black --config "${base_dir}/pyproject.toml" openfl
+black --config "${base_dir}/pyproject.toml" openfl_contrib
 
-flake8 --config "${base_dir}/setup.cfg" openfl
+flake8 --config "${base_dir}/setup.cfg" openfl_contrib

shell/lint.sh

@@ -6,8 +6,8 @@ base_dir=$(dirname $(dirname $0))
 # Run the pre-commit checks
 pre-commit run --all-files
 
-isort --sp "${base_dir}/pyproject.toml" --check openfl
+isort --sp "${base_dir}/pyproject.toml" --check openfl_contrib
 
-black --config "${base_dir}/pyproject.toml" --check openfl
+black --config "${base_dir}/pyproject.toml" --check openfl_contrib
 
-flake8 --config "${base_dir}/setup.cfg" --show-source openfl
+flake8 --config "${base_dir}/setup.cfg" --show-source openfl_contrib