Bump precommit hooks and fix files accordingly

.pre-commit-config.yaml

 repos:
-  - repo: https://github.com/asottile/seed-isort-config
-    rev: v2.2.0
-    hooks:
-      - id: seed-isort-config
-  - repo: https://github.com/pre-commit/mirrors-isort
-    rev: v5.10.1
+  - repo: https://github.com/PyCQA/isort
+    rev: 5.12.0
     hooks:
       - id: isort
   - repo: https://github.com/ambv/black
-    rev: 22.3.0
+    rev: 23.1.0
     hooks:
     - id: black
   - repo: https://github.com/pycqa/flake8
-    rev: 3.9.2
+    rev: 6.0.0
     hooks:
       - id: flake8
         additional_dependencies:
-          - 'flake8-coding==1.3.1'
-          - 'flake8-copyright==0.2.2'
-          - 'flake8-debugger==3.1.0'
+          - 'flake8-coding==1.3.2'
+          - 'flake8-debugger==4.1.2'
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.1.0
+    rev: v4.4.0
     hooks:
       - id: check-ast
       - id: check-docstring-first
@@ -37,7 +32,7 @@ repos:
       - id: check-json
       - id: requirements-txt-fixer
   - repo: https://github.com/codespell-project/codespell
-    rev: v2.1.0
+    rev: v2.2.2
     hooks:
       - id: codespell
         args: ['--write-changes']

doc_ufcn/train/cli.py

@@ -30,7 +30,6 @@ def parse_args():
 
 
 def main():
-
     args = parse_args()
 
     # Parse all configuration files provided from CLI

doc_ufcn/train/utils/__init__.py

@@ -67,7 +67,6 @@ def create_buckets(images_sizes, bin_size):
 
 class Sampler(torch.utils.data.Sampler):
     def __init__(self, data, bin_size=20, batch_size=None, nb_params=None):
-
         self.bin_size = bin_size
         self.batch_size = batch_size
         self.nb_params = nb_params

hugging_face/app.py

@@ -116,7 +116,6 @@ def query_image(image):
 
 
 with gr.Blocks() as process_image:
-
     # Create app title
     gr.Markdown(f"# {config['title']}")
 
@@ -125,16 +124,13 @@ with gr.Blocks() as process_image:
 
     # Create a first row of blocks
     with gr.Row():
-
         # Create a column on the left
         with gr.Column():
-
             # Generates an image that can be uploaded by a user
             image = gr.Image()
 
             # Create a row under the image
             with gr.Row():
-
                 # Generate a button to clear the inputs and outputs
                 clear_button = gr.Button("Clear", variant="secondary")
 
@@ -143,25 +139,20 @@ with gr.Blocks() as process_image:
 
             # Create a row under the buttons
             with gr.Row():
-
                 # Generate example images that can be used as input image
                 examples = gr.Examples(inputs=image, examples=config["examples"])
 
         # Create a column on the right
         with gr.Column():
-
             # Generates an output image that does not support upload
             image_output = gr.Image(interactive=False)
 
             # Create a row under the predicted image
             with gr.Row():
-
                 # Create a column so that the JSON output doesn't take the full size of the page
                 with gr.Column():
-
                     # Create a collapsible region
                     with gr.Accordion("JSON"):
-
                         # Generates a json with the model predictions
                         json_output = gr.JSON()
 

tools/training-csv-config.py

@@ -40,7 +40,6 @@ def generate_configurations(csv_path):
 
     reader = csv.DictReader(csv_path.open(), delimiter=",")
     for row in reader:
-
         config = {}
         # Get experiment name.
         assert row["experiment_name"] != "", "Missing experiment name"
@@ -87,7 +86,6 @@ def run(csv_path, output):
     os.makedirs(output, exist_ok=True)
 
     for index, config in enumerate(generate_configurations(csv_path), 1):
-
         # Save each configuration in a dedicated file file.
         json_file = str(index) + "_" + config["experiment_name"] + ".json"
         with open(os.path.join(output, json_file), "w") as file: