From ce8c7205dc82b20bc4437de70e2cd7e04250e3a3 Mon Sep 17 00:00:00 2001
From: Sean Sube <seansube@gmail.com>
Date: Fri, 17 Feb 2023 22:49:13 -0600
Subject: [PATCH] apply lint

---
 api/onnx_web/convert/__main__.py | 1 +
 api/onnx_web/convert/utils.py    | 4 +++-
 api/onnx_web/utils.py            | 6 ++++--
 3 files changed, 8 insertions(+), 3 deletions(-)

diff --git a/api/onnx_web/convert/__main__.py b/api/onnx_web/convert/__main__.py
index ea62fd6b..bfeabb00 100644
--- a/api/onnx_web/convert/__main__.py
+++ b/api/onnx_web/convert/__main__.py
@@ -266,6 +266,7 @@ def convert_models(ctx: ConversionContext, args, models: Models):
                 except Exception as e:
                     logger.error("error converting correction model %s: %s", name, e)
 
+
 def main() -> int:
     parser = ArgumentParser(
         prog="onnx-web model converter", description="convert checkpoint models to ONNX"
diff --git a/api/onnx_web/convert/utils.py b/api/onnx_web/convert/utils.py
index 7ddfe5f2..676e2663 100644
--- a/api/onnx_web/convert/utils.py
+++ b/api/onnx_web/convert/utils.py
@@ -222,7 +222,9 @@ def load_tensor(name: str, map_location=None):
                 )
                 checkpoint = torch.load(name, map_location=map_location)
                 checkpoint = (
-                    checkpoint["state_dict"] if "state_dict" in checkpoint else checkpoint
+                    checkpoint["state_dict"]
+                    if "state_dict" in checkpoint
+                    else checkpoint
                 )
     else:
         logger.debug("loading ckpt")
diff --git a/api/onnx_web/utils.py b/api/onnx_web/utils.py
index 104cf99e..a23198e4 100644
--- a/api/onnx_web/utils.py
+++ b/api/onnx_web/utils.py
@@ -1,7 +1,7 @@
 import gc
+import threading
 from logging import getLogger
 from os import environ, path
-import threading
 from typing import Any, Dict, List, Optional, Union
 
 import torch
@@ -136,7 +136,9 @@ def get_size(val: Union[int, str, None]) -> SizeChart:
 
 
 def run_gc(devices: List[DeviceParams] = []):
-    logger.debug("running garbage collection with %s active threads", threading.active_count())
+    logger.debug(
+        "running garbage collection with %s active threads", threading.active_count()
+    )
     gc.collect()
 
     if torch.cuda.is_available():