[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Author: pre-commit-ci[bot]

happypose/pose_estimators/cosypose/cosypose/evaluation/evaluation.py

@@ -65,7 +65,9 @@ def load_detector(run_id, ds_name):
     cfg = check_update_config_detector(cfg)
     label_to_category_id = cfg.label_to_category_id
     model = create_model_detector(cfg, len(label_to_category_id))
-    ckpt = torch.load(run_dir / "checkpoint.pth.tar", map_location=device, weights_only=True)
+    ckpt = torch.load(
+        run_dir / "checkpoint.pth.tar", map_location=device, weights_only=True
+    )
     ckpt = ckpt["state_dict"]
     model.load_state_dict(ckpt)
     model = model.to(device).eval()

happypose/pose_estimators/cosypose/cosypose/training/evaluation.py

@@ -69,7 +69,9 @@ def load_detector(run_id, ds_name):
     cfg = check_update_config_detector(cfg)
     label_to_category_id = cfg.label_to_category_id
     model = create_model_detector(cfg, len(label_to_category_id))
-    ckpt = torch.load(run_dir / "checkpoint.pth.tar", map_location=device, weights_only=True)
+    ckpt = torch.load(
+        run_dir / "checkpoint.pth.tar", map_location=device, weights_only=True
+    )
     ckpt = ckpt["state_dict"]
     model.load_state_dict(ckpt)
     model = model.to(device).eval()

happypose/pose_estimators/cosypose/cosypose/training/pose_models_cfg.py

@@ -65,7 +65,9 @@ def load_model_cosypose(
     cfg = yaml.load((run_dir / "config.yaml").read_text(), Loader=yaml.UnsafeLoader)
     cfg = check_update_config(cfg)
     model = create_pose_model_cosypose(cfg, renderer=renderer, mesh_db=mesh_db_batched)
-    ckpt = torch.load(run_dir / "checkpoint.pth.tar", map_location=device, weights_only=True)
+    ckpt = torch.load(
+        run_dir / "checkpoint.pth.tar", map_location=device, weights_only=True
+    )
     ckpt = ckpt["state_dict"]
     model.load_state_dict(ckpt)
     model = model.to(device).eval()

happypose/toolbox/inference/utils.py

@@ -64,7 +64,11 @@ def load_detector(run_id: str, device="cpu") -> torch.nn.Module:
     cfg = check_update_config_detector(cfg)
     label_to_category_id = cfg.label_to_category_id
     model = create_model_detector(cfg, len(label_to_category_id))
-    ckpt = torch.load(run_dir / "checkpoint.pth.tar", map_location=torch.device(device), weights_only=True)
+    ckpt = torch.load(
+        run_dir / "checkpoint.pth.tar",
+        map_location=torch.device(device),
+        weights_only=True,
+    )
     ckpt = ckpt["state_dict"]
     model.load_state_dict(ckpt)
     model = model.to(device).eval()