chore: ruff

Author: psychedelicious

invokeai/app/invocations/segment_anything.py

@@ -185,9 +185,9 @@ def _filter_masks(
             # Find the largest mask.
             return [max(masks, key=lambda x: float(x.sum()))]
         elif self.mask_filter == "highest_box_score":
-            assert bounding_boxes is not None, (
-                "Bounding boxes must be provided to use the 'highest_box_score' mask filter."
-            )
+            assert (
+                bounding_boxes is not None
+            ), "Bounding boxes must be provided to use the 'highest_box_score' mask filter."
             assert len(masks) == len(bounding_boxes)
             # Find the index of the bounding box with the highest score.
             # Note that we fallback to -1.0 if the score is None. This is mainly to satisfy the type checker. In most

invokeai/app/services/config/config_default.py

@@ -483,9 +483,9 @@ def load_and_migrate_config(config_path: Path) -> InvokeAIAppConfig:
     try:
         # Meta is not included in the model fields, so we need to validate it separately
         config = InvokeAIAppConfig.model_validate(loaded_config_dict)
-        assert config.schema_version == CONFIG_SCHEMA_VERSION, (
-            f"Invalid schema version, expected {CONFIG_SCHEMA_VERSION}: {config.schema_version}"
-        )
+        assert (
+            config.schema_version == CONFIG_SCHEMA_VERSION
+        ), f"Invalid schema version, expected {CONFIG_SCHEMA_VERSION}: {config.schema_version}"
         return config
     except Exception as e:
         raise RuntimeError(f"Failed to load config file {config_path}: {e}") from e

invokeai/backend/model_manager/merge.py

@@ -115,19 +115,19 @@ def merge_diffusion_models_and_save(
         base_models: Set[BaseModelType] = set()
         variant = None if self._installer.app_config.precision == "float32" else "fp16"
 
-        assert len(model_keys) <= 2 or interp == MergeInterpolationMethod.AddDifference, (
-            "When merging three models, only the 'add_difference' merge method is supported"
-        )
+        assert (
+            len(model_keys) <= 2 or interp == MergeInterpolationMethod.AddDifference
+        ), "When merging three models, only the 'add_difference' merge method is supported"
 
         for key in model_keys:
             info = store.get_model(key)
             model_names.append(info.name)
-            assert isinstance(info, MainDiffusersConfig), (
-                f"{info.name} ({info.key}) is not a diffusers model. It must be optimized before merging"
-            )
-            assert info.variant == ModelVariantType("normal"), (
-                f"{info.name} ({info.key}) is a {info.variant} model, which cannot currently be merged"
-            )
+            assert isinstance(
+                info, MainDiffusersConfig
+            ), f"{info.name} ({info.key}) is not a diffusers model. It must be optimized before merging"
+            assert info.variant == ModelVariantType(
+                "normal"
+            ), f"{info.name} ({info.key}) is a {info.variant} model, which cannot currently be merged"
 
             # tally base models used
             base_models.add(info.base)

tests/app/services/download/test_download_queue.py

@@ -212,12 +212,12 @@ def event_handler(job: DownloadJob | MultiFileDownloadJob, excp: Optional[Except
     assert job.bytes > 0, "expected download bytes to be positive"
     assert job.bytes == job.total_bytes, "expected download bytes to equal total bytes"
     assert job.download_path == tmp_path / "sdxl-turbo"
-    assert Path(tmp_path, "sdxl-turbo/model_index.json").exists(), (
-        f"expected {tmp_path}/sdxl-turbo/model_inded.json to exist"
-    )
-    assert Path(tmp_path, "sdxl-turbo/text_encoder/config.json").exists(), (
-        f"expected {tmp_path}/sdxl-turbo/text_encoder/config.json to exist"
-    )
+    assert Path(
+        tmp_path, "sdxl-turbo/model_index.json"
+    ).exists(), f"expected {tmp_path}/sdxl-turbo/model_inded.json to exist"
+    assert Path(
+        tmp_path, "sdxl-turbo/text_encoder/config.json"
+    ).exists(), f"expected {tmp_path}/sdxl-turbo/text_encoder/config.json to exist"
 
     assert events == {DownloadJobStatus.RUNNING, DownloadJobStatus.COMPLETED}
     queue.stop()