Run ruff and update imports

invokeai/backend/model_manager/probe.py

@@ -31,7 +31,7 @@ from invokeai.backend.model_manager.config import (
 )
 from invokeai.backend.model_manager.util.model_util import lora_token_vector_length, read_checkpoint_meta
 from invokeai.backend.quantization.gguf.layers import GGUFTensor
-from invokeai.backend.quantization.gguf.loaders import load_gguf_sd
+from invokeai.backend.quantization.gguf.loaders import gguf_sd_loader
 from invokeai.backend.spandrel_image_to_image_model import SpandrelImageToImageModel
 from invokeai.backend.util.silence_warnings import SilenceWarnings
 
@@ -412,7 +412,7 @@ class ModelProbe(object):
                 assert isinstance(model, dict)
                 return model
             elif model_path.suffix.endswith(".gguf"):
-                return load_gguf_sd(model_path)
+                return gguf_sd_loader(model_path)
             else:
                 return safetensors.torch.load_file(model_path)
 

invokeai/backend/model_manager/util/model_util.py

@@ -8,7 +8,7 @@ import safetensors
 import torch
 from picklescan.scanner import scan_file_path
 
-from invokeai.backend.quantization.gguf.loaders import load_gguf_sd
+from invokeai.backend.quantization.gguf.loaders import gguf_sd_loader
 
 
 def _fast_safetensors_reader(path: str) -> Dict[str, torch.Tensor]:
@@ -57,7 +57,7 @@ def read_checkpoint_meta(path: Union[str, Path], scan: bool = False) -> Dict[str
             if scan_result.infected_files != 0:
                 raise Exception(f'The model file "{path}" is potentially infected by malware. Aborting import.')
         if str(path).endswith(".gguf"):
-            checkpoint = load_gguf_sd(Path(path))
+            checkpoint = gguf_sd_loader(Path(path))
         else:
             checkpoint = torch.load(path, map_location=torch.device("meta"))
     return checkpoint

invokeai/backend/quantization/gguf/loaders.py

@@ -9,8 +9,6 @@ from invokeai.backend.quantization.gguf.ggml_tensor import GGMLTensor
 from invokeai.backend.quantization.gguf.layers import GGUFTensor
 from invokeai.backend.quantization.gguf.utils import TORCH_COMPATIBLE_QTYPES
 
-TORCH_COMPATIBLE_QTYPES = {gguf.GGMLQuantizationType.F32, gguf.GGMLQuantizationType.F16}
-
 
 def gguf_sd_loader(path: Path) -> dict[str, GGUFTensor]:
     reader = gguf.GGUFReader(path)

tests/backend/quantization/gguf/test_gguf_tensor.py

@@ -14,4 +14,4 @@ def test_ggml_tensor():
     ggml_tensor = GGMLTensor(data, tensor_type, tensor_shape)
     ones = torch.ones([1], dtype=torch.float32)
 
-    x = ggml_tensor * ones
+    _ = ggml_tensor * ones