Update pre-commit hooks

.pre-commit-config.yaml

@@ -2,7 +2,7 @@ default_language_version:
     python: python3
 repos:
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.12.4
+    rev: v0.15.0
     hooks:
       - id: ruff
         args: [--fix, --exit-non-zero-on-fix]
@@ -18,11 +18,11 @@ repos:
         args: [--in-place, --black, --style=epytext]
 
   - repo: https://github.com/executablebooks/mdformat
-    rev: 0.7.22
+    rev: 1.0.0
     hooks:
       - id: mdformat
         additional_dependencies:
-          - mdformat-gfm==0.3.6
+          - mdformat-gfm
 
   - repo: https://github.com/ComPWA/taplo-pre-commit
     rev: v0.9.3
@@ -31,7 +31,7 @@ repos:
       - id: taplo-format
 
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v5.0.0
+    rev: v6.0.0
     hooks:
       - id: trailing-whitespace
       - id: check-docstring-first

modelconverter/__main__.py

@@ -45,7 +45,9 @@
 
 app = App(
     name="Modelconverter",
-    version=lambda: f"ModelConverter v{importlib.metadata.version('modelconv')}",
+    version=lambda: (
+        f"ModelConverter v{importlib.metadata.version('modelconv')}"
+    ),
 )
 
 app.meta.group_parameters = Group("Global Parameters", sort_key=0)

modelconverter/packages/rvc2/benchmark.py

@@ -55,9 +55,7 @@ def _benchmark(
                         model_path,
                         platform=device.getPlatformAsString(),
                     ),
-                    apiKey=environ.HUBAI_API_KEY
-                    if environ.HUBAI_API_KEY
-                    else "",
+                    apiKey=environ.HUBAI_API_KEY or "",
                 )
             )
         elif (

modelconverter/packages/rvc4/analyze.py

@@ -435,9 +435,7 @@ def _process_diagview_csv(self, csv_path: str) -> None:
             pl.col("layer_name")
             .str.split(":")
             .list.first()
-            .map_elements(
-                lambda x: self._replace_bad_layer_name(x), return_dtype=pl.Utf8
-            )
+            .map_elements(self._replace_bad_layer_name, return_dtype=pl.Utf8)
             .alias("layer_name"),
             pl.col("time_mean")
             .mul(1 / total_time)

modelconverter/packages/rvc4/benchmark.py

@@ -334,7 +334,7 @@ def _benchmark_snpe(
                     model_path,
                     platform=dai.Platform.RVC4.name,
                 ),
-                apiKey=environ.HUBAI_API_KEY if environ.HUBAI_API_KEY else "",
+                apiKey=environ.HUBAI_API_KEY or "",
             )
             tmp_dir = Path(model_archive).parent / "tmp"
             shutil.unpack_archive(model_archive, tmp_dir)
@@ -413,7 +413,7 @@ def _benchmark_dai(
                     model_path,
                     platform=device.getPlatformAsString(),
                 ),
-                apiKey=environ.HUBAI_API_KEY if environ.HUBAI_API_KEY else "",
+                apiKey=environ.HUBAI_API_KEY or "",
             )
         elif str(model_path).endswith(".tar.xz"):
             modelPath = str(model_path)

modelconverter/packages/rvc4/visualize.py

@@ -223,7 +223,7 @@ def _visualize_layer_outputs(self) -> go.Figure:
     def _get_csv_paths(
         self, dir_path: Path, comparison_type: str = "layer_comparison"
     ) -> dict[str, str]:
-        dir_path = dir_path if dir_path else constants.OUTPUTS_DIR / "analysis"
+        dir_path = dir_path or constants.OUTPUTS_DIR / "analysis"
         csv_paths = {}
 
         for file in dir_path.glob(f"*{comparison_type}*.csv"):

modelconverter/utils/docker_utils.py

@@ -12,12 +12,12 @@
 
 import psutil
 import yaml
+from docker.utils import parse_repository_tag
 from loguru import logger
 from luxonis_ml.utils import environ
 from rich.progress import BarColumn, Progress, TaskProgressColumn, TextColumn
 
 import docker
-from docker.utils import parse_repository_tag
 
 
 def get_docker_client_from_active_context() -> docker.DockerClient:
@@ -217,7 +217,7 @@
     tmp_path: Path | None = None
     try:
         request = Request(url, headers={"User-Agent": "modelconverter"})  # noqa: S310
         with urlopen(request, timeout=30) as response:  # noqa: S310
             if getattr(response, "status", 200) >= 400:
                 raise RuntimeError(
                     f"HTTP {response.status} while downloading {url}"

modelconverter/utils/onnx_tools.py

@@ -27,7 +27,9 @@ def get_extra_quant_tensors(
     output_configs: dict[str, OutputConfig],
     depth: int = 2,
 ) -> list[str]:
-    """Return unique tensor names that are inputs to producer nodes encountered when walking upstream from the selected graph outputs, up to depth producer hops.
+    """Return unique tensor names that are inputs to producer nodes
+    encountered when walking upstream from the selected graph outputs,
+    up to depth producer hops.
 
     - Starts from graph outputs whose names are keys in output_configs.
     - At each hop: for each tensor, find its producing node; add that node's
@@ -1398,21 +1400,21 @@ def compare_outputs(self, from_modelproto: bool = False) -> bool:
 
         inputs = {}
         for input in ort_session_1.get_inputs():
-            if input.type in ["tensor(float64)"]:
+            if input.type == "tensor(float64)":
                 input_type = np.float64
-            elif input.type in ["tensor(float32)", "tensor(float)"]:
+            elif input.type in {"tensor(float32)", "tensor(float)"}:
                 input_type = np.float32
-            elif input.type in ["tensor(float16)"]:
+            elif input.type == "tensor(float16)":
                 input_type = np.float16
-            elif input.type in ["tensor(int64)"]:
+            elif input.type == "tensor(int64)":
                 input_type = np.int64
-            elif input.type in ["tensor(int32)"]:
+            elif input.type == "tensor(int32)":
                 input_type = np.int32
-            elif input.type in ["tensor(int16)"]:
+            elif input.type == "tensor(int16)":
                 input_type = np.int16
-            elif input.type in ["tensor(int8)"]:
+            elif input.type == "tensor(int8)":
                 input_type = np.int8
-            elif input.type in ["tensor(bool)"]:
+            elif input.type == "tensor(bool)":
                 input_type = "bool"
 
             inputs[input.name] = np.random.rand(*input.shape).astype(

modelconverter/utils/subprocess.py

@@ -11,6 +11,7 @@
 
 import psutil
 from loguru import logger
+from typing_extensions import Self
 
 from .exceptions import SubprocessException
 
@@ -161,7 +162,7 @@
         """
         return self.proc.wait(timeout=self.timeout or timeout)
 
-    def __enter__(self) -> "SubprocessHandle":
+    def __enter__(self) -> Self:
         if shutil.which(self.cmd_name) is None:
             raise SubprocessException(
                 f"Command `{self.cmd_name}` not found. Ensure it is in PATH."
@@ -171,7 +172,7 @@
             logger.info(f"Executing `{' '.join(self.cmd)}`")
 
         self._start_time = time.time()
         self._proc = subprocess.Popen(
             self.cmd,
             stdout=subprocess.PIPE,
             stderr=subprocess.PIPE,