HongChuang/ultralytics-ascend
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Apply Ruff 0.9.0 (#18622)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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Glenn Jocher 2025-01-10 00:05:09 +01:00 • committed by GitHub
parent cc1e77138c
commit 3902e740cf
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22 changed files with 69 additions and 65 deletions
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30
ultralytics/engine/exporter.py
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@ -357,7 +357,7 @@ class Exporter:
)
self.pretty_name = Path(self.model.yaml.get("yaml_file", self.file)).stem.replace("yolo", "YOLO")
data = model.args["data"] if hasattr(model, "args") and isinstance(model.args, dict) else ""
description = f'Ultralytics {self.pretty_name} model {f"trained on {data}" if data else ""}'
description = f"Ultralytics {self.pretty_name} model {f'trained on {data}' if data else ''}"
self.metadata = {
"description": description,
"author": "Ultralytics",
@ -377,7 +377,7 @@ class Exporter:
LOGGER.info(
f"\n{colorstr('PyTorch:')} starting from '{file}' with input shape {tuple(im.shape)} BCHW and "
f'output shape(s) {self.output_shape} ({file_size(file):.1f} MB)'
f"output shape(s) {self.output_shape} ({file_size(file):.1f} MB)"
)
# Exports
@ -427,11 +427,11 @@ class Exporter:
predict_data = f"data={data}" if model.task == "segment" and fmt == "pb" else ""
q = "int8" if self.args.int8 else "half" if self.args.half else "" # quantization
LOGGER.info(
f'\nExport complete ({time.time() - t:.1f}s)'
f"\nExport complete ({time.time() - t:.1f}s)"
f"\nResults saved to {colorstr('bold', file.parent.resolve())}"
f'\nPredict: yolo predict task={model.task} model={f} imgsz={imgsz} {q} {predict_data}'
f'\nValidate: yolo val task={model.task} model={f} imgsz={imgsz} data={data} {q} {s}'
f'\nVisualize: https://netron.app'
f"\nPredict: yolo predict task={model.task} model={f} imgsz={imgsz} {q} {predict_data}"
f"\nValidate: yolo val task={model.task} model={f} imgsz={imgsz} data={data} {q} {s}"
f"\nVisualize: https://netron.app"
)
self.run_callbacks("on_export_end")
@ -680,16 +680,16 @@ class Exporter:
shutil.rmtree(unzip_dir) # delete unzip dir
ncnn_args = [
f'ncnnparam={f / "model.ncnn.param"}',
f'ncnnbin={f / "model.ncnn.bin"}',
f'ncnnpy={f / "model_ncnn.py"}',
f"ncnnparam={f / 'model.ncnn.param'}",
f"ncnnbin={f / 'model.ncnn.bin'}",
f"ncnnpy={f / 'model_ncnn.py'}",
]
pnnx_args = [
f'pnnxparam={f / "model.pnnx.param"}',
f'pnnxbin={f / "model.pnnx.bin"}',
f'pnnxpy={f / "model_pnnx.py"}',
f'pnnxonnx={f / "model.pnnx.onnx"}',
f"pnnxparam={f / 'model.pnnx.param'}",
f"pnnxbin={f / 'model.pnnx.bin'}",
f"pnnxpy={f / 'model_pnnx.py'}",
f"pnnxonnx={f / 'model.pnnx.onnx'}",
]
cmd = [
@ -1139,7 +1139,9 @@ class Exporter:
def export_imx(self, prefix=colorstr("IMX:")):
"""YOLO IMX export."""
gptq = False
assert LINUX, "export only supported on Linux. See https://developer.aitrios.sony-semicon.com/en/raspberrypi-ai-camera/documentation/imx500-converter"
assert LINUX, (
"export only supported on Linux. See https://developer.aitrios.sony-semicon.com/en/raspberrypi-ai-camera/documentation/imx500-converter"
)
if getattr(self.model, "end2end", False):
raise ValueError("IMX export is not supported for end2end models.")
if "C2f" not in self.model.__str__():