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Docs Ruff codeblocks reformat and fix (#12847)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Glenn Jocher 2024-05-19 19:13:04 +02:00 • committed by GitHub
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9 changed files with 167 additions and 178 deletions
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43
docs/en/integrations/tensorrt.md
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@ -153,15 +153,16 @@ Experimentation by NVIDIA led them to recommend using at least 500 calibration i
model = YOLO("yolov8n.pt")
model.export(
format="engine",
dynamic=True, #(1)!
batch=8, #(2)!
workspace=4, #(3)!
dynamic=True, # (1)!
batch=8, # (2)!
workspace=4, # (3)!
int8=True,
data="coco.yaml", #(4)!
data="coco.yaml", # (4)!
)
# Load the exported TensorRT INT8 model
model = YOLO("yolov8n.engine", task="detect")
# Run inference
result = model.predict("https://ultralytics.com/images/bus.jpg")
```
@ -385,36 +386,14 @@ Expand sections below for information on how these models were exported and test
model = YOLO("yolov8n.pt")
# TensorRT FP32
out = model.export(
format="engine",
imgsz:640,
dynamic:True,
verbose:False,
batch:8,
workspace:2
)
out = model.export(format="engine", imgsz=640, dynamic=True, verbose=False, batch=8, workspace=2)
# TensorRT FP16
out = model.export(format="engine", imgsz=640, dynamic=True, verbose=False, batch=8, workspace=2, half=True)
# TensorRT INT8 with calibration `data` (i.e. COCO, ImageNet, or DOTAv1 for appropriate model task)
out = model.export(
format="engine",
imgsz:640,
dynamic:True,
verbose:False,
batch:8,
workspace:2,
half=True
)
# TensorRT INT8
out = model.export(
format="engine",
imgsz:640,
dynamic:True,
verbose:False,
batch:8,
workspace:2,
int8=True,
data:"data.yaml" # COCO, ImageNet, or DOTAv1 for appropriate model task
format="engine", imgsz=640, dynamic=True, verbose=False, batch=8, workspace=2, int8=True, data="coco8.yaml"
)
```