Update MLP module for RTDETR backward compatibility (#14901)
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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2 changed files with 5 additions and 2 deletions
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@ -8,6 +8,7 @@ from PIL import Image
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from tests import CUDA_DEVICE_COUNT, CUDA_IS_AVAILABLE
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from ultralytics.cfg import TASK2DATA, TASK2MODEL, TASKS
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from ultralytics.utils import ASSETS, WEIGHTS_DIR, checks
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from ultralytics.utils.torch_utils import TORCH_1_9
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# Constants
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TASK_MODEL_DATA = [(task, WEIGHTS_DIR / TASK2MODEL[task], TASK2DATA[task]) for task in TASKS]
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@ -57,6 +58,8 @@ def test_rtdetr(task="detect", model="yolov8n-rtdetr.yaml", data="coco8.yaml"):
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# Warning: must use imgsz=640 (note also add coma, spaces, fraction=0.25 args to test single-image training)
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run(f"yolo train {task} model={model} data={data} --imgsz= 160 epochs =1, cache = disk fraction=0.25")
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run(f"yolo predict {task} model={model} source={ASSETS / 'bus.jpg'} imgsz=160 save save_crop save_txt")
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if TORCH_1_9:
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run(f"yolo predict {task} model='rtdetr-l.pt' source={ASSETS / 'bus.jpg'} imgsz=160 save save_crop save_txt")
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@pytest.mark.skipif(checks.IS_PYTHON_3_12, reason="MobileSAM with CLIP is not supported in Python 3.12")
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@ -186,8 +186,8 @@ class MLP(nn.Module):
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def forward(self, x):
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"""Forward pass for the entire MLP."""
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for i, layer in enumerate(self.layers):
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x = self.act(layer(x)) if i < self.num_layers - 1 else layer(x)
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return x.sigmoid() if self.sigmoid else x
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x = getattr(self, "act", nn.ReLU())(layer(x)) if i < self.num_layers - 1 else layer(x)
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return x.sigmoid() if getattr(self, "sigmoid", False) else x
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class LayerNorm2d(nn.Module):
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