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set COARSE_PRED_EACH_LAYER to False for semantic seg
Summary: Make training much more stable (no NaNs in 7 runs). Results slightly better (average is around 78.8). Reviewed By: alexander-kirillov Differential Revision: D22427114 fbshipit-source-id: 3a3ea9895e5ac955a62454b73cff71f496e0fbfb
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projects/PointRend/README.md

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@@ -115,9 +115,9 @@ Cityscapes model is trained with ImageNet pretraining.
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<tr><td align="left"><a href="configs/SemanticSegmentation/pointrend_semantic_R_101_FPN_1x_cityscapes.yaml">SemanticFPN + PointRend</a></td>
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<td align="center">R101-FPN</td>
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<td align="center">1024&times;2048</td>
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<td align="center">78.6</td>
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<td align="center">186480235</td>
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<td align="center"><a href="https://dl.fbaipublicfiles.com/detectron2/PointRend/SemanticSegmentation/pointrend_semantic_R_101_FPN_1x_cityscapes/186480235/model_final_5f3665.pkl">model</a>&nbsp;|&nbsp;<a href="https://dl.fbaipublicfiles.com/detectron2/PointRend/SemanticSegmentation/pointrend_semantic_R_101_FPN_1x_cityscapes/186480235/metrics.json">metrics</a></td>
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<td align="center">78.9</td>
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<td align="center">202576688</td>
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<td align="center"><a href="https://dl.fbaipublicfiles.com/detectron2/PointRend/SemanticSegmentation/pointrend_semantic_R_101_FPN_1x_cityscapes/202576688/model_final_cf6ac1.pkl">model</a>&nbsp;|&nbsp;<a href="https://dl.fbaipublicfiles.com/detectron2/PointRend/SemanticSegmentation/pointrend_semantic_R_101_FPN_1x_cityscapes/202576688/metrics.json">metrics</a></td>
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</tr>
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</tbody></table>
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projects/PointRend/configs/SemanticSegmentation/Base-PointRend-Semantic-FPN.yaml

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SUBDIVISION_STEPS: 2
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SUBDIVISION_NUM_POINTS: 8192
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COARSE_SEM_SEG_HEAD_NAME: "SemSegFPNHead"
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COARSE_PRED_EACH_LAYER: False
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DATASETS:
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TRAIN: ("coco_2017_train_panoptic_stuffonly",)
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TEST: ("coco_2017_val_panoptic_stuffonly",)

projects/PointRend/configs/SemanticSegmentation/pointrend_semantic_R_50_FPN_1x_coco.yaml

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projects/PointRend/point_rend/semantic_seg.py

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class PointRendSemSegHead(nn.Module):
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"""
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A semantic segmentation head that combines a head set in `POINT_HEAD.COARSE_SEM_SEG_HEAD_NAME`
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and a point head set in `MODEL.POINT_HEAD.NAME`.
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and a point head set in `MODEL.POINT_HEAD.NAME`.
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"""
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def __init__(self, cfg, input_shape: Dict[str, ShapeSpec]):

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