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| import os | |
| import torch | |
| import torch.nn as nn | |
| import torch.optim as optim | |
| import torch.distributed as dist | |
| import torch.multiprocessing as mp | |
| import torchvision.models as models | |
| from torch.utils.data import Dataset | |
| from torch.nn.parallel import DistributedDataParallel as DDP | |
| from torch.utils.data.distributed import DistributedSampler |
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| """Minimal, self-contained reproduction of the FloorSet-Lite MIB inconsistency. | |
| MIB (Multiple-Instantiation Block) requires every member of a group to share IDENTICAL (w,h) | |
| dimensions -- which forces an identical area. This script proves, straight from IntelLabs' published | |
| data (no project code on the train path), that the TRAIN set assigns members of one MIB group | |
| DIFFERENT target areas, so the MIB constraint is unsatisfiable by construction. It then runs the exact | |
| same check on the VAL set, which is clean -- demonstrating the check is correct and the bug is in the | |
| train data, not the check. | |
| Raw layout tensor layout (FloorSet-Lite): ``c[0][i]`` is ``[n,6]`` with column 0 = target area and |
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