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_base_ = [ |
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'../_base_/models/san_vit-b16.py', |
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'../_base_/datasets/pascal_context_59.py', '../_base_/default_runtime.py', |
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'../_base_/schedules/schedule_160k.py' |
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] |
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crop_size = (640, 640) |
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|
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test_pipeline = [ |
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dict(type='LoadImageFromFile'), |
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dict(type='ResizeShortestEdge', scale=crop_size, max_size=2560), |
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dict(type='LoadAnnotations'), |
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dict(type='PackSegInputs') |
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] |
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|
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train_dataloader = dict(batch_size=2) |
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val_dataloader = dict(batch_size=1, dataset=dict(pipeline=test_pipeline)) |
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test_dataloader = val_dataloader |
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|
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data_preprocessor = dict( |
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mean=[122.7709, 116.7460, 104.0937], |
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std=[68.5005, 66.6322, 70.3232], |
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size_divisor=640, |
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test_cfg=dict(size_divisor=32)) |
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model = dict( |
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data_preprocessor=data_preprocessor, |
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pretrained='pretrain/vit_base_patch16_224.pth', |
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text_encoder=dict(dataset_name='pascal_context'), |
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decode_head=dict(num_classes=59)) |
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|
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optim_wrapper = dict( |
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_delete_=True, |
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type='OptimWrapper', |
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optimizer=dict( |
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type='AdamW', lr=0.00006, betas=(0.9, 0.999), weight_decay=0.01), |
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paramwise_cfg=dict( |
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custom_keys={ |
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'pos_embed': dict(decay_mult=0.), |
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'cls_token': dict(decay_mult=0.), |
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'norm': dict(decay_mult=0.) |
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})) |
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|
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param_scheduler = [ |
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dict( |
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type='LinearLR', start_factor=1e-6, by_epoch=False, begin=0, end=1500), |
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dict( |
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type='PolyLR', |
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eta_min=0.0, |
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power=1.0, |
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begin=1500, |
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end=160000, |
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by_epoch=False, |
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) |
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] |
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