Duplicate key is not allowed among bases

[YananGu]

您好， 我在运行代码时出现了以下错误：

发生异常: KeyError "Duplicate key is not allowed among bases. Duplicate keys: {'evaluation'}" File "/mnt/data/ViT-Adapter/detection/train.py", line 91, in main cfg = Config.fromfile(args.config) File "/mnt/data/ViT-Adapter/detection/train.py", line 192, in main() KeyError: "Duplicate key is not allowed among bases. Duplicate keys: {'evaluation'}"

请问您遇到过这种错误吗，有什么解决的办法吗？

[duanduanduanyuchen]

看起来是config文件写错了，可能是base文件中的evaluation有重复之类的，你可以把config文件发出来看看吗？

[YananGu]

@duanduanduanyuchen 我没改配置文件，就是按照原代码跑的。。

    '../_base_/models/mask_rcnn_r50_fpn.py',
    '../_base_/datasets/coco_instance.py',
    '../_base_/schedules/schedule_3x.py',
    '../_base_/default_runtime.py'
]
# pretrained = 'https://dl.fbaipublicfiles.com/deit/deit_tiny_patch16_224-a1311bcf.pth'
pretrained = 'pretrained/deit_tiny_patch16_224-a1311bcf.pth'
model = dict(
    backbone=dict(
        _delete_=True,
        type='ViTAdapter',
        patch_size=16,
        embed_dim=192,
        depth=12,
        num_heads=3,
        mlp_ratio=4,
        drop_path_rate=0.1,
        conv_inplane=64,
        n_points=4,
        deform_num_heads=6,
        cffn_ratio=0.25,
        deform_ratio=1.0,
        interaction_indexes=[[0, 2], [3, 5], [6, 8], [9, 11]],
        window_attn=[True, True, False, True, True, False,
                     True, True, False, True, True, False],
        window_size=[14, 14, None, 14, 14, None,
                     14, 14, None, 14, 14, None],
        pretrained=pretrained),
    neck=dict(
        type='FPN',
        in_channels=[192, 192, 192, 192],
        out_channels=256,
        num_outs=5))
# optimizer
img_norm_cfg = dict(
    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
# augmentation strategy originates from DETR / Sparse RCNN
train_pipeline = [
    dict(type='LoadImageFromFile'),
    dict(type='LoadAnnotations', with_bbox=True, with_mask=True),
    dict(type='RandomFlip', flip_ratio=0.5),
    dict(type='AutoAugment',
         policies=[
             [
                 dict(type='Resize',
                      img_scale=[(480, 1333), (512, 1333), (544, 1333), (576, 1333),
                                 (608, 1333), (640, 1333), (672, 1333), (704, 1333),
                                 (736, 1333), (768, 1333), (800, 1333)],
                      multiscale_mode='value',
                      keep_ratio=True)
             ],
             [
                 dict(type='Resize',
                      img_scale=[(400, 1333), (500, 1333), (600, 1333)],
                      multiscale_mode='value',
                      keep_ratio=True),
                 dict(type='RandomCrop',
                      crop_type='absolute_range',
                      crop_size=(384, 600),
                      allow_negative_crop=True),
                 dict(type='Resize',
                      img_scale=[(480, 1333), (512, 1333), (544, 1333),
                                 (576, 1333), (608, 1333), (640, 1333),
                                 (672, 1333), (704, 1333), (736, 1333),
                                 (768, 1333), (800, 1333)],
                      multiscale_mode='value',
                      override=True,
                      keep_ratio=True)
             ]
         ]),
    dict(type='RandomCrop',
         crop_type='absolute_range',
         crop_size=(1024, 1024),
         allow_negative_crop=True),
    dict(type='Normalize', **img_norm_cfg),
    dict(type='Pad', size_divisor=32),
    dict(type='DefaultFormatBundle'),
    dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels', 'gt_masks']),
]
data = dict(train=dict(pipeline=train_pipeline))
optimizer = dict(
    _delete_=True, type='AdamW', lr=0.0001, weight_decay=0.05,
    paramwise_cfg=dict(
    custom_keys={
        'level_embed': dict(decay_mult=0.),
        'pos_embed': dict(decay_mult=0.),
        'norm': dict(decay_mult=0.),
        'bias': dict(decay_mult=0.)
    }))
optimizer_config = dict(grad_clip=None)
fp16 = dict(loss_scale=dict(init_scale=512))
checkpoint_config = dict(
    interval=1,
    max_keep_ckpts=3,
    save_last=True,
)

[duanduanduanyuchen]

确实是base文件中的evaluation这个key有重复： ViT-Adapter/detection/configs/_base_/datasets/coco_instance.py和ViT-Adapter/detection/configs/_base_/default_runtime.py 这两个文件中都有evaluation这个变量，你可以把default_runtime.py中的evaluation = dict(save_best='auto')去掉，或者挪到你的这个config文件中来

[YananGu]

非常感谢你！问题解决了！