mmpretrain/configs/_base_/models/vgg19bn.py

# model settings
model = dict(
    type='ImageClassifier',
    backbone=dict(
        type='VGG', depth=19, norm_cfg=dict(type='BN'), num_classes=1000),
    neck=None,
    head=dict(
        type='ClsHead',
        loss=dict(type='CrossEntropyLoss', loss_weight=1.0),
        topk=(1, 5),
    ))
Add VGG and pretained models (#27) * add vgg * add vgg model coversion tool * fix out_indices and docstr * add vgg models in configs * add params, flops and accuracy in docs * add pretrained models url * use ConvModule and refine var names * update vgg conversion tool * modify bn config * add docs for arch_setting * add unit test for vgg * rm debug code * update vgg pretrained models 2020-09-29 17:49:42 +08:00			`# model settings`
			`model = dict(`
			`type='ImageClassifier',`
			`backbone=dict(`
			`type='VGG', depth=19, norm_cfg=dict(type='BN'), num_classes=1000),`
			`neck=None,`
			`head=dict(`
			`type='ClsHead',`
			`loss=dict(type='CrossEntropyLoss', loss_weight=1.0),`
			`topk=(1, 5),`
			`))`