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| from .clip_vit import CLIPViT |
| from .intern_vit_6b import InternViT6B |
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| def build_model(config): |
| model_type = config.MODEL.TYPE |
| if model_type == 'intern_vit_6b': |
| model = InternViT6B( |
| num_classes=config.MODEL.NUM_CLASSES, |
| patch_size=config.MODEL.INTERN_VIT_6B.PATCH_SIZE, |
| img_size=config.DATA.IMG_SIZE, |
| pretrain_size=config.MODEL.INTERN_VIT_6B.PRETRAIN_SIZE, |
| qkv_bias=config.MODEL.INTERN_VIT_6B.QKV_BIAS, |
| drop_path_rate=config.MODEL.DROP_PATH_RATE, |
| embed_dim=config.MODEL.INTERN_VIT_6B.EMBED_DIM, |
| num_heads=config.MODEL.INTERN_VIT_6B.NUM_HEADS, |
| mlp_ratio=config.MODEL.INTERN_VIT_6B.MLP_RATIO, |
| init_values=config.MODEL.INTERN_VIT_6B.INIT_VALUES, |
| qk_normalization=config.MODEL.INTERN_VIT_6B.QK_NORMALIZATION, |
| depth=config.MODEL.INTERN_VIT_6B.DEPTH, |
| use_flash_attn=config.MODEL.INTERN_VIT_6B.USE_FLASH_ATTN, |
| with_cp=config.TRAIN.USE_CHECKPOINT, |
| freeze_vit=config.MODEL.INTERN_VIT_6B.FREEZE_VIT, |
| pretrained=config.MODEL.INTERN_VIT_6B.PRETRAINED, |
| cls_target=config.MODEL.INTERN_VIT_6B.CLS_TARGET, |
| norm_type=config.MODEL.INTERN_VIT_6B.NORM_TYPE, |
| ) |
| elif model_type == 'clip_vit': |
| model = CLIPViT( |
| patch_size=config.MODEL.CLIP_VIT.PATCH_SIZE, |
| img_size=config.DATA.IMG_SIZE, |
| pretrain_size=config.MODEL.CLIP_VIT.PRETRAIN_SIZE, |
| embed_dim=config.MODEL.CLIP_VIT.EMBED_DIM, |
| num_heads=config.MODEL.CLIP_VIT.NUM_HEADS, |
| mlp_ratio=config.MODEL.CLIP_VIT.MLP_RATIO, |
| depth=config.MODEL.CLIP_VIT.DEPTH, |
| with_cp=config.TRAIN.USE_CHECKPOINT, |
| freeze_vit=config.MODEL.CLIP_VIT.FREEZE_VIT, |
| pretrained=config.MODEL.CLIP_VIT.PRETRAINED, |
| cls_target=config.MODEL.CLIP_VIT.CLS_TARGET, |
| ) |
| else: |
| raise NotImplementedError(f'Unkown model: {model_type}') |
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| return model |
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