| ''' |
| CopyRight @DeepGlint 2025 |
| ''' |
|
|
|
|
| import torch |
| import torch.nn as nn |
| from transformers import CLIPVisionModel, CLIPImageProcessor, CLIPVisionConfig |
|
|
|
|
| def build_vision_tower(model_cfg, **kwargs): |
| vision_tower = getattr(model_cfg, "vision_tower_config", getattr(model_cfg, "vision_tower", None)) |
| return CLIPVisionTower(vision_tower, args=model_cfg, **kwargs) |
|
|
|
|
| class CLIPVisionTower(nn.Module): |
| def __init__(self, vision_tower, args, delay_load=False): |
| super().__init__() |
|
|
| self.is_loaded = False |
|
|
| self.vision_tower_cfg = vision_tower |
| self.vision_tower_processor = args.vision_tower_processor |
| self.select_layer = args.mm_vision_select_layer |
| self.select_feature = getattr(args, "mm_vision_select_feature", "patch") |
|
|
| if not delay_load: |
| self.init_model() |
| elif getattr(args, "unfreeze_mm_vision_tower", False): |
| |
| self.init_model() |
| elif hasattr(args, "mm_tunable_parts") and "mm_vision_tower" in args.mm_tunable_parts: |
| self.init_model() |
| else: |
| raise RuntimeError("Not support now, please check config.json or contact us") |
|
|
| def init_model(self, device_map=None): |
| if self.is_loaded: |
| return |
| vision_tower_config = CLIPVisionConfig().from_dict(self.vision_tower_cfg) |
| self.image_processor = CLIPImageProcessor(**self.vision_tower_processor) |
| self.vision_tower = CLIPVisionModel(config=vision_tower_config) |
| self.vision_tower.requires_grad_(False) |
|
|
| self.is_loaded = True |
|
|
| def feature_select(self, image_forward_outs): |
| select_feature_type = self.select_feature |
|
|
| if self.select_feature in ["slicefour_patch", "slicefour_cls_patch"]: |
| select_every_k_layer = len(image_forward_outs.hidden_states) // 4 |
| image_features = torch.cat([image_forward_outs.hidden_states[i] for i in range(select_every_k_layer + self.select_layer, len(image_forward_outs.hidden_states), select_every_k_layer)], dim=-1) |
| select_feature_type = select_feature_type.replace("slicefour_", "") |
| elif self.select_feature in ["slice_m25811_f6_patch", "slice_m25811_f6_cls_patch"]: |
| select_layers = [-2, -5, -8, -11, 6] |
| image_features = torch.cat([image_forward_outs.hidden_states[i] for i in select_layers], dim=-1) |
| select_feature_type = select_feature_type.replace("slice_m25811_f6_", "") |
| else: |
| image_features = image_forward_outs.hidden_states[self.select_layer] |
|
|
| if select_feature_type == "patch": |
| image_features = image_features[:, 1:] |
| elif select_feature_type == "cls_patch": |
| image_features = image_features |
| else: |
| raise ValueError(f"Unexpected select feature: {select_feature_type}") |
| return image_features |
|
|
| def forward(self, images): |
| if type(images) is list: |
| image_features = [] |
| for image in images: |
| image_forward_out = self.vision_tower(image.to(device=self.device, dtype=self.dtype).unsqueeze(0), output_hidden_states=True) |
| image_feature = self.feature_select(image_forward_out).to(image.dtype) |
| image_features.append(image_feature) |
| else: |
| image_forward_outs = self.vision_tower(images.to(device=self.device, dtype=self.dtype), output_hidden_states=True) |
| image_features = self.feature_select(image_forward_outs).to(images.dtype) |
|
|
| return image_features |
|
|
| @property |
| def dummy_feature(self): |
| return torch.zeros(1, self.hidden_size, device=self.device, dtype=self.dtype) |
|
|
| @property |
| def dtype(self): |
| return self.vision_tower.dtype |
|
|
| @property |
| def device(self): |
| return self.vision_tower.device |
|
|
| @property |
| def config(self): |
| if self.is_loaded: |
| return self.vision_tower.config |
| else: |
| return self.cfg_only |
|
|
| @property |
| def hidden_size(self): |
| _hidden_size = self.config.hidden_size |
| if "slicefour" in self.select_feature: |
| _hidden_size *= 4 |
| if "slice_m25811_f6" in self.select_feature: |
| _hidden_size *= 5 |
| return _hidden_size |
|
|
| @property |
| def num_patches_per_side(self): |
| return self.config.image_size // self.config.patch_size |
|
|
| @property |
| def num_patches(self): |
| _num_patches = (self.config.image_size // self.config.patch_size) ** 2 |
| if "cls_patch" in self.select_feature: |
| _num_patches += 1 |
| return _num_patches |
|
|
| @property |
| def image_size(self): |
| return self.config.image_size |
