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import torch
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import torch.nn as nn
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from transformers import CLIPVisionModel, CLIPImageProcessor, CLIPVisionConfig
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from CKPT_PTH import LLAVA_CLIP_PATH
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class CLIPVisionTower(nn.Module):
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def __init__(self, vision_tower, args, delay_load=False):
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super().__init__()
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self.is_loaded = False
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self.vision_tower_name = vision_tower
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print(f'Loading vision tower: {self.vision_tower_name}')
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self.select_layer = args.mm_vision_select_layer
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self.select_feature = getattr(args, 'mm_vision_select_feature', 'patch')
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if not delay_load:
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self.load_model()
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else:
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self.cfg_only = CLIPVisionConfig.from_pretrained(
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self.vision_tower_name if LLAVA_CLIP_PATH is None else LLAVA_CLIP_PATH)
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def load_model(self):
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self.image_processor = CLIPImageProcessor.from_pretrained(
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self.vision_tower_name if LLAVA_CLIP_PATH is None else LLAVA_CLIP_PATH)
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self.vision_tower = CLIPVisionModel.from_pretrained(
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self.vision_tower_name if LLAVA_CLIP_PATH is None else LLAVA_CLIP_PATH)
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self.vision_tower.requires_grad_(False)
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self.is_loaded = True
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def feature_select(self, image_forward_outs):
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image_features = image_forward_outs.hidden_states[self.select_layer]
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if self.select_feature == 'patch':
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image_features = image_features[:, 1:]
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elif self.select_feature == 'cls_patch':
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image_features = image_features
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else:
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raise ValueError(f'Unexpected select feature: {self.select_feature}')
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return image_features
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@torch.no_grad()
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def forward(self, images):
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if type(images) is list:
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image_features = []
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for image in images:
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image_forward_out = self.vision_tower(image.to(device=self.device, dtype=self.dtype).unsqueeze(0), output_hidden_states=True)
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image_feature = self.feature_select(image_forward_out).to(image.dtype)
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image_features.append(image_feature)
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else:
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image_forward_outs = self.vision_tower(images.to(device=self.device, dtype=self.dtype), output_hidden_states=True)
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image_features = self.feature_select(image_forward_outs).to(images.dtype)
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return image_features
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@property
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def dummy_feature(self):
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return torch.zeros(1, self.hidden_size, device=self.device, dtype=self.dtype)
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@property
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def dtype(self):
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return self.vision_tower.dtype
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@property
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def device(self):
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return self.vision_tower.device
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@property
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def config(self):
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if self.is_loaded:
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return self.vision_tower.config
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else:
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return self.cfg_only
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@property
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def hidden_size(self):
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return self.config.hidden_size
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@property
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def num_patches(self):
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return (self.config.image_size // self.config.patch_size) ** 2
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