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import torch
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import torch.nn as nn
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from .eva_clip_processors import EvaClipImageTrainProcessor
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from .eva_vit import EVAEncoderWrapper
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from .factory import list_models, add_model_config, get_model_config
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from llava.utils import rank0_print
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class EvaClipVisionTower(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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self.vision_tower_pretrained = args.vision_tower_pretrained
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self.config = get_model_config(vision_tower)
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if not delay_load:
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rank0_print(f"Loading EVA ViT: {self.vision_tower_name}")
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self.load_model()
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elif getattr(args, "unfreeze_mm_vision_tower", False):
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rank0_print(f"The checkpoint seems to contain `vision_tower` weights: `unfreeze_mm_vision_tower`: True.")
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self.load_model()
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elif hasattr(args, "mm_tunable_parts") and "mm_vision_tower" in args.mm_tunable_parts:
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rank0_print(f"The checkpoint seems to contain `vision_tower` weights: `mm_tunable_parts` contains `mm_vision_tower`.")
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self.load_model()
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else:
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self.cfg_only = self.config
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def load_model(self, device_map=None):
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rank0_print(f"Pretrained: {self.vision_tower_pretrained}")
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self.image_processor = EvaClipImageTrainProcessor(self.config["vision_cfg"]["image_size"])
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self.vision_tower = EVAEncoderWrapper(self.vision_tower_pretrained, self.config)
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rank0_print(f"Loaded image processor: {self.image_processor}")
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self.vision_tower.requires_grad_(False)
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self.is_loaded = True
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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_feature = self.vision_tower(image.to(device=self.device, dtype=self.dtype).unsqueeze(0)).to(image.dtype)
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image_features.append(image_feature)
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else:
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image_features = self.vision_tower(images.to(device=self.device, dtype=self.dtype)).to(images.dtype)
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return image_features
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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 hidden_size(self):
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return self.config["vision_cfg"]["width"]
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@property
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def num_patches(self):
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return (self.config["vision_cfg"]["image_size"] // self.config["vision_cfg"]["patch_size"]) ** 2
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@property
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def num_patches_per_side(self):
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return self.config["vision_cfg"]["image_size"] // self.config["vision_cfg"]["patch_size"]
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@property
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def image_size(self):
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return self.config["vision_cfg"]["image_size"]
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