feat: initialize project with Python 3.10 and feature retrieval module

mini-nav/feature_retrieval.py

@@ -0,0 +1,37 @@
+from typing import cast
+import torch
+from tqdm.auto import tqdm
+from datasets import Dataset, load_dataset
+from transformers import AutoImageProcessor, AutoModel
+
+
+@torch.no_grad()
+def establish_database(processor, model, images, batch_size=64):
+    device = model.device
+    model.eval()
+
+    for i in tqdm(range(0, len(images), batch_size)):
+        batch = images[i : i + batch_size]
+
+        inputs = processor(images=batch, return_tensors="pt")
+
+        # 迁移数据到GPU
+        inputs.to(device, non_blocking=True)
+
+        outputs = model(**inputs)
+        feats = outputs.last_hidden_state  # [B, N, D]
+        # 后处理 / 存库
+
+        
+
+
+if __name__ == "__main__":
+    train_dataset = load_dataset("uoft-cs/cifar10", split="train")
+    train_dataset = cast(Dataset, train_dataset)
+
+    processor = AutoImageProcessor.from_pretrained(
+        "facebook/dinov2-large", device_map="cuda"
+    )
+    model = AutoModel.from_pretrained("facebook/dinov2-large", device_map="cuda")
+
+    establish_database(processor, model, train_dataset["img"])