import sys
import torch
from model import AevanisVisionBackbone

if sys.stdout.encoding and sys.stdout.encoding.lower() != 'utf-8':
    try:
        sys.stdout.reconfigure(encoding='utf-8')
    except Exception:
        pass

# 1. Load Pre-Trained Weights
model = AevanisVisionBackbone.from_pretrained("pytorch_model.bin", model_scale="core")
model.eval()

# 2. Single 224x224 RGB Image Input
dummy_input = torch.randn(1, 3, 224, 224)

# 3. Extract Representations
with torch.no_grad():
    features = model(dummy_input)

print("[INFO] CLS Token Embedding :", features["cls_token"].shape)      # [1, 384]
print("[INFO] Spatial 14x14 Grid  :", features["spatial_tokens"].shape) # [1, 196, 384]
print("[SUCCESS] Aevanis Vision Core Backbone inference completed without error.")