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import argparse
import torch
import os
from models.exaonepath import EXAONEPathV1p5Downstream
from utils.constants import CLASS_NAMES
from tokens import HF_TOKEN
def infer(model, input_file):
print("Processing", input_file, "...")
probs = model(input_file)
result_str = "Result -- " + " / ".join(
[f"{name}: {probs[i].item():.4f}" for i, name in enumerate(CLASS_NAMES)]
)
print(result_str + "\n")
if __name__ == '__main__':
parser = argparse.ArgumentParser(description="Inference")
parser.add_argument('--svs_dir', type=str, default='./samples', help="")
args = parser.parse_args()
hf_token = HF_TOKEN
model = EXAONEPathV1p5Downstream.from_pretrained("LGAI-EXAONE/EXAONE-Path-1.5", use_auth_token=hf_token)
model.load_state_dict(torch.load('./pytorch_model.bin'))
model.to(torch.device("cuda" if torch.cuda.is_available() else "cpu"))
model.eval()
model.feature_extractor = torch.compile(model.feature_extractor)
model.agg_model = torch.compile(model.agg_model)
for svs_name in os.listdir(args.svs_dir):
infer(model, os.path.join(args.svs_dir, svs_name))
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