import sys

sys.path.append('.')

import torch

from torch.nn import functional as F

import os

import yaml

from src.new_grad_cam import gc

def test(conf):

    device = conf['device']

    dataset = conf['test_dataset']

    classes = conf['data']['classes']

    weights_path = conf['weights_path']

    results_dir = conf['results_dir']

    model = conf['model']

    model.load_state_dict(torch.load(weights_path))

    model = model.to(device)

    model.eval()

    gc(model=model,

       dataset=dataset,

       results_dir=results_dir,

       classes=classes,

       device=device)

if __name__ == '__main__':

    from config import get_config

    conf = get_config('./conf/testing.yaml')

    test(conf)