import numpy as np 

import torch

from src.utils import calculate_metrics

def hybrid_test_results(model, hybrid_test_loader, icdtype, device):

  model.eval()

  with torch.no_grad():

    model_result = []

    targets = []

    for rnn_x, cnn_x, batch_targets in hybrid_test_loader:

      rnn_x = rnn_x.to(device)

      cnn_x = cnn_x.to(device)

      model_batch_result = model(rnn_x, cnn_x)

      model_result.extend(model_batch_result.cpu().numpy())

      targets.extend(batch_targets[icdtype].cpu().numpy())

  result = calculate_metrics(np.array(model_result), np.array(targets))

  print('-'*10 + icdtype + '-'*10)

  print(result)