diff --git a/main_custom.py b/main_custom.py index 514c0bcc85ce59048599adced37e45518b53f384..ecbb936ed2eb0522850f276a07d737c115d1a554 100644 --- a/main_custom.py +++ b/main_custom.py @@ -281,8 +281,8 @@ def save_pred(model, data_val, forward, output_path, file = False): pred_rt, pred_int, seqs, charges, true_rt, true_int, file_list = [], [], [], [], [], [], [] if file: data_val.dataset.set_file_mode(True) - for seq, charge, rt, intensity, file in data_val: - rt, intensity = rt.float(), intensity.float() + for seq, charge, rt, intensity, file in data_val: + rt, intensity = rt.float(), intensity.float() if torch.cuda.is_available(): seq, charge, rt, intensity = seq.cuda(), charge.cuda(), rt.cuda(), intensity.cuda() pr_rt, pr_intensity = model.forward(seq, charge) @@ -293,13 +293,27 @@ def save_pred(model, data_val, forward, output_path, file = False): true_rt.extend(rt.data.cpu().tolist()) true_int.extend(intensity.data.cpu().tolist()) file_list.extend([file]) + else : + for seq, charge, rt, intensity in data_val: + rt, intensity = rt.float(), intensity.float() + if torch.cuda.is_available(): + seq, charge, rt, intensity = seq.cuda(), charge.cuda(), rt.cuda(), intensity.cuda() + pr_rt, pr_intensity = model.forward(seq, charge) + pred_rt.extend(pr_rt.data.cpu().tolist()) + pred_int.extend(pr_intensity.data.cpu().tolist()) + seqs.extend(seq.data.cpu().tolist()) + charges.extend(charge.data.cpu().tolist()) + true_rt.extend(rt.data.cpu().tolist()) + true_int.extend(intensity.data.cpu().tolist()) + data_frame['rt pred'] = pred_rt data_frame['seq'] = seqs data_frame['pred int'] = pred_int data_frame['true rt'] = true_rt data_frame['true int'] = true_int data_frame['charge'] = charges - data_frame['file'] = file_list + if file : + data_frame['file'] = file_list