if is_cuda: device = torch.device("cuda") deviceStr = "cuda" print("GPU is available") else: device = torch.device("cpu") print("GPU not available, CPU used") print("Using device {}.".format(device)) torch.manual_seed(args.seed) dataset = Dataset(args.data_dir) train_loader = dataset.getDatasetTrain(args.batch_size) test_loader = dataset.getDatasetTest(args.batch_size) val_loader = dataset.getDataValid(args.batch_size) dictionary = dataset.getDictionaryFromS3(args.dictionary_file_name) modelConfig = { "embedding_dim" : args.embedding_dim, "hidden_dim" : args.hidden_dim, "vocab_size" : args.vocab_size, "output_size" : args.output_size, "n_layers" : args.n_layers, "device" : deviceStr, "batch_size" : args.batch_size, } model_cfg = os.path.join(args.model_dir, 'model.cfg')