help='Batch size')
parser.add_argument('-n_best', type=int, default=1,
help="""If verbose is set, will output the n_best decoded sentences""")
parser.add_argument('-no_cuda', action='store_true')
opt = parser.parse_args()
opt.cuda = not opt.no_cuda
# Prepare DataLoader
data = torch.load(opt.src)
data['settings'].cuda = opt.cuda
# Create Translator Model
translator = Summarizer(opt)
# Create Tokenizer
tokenizer = FullTokenizer(opt.vocab)
@app.route('/', methods=['POST'])
def summarization():
json_data = request.get_json()
data_loader = preprocess(json_data)
summaries = summarize(data_loader)
summaries = remove_symbol(summaries)
return jsonify({
'summaries': summaries,
})