Make the server actually work

server.py

@@ -62,6 +62,10 @@ class Server():
             setattr(processed, f'{name}_limited', limited_entry)
             setattr(processed, f'{name}_elmo', [[s.strip() for s in l] for l in raw])
 
+        processed.oov_to_limited_idx = self._oov_to_limited_idx
+        processed.limited_idx_to_full_idx = self._limited_idx_to_full_idx
+        return processed
+
     async def handle_client(self, client_reader, client_writer):
         try:
             request = json.loads(await client_reader.readline())
@@ -81,14 +85,14 @@ class Server():
             ex = Example.fromlist([context, question, answer, CONTEXT_SPECIAL, QUESTION_SPECIAL, context_question], fields, tokenize=tokenize)
             
             batch = self.numericalize_example(ex)
-            _, prediction_batch = model(batch)
+            _, prediction_batch = model(batch, iteration=0)
             
             if task == 'almond':
                 predictions = field.reverse(prediction_batch, detokenize=lambda x: ' '.join(x))
             else:
                 predictions = field.reverse(prediction_batch)
                 
-            await client_writer.writeln(json.dumps(dict(id=request['id'], answer=predictions[0])))
+            client_writer.write((json.dumps(dict(id=request['id'], answer=predictions[0])) + '\n').encode('utf-8'))
     
         except IOError:
             logger.info('Connection to client_reader closed')
@@ -142,7 +146,8 @@ def get_args():
                     'transformer_layers', 'rnn_layers', 'transformer_hidden', 
                     'dimension', 'load', 'max_val_context_length', 'val_batch_size', 
                     'transformer_heads', 'max_output_length', 'max_generative_vocab', 
-                    'lower', 'cove', 'intermediate_cove', 'elmo', 'glove_and_char', 'use_maxmargin_loss']
+                    'lower', 'cove', 'intermediate_cove', 'elmo', 'glove_and_char', 'use_maxmargin_loss',
+                    'reverse_task_bool']
         for r in retrieve:
             if r in config:
                 setattr(args, r,  config[r])
@@ -204,7 +209,7 @@ if __name__ == '__main__':
     model.load_state_dict(model_dict)
     
     server = Server(args, field, model)
-    server.prepare(args)
+    server.prepare_data()
     model.set_embeddings(field.vocab.vectors)
 
     server.run()