fix typ and parameter description

Author: YeAnbang

applications/ColossalChat/rl_example.py

@@ -126,25 +126,25 @@
         "--tensor-parallel-size",
         type=int,
         default=1,
-        help="Tensor parallel size for the inference backend. Please check the generation arguments documentation for your backend.",
+        help="Tensor parallel size for the trainer (consumer). Please check the generation arguments documentation for your backend.",
     )
     parser.add_argument(
         "-pp",
         "--pipeline-parallel-size",
         type=int,
         default=1,
-        help="Pipeline parallel size for the inference backend. Please check the generation arguments documentation for your backend.",
+        help="Pipeline parallel size for the trainer (consumer). Please check the generation arguments documentation for your backend.",
     )
     parser.add_argument(
         "-zero",
         "--zero-stage",
         type=int,
         default=0,
-        help="Zero stage for the inference backend. Please check the generation arguments documentation for your backend.",
+        help="Zero stage for the trainer (consumer). Please check the generation arguments documentation for your backend.",
     )
     parser.add_argument(
         "-ptp",
-        "--produce-tensor-parallel-size",
+        "--producer-tensor-parallel-size",
         type=int,
         default=1,
         help="Tensor parallel size for the producer. Please check the generation arguments documentation for your backend.",
@@ -206,7 +206,7 @@
                 enforce_eager=True,
                 enable_chunked_prefill=True,
                 max_model_len=args.max_new_tokens + args.max_prompt_tokens,
-                tensor_parallel_size=args.produce_tensor_parallel_size,
+                tensor_parallel_size=args.producer_tensor_parallel_size,
             )
         )
         generate_config.update(
@@ -276,7 +276,7 @@
 
     launch_distributed(
         num_producers=args.num_inferencer,
-        num_proc_per_producer=inference_model_config.get("tensor_parallel_size", args.produce_tensor_parallel_size),
+        num_proc_per_producer=inference_model_config.get("tensor_parallel_size", args.producer_tensor_parallel_size),
         num_consumer_procs=args.num_trainers,
         num_episodes=args.num_episodes,
         inference_batch_size=args.inference_batch_size,