[feat] support HyperParallel Context Parallel feature (#10559)

Co-authored-by: wcrzlh <weichaoran@huawei.com>

src/llamafactory/hparams/finetuning_args.py

@@ -500,6 +500,10 @@ class FinetuningArguments(
             )
         },
     )
+    hyper_parallel_cp_size: int = field(
+        default=1,
+        metadata={"help": "Context parallel size used when `use_hyper_parallel=True`."},
+    )
     use_muon: bool = field(
         default=False,
         metadata={"help": "Whether or not to use the Muon optimizer."},
@@ -576,6 +580,7 @@ class FinetuningArguments(
         assert self.finetuning_type in ["lora", "oft", "freeze", "full"], "Invalid fine-tuning method."
         assert self.ref_model_quantization_bit in [None, 8, 4], "We only accept 4-bit or 8-bit quantization."
         assert self.reward_model_quantization_bit in [None, 8, 4], "We only accept 4-bit or 8-bit quantization."
+        assert self.hyper_parallel_cp_size > 0, "`hyper_parallel_cp_size` must be greater than 0."
 
         if self.stage == "ppo" and self.reward_model is None:
             raise ValueError("`reward_model` is necessary for PPO training.")