[EPLB]Eplb Config Renaming (#5533)

### What this PR does / why we need it?
1. Rename num_iterations_eplb_update to expert_heat_collection_interval.
2. Rename num_wait_worker_iterations to algorithm_execution_interval.
3. Rename init_redundancy_expert to num_redundant_experts because the
variable with the same meaning in vLLM is named this way.
4. Delete gate_eplb because we don't need this feature.
5. Move eplb config into a dict in additional config.
6. Depend on pr5817

### Does this PR introduce _any_ user-facing change?

before this pr：
`--additional-config '{"dynamic_eplb":true,
"num_iterations_eplb_update": 4000, "num_wait_worker_iterations": 150,
"init_redundancy_expert": 16, "expert_map_path": "xxx.json"}'`

after this pr: 
`--additional-config
'{"eplb_config":{"dynamic_eplb":true,"expert_heat_collection_interval":4000,
"algorithm_execution_interval":150,"num_redundant_experts": 16,
"expert_map_path": "xxx.json"}}'`

### How was this patch tested?

#### test qwen3-235b eplb num_redundant_experts=16

without pr5817
| dataset | version | metric | mode | vllm-api-general-chat |
|----- | ----- | ----- | ----- | -----|
| aime2024 | 604a78 | accuracy | gen | 83.33 |

with pr5817
| dataset | version | metric | mode | vllm-api-general-chat |
|----- | ----- | ----- | ----- | -----|
| aime2024 | 604a78 | accuracy | gen | 86.67 |

- vLLM version: v0.13.0
- vLLM main:
45c1ca1ca1

Signed-off-by: shenchuxiaofugui <1311027364@qq.com>

vllm_ascend/worker/model_runner_v1.py

@@ -91,7 +91,6 @@ from vllm_ascend.compilation.acl_graph import (ACLGraphWrapper,
 from vllm_ascend.eplb.adaptor.vllm_adaptor import VllmEplbAdaptor
 from vllm_ascend.eplb.core.eplb_device_transfer_loader import \
     D2DExpertWeightLoader
-from vllm_ascend.eplb.core.eplb_utils import EPLBParamUtils
 from vllm_ascend.eplb.core.eplb_worker import EplbProcess
 from vllm_ascend.eplb.eplb_updator import EplbUpdator
 from vllm_ascend.eplb.utils import model_register
@@ -290,13 +289,11 @@ class NPUModelRunner(GPUModelRunner):
 
         self.use_aclgraph = self._use_aclgraph()
 
-        self.dynamic_eplb = self.ascend_config.dynamic_eplb or self.ascend_config.expert_map_record_path
+        eplb_config = self.ascend_config.eplb_config
+        self.dynamic_eplb = eplb_config.dynamic_eplb
         if self.dynamic_eplb:
-            EPLBParamUtils.check_dynamic_eplb(self.ascend_config.dynamic_eplb)
-            EPLBParamUtils.check_expert_map_record_path(
-                self.ascend_config.expert_map_record_path)
             self.is_eplb_warmuped = False
-            self.policy_type = self.ascend_config.eplb_policy_type
+            self.policy_type = eplb_config.eplb_policy_type
             self.eplb_loader = D2DExpertWeightLoader()
             self.manager = Manager()
             self.shared_dict = self.manager.dict({
@@ -308,8 +305,7 @@ class NPUModelRunner(GPUModelRunner):
                                             policy_type=self.policy_type,
                                             enable_d2d=True)
             self.process = self.eplb_process._launch_process()
-            ascend_config = get_ascend_config()
-            self.eplb_updator = EplbUpdator(ascend_config, self.eplb_loader,
+            self.eplb_updator = EplbUpdator(eplb_config, self.eplb_loader,
                                             self.eplb_process, self.process)
         # Input Batch
         # NOTE(Chen): Ideally, we should initialize the input batch inside