[long_seq] remove long_seq env (#4660)

### What this PR does / why we need it?
remove env VLLM_ASCEND_ENABLE_CONTEXT_PARALLEL 

- vLLM version: v0.12.0

---------

Signed-off-by: LookAround <lixushi@huawei.com>
Signed-off-by: ZhangMingWei716 <2894054457@qq.com>
Co-authored-by: ZhangMingWei716 <2894054457@qq.com>
Co-authored-by: wangxiyuan <wangxiyuan1007@gmail.com>

vllm_ascend/distributed/parallel_state.py

@@ -9,8 +9,7 @@ from vllm.distributed.parallel_state import (GroupCoordinator, get_dp_group,
 
 import vllm_ascend.envs as envs_ascend
 from vllm_ascend.ascend_config import get_ascend_config
-from vllm_ascend.utils import (flashcomm2_enable,
-                               prefill_context_parallel_enable)
+from vllm_ascend.utils import flashcomm2_enable
 
 # Currently, mc2 op need their own group coordinator.
 _MC2: Optional[GroupCoordinator] = None
@@ -74,15 +73,10 @@ def init_ascend_model_parallel(parallel_config: ParallelConfig, ):
     # The layout of all ranks: ExternalDP * EP
     # ExternalDP is the data parallel group that is not part of the model,
     # every dp rank can generate independently (in verl integration).
-    if prefill_context_parallel_enable():
-        all_ranks = torch.arange(world_size).reshape(
-            -1, parallel_config.data_parallel_size *
-            parallel_config.prefill_context_parallel_size *
-            parallel_config.tensor_parallel_size)
-    else:
-        all_ranks = torch.arange(world_size).reshape(
-            -1, parallel_config.data_parallel_size *
-            parallel_config.tensor_parallel_size)
+    all_ranks = torch.arange(world_size).reshape(
+        -1, parallel_config.data_parallel_size *
+        parallel_config.prefill_context_parallel_size *
+        parallel_config.tensor_parallel_size)
 
     pd_tp_ratio = get_ascend_config().pd_tp_ratio
     pd_head_ratio = get_ascend_config().pd_head_ratio