[Distributed] Add enable_expert_parallel arg (#14305)

Signed-off-by: Tyler Michael Smith <tyler@neuralmagic.com>

vllm/envs.py

@@ -86,7 +86,6 @@ if TYPE_CHECKING:
     VLLM_MLA_PERFORM_MATRIX_ABSORPTION: bool = True
     VLLM_MLA_DISABLE_REQUANTIZATION: bool = False
     VLLM_MLA_CUDA_MEM_ALIGN_KV_CACHE: bool = True
-    VLLM_TEST_ENABLE_EP: bool = False
     VLLM_ENABLE_MOE_ALIGN_BLOCK_SIZE_TRITON: bool = False
     VLLM_RAY_PER_WORKER_GPUS: float = 1.0
     VLLM_RAY_BUNDLE_INDICES: str = ""
@@ -579,12 +578,6 @@ environment_variables: dict[str, Callable[[], Any]] = {
     lambda: bool(int(os.getenv("VLLM_ENABLE_MOE_ALIGN_BLOCK_SIZE_TRITON", "0"))
                  ),
 
-    # If set, vLLM will use the experimental expert parallel implementation on
-    # the FusedMoE layer, using tensor parallelism size as expert parallelism
-    # size.
-    "VLLM_TEST_ENABLE_EP":
-    lambda: bool(int(os.getenv("VLLM_TEST_ENABLE_EP", "0"))),
-
     # Number of GPUs per worker in Ray, if it is set to be a fraction,
     # it allows ray to schedule multiple actors on a single GPU,
     # so that users can colocate other actors on the same GPUs as vLLM.