[Feat]support sequence parallelism by pass for VL models (#5632)

vllm_ascend/platform.py

@@ -48,6 +48,7 @@ from vllm_ascend.utils import (
     update_aclgraph_sizes,
     update_cudagraph_capture_sizes,
     is_310p,
+    enable_flash_comm_v1,
 )
 
 if TYPE_CHECKING:
@@ -198,32 +199,9 @@ class NPUPlatform(Platform):
                 if not isinstance(ascend_compilation_config, dict)
                 else ascend_compilation_config
             )
+        ascend_config.update_compile_ranges_split_points()
 
-            if vllm_config.additional_config.get("ascend_compilation_config", {}).get("fuse_allreduce_rms", True):
-                from vllm_ascend.compilation.passes.allreduce_rmsnorm_fusion_pass import ALLREDUCE_NORM_FUSE_THRESHOLD
-
-                new_compile_ranges_split_points = vllm_config.compilation_config.compile_ranges_split_points
-                new_compile_ranges_split_points.append(ALLREDUCE_NORM_FUSE_THRESHOLD)
-                new_compile_ranges_split_points = sorted(new_compile_ranges_split_points)
-                vllm_config.compilation_config.compile_ranges_split_points = new_compile_ranges_split_points
-                logger.debug(
-                    "set compile_ranges_split_points to "
-                    "{new_compile_ranges_split_points} for matmul and allreduce fusion"
-                )
-
-        npugraph_ex_config = ascend_config.npugraph_ex_config
-        if npugraph_ex_config and npugraph_ex_config.fuse_allreduce_rms:
-            from vllm_ascend.compilation.passes.allreduce_rmsnorm_fusion_pass import ALLREDUCE_NORM_FUSE_THRESHOLD
-
-            new_compile_ranges_split_points = vllm_config.compilation_config.compile_ranges_split_points
-            new_compile_ranges_split_points.append(ALLREDUCE_NORM_FUSE_THRESHOLD)
-            new_compile_ranges_split_points = sorted(new_compile_ranges_split_points)
-            vllm_config.compilation_config.compile_ranges_split_points = new_compile_ranges_split_points
-            logger.debug(
-                "set compile_ranges_split_points to {new_compile_ranges_split_points} for matmul and allreduce fusion"
-            )
-
-        elif model_config and hasattr(model_config.hf_text_config, "index_topk"):
+        if model_config and hasattr(model_config.hf_text_config, "index_topk"):
             vllm_config.cache_config.cache_dtype = str(model_config.dtype).replace("torch.", "")
 
         ascend_fusion_config = ascend_config.ascend_fusion_config
@@ -417,15 +395,19 @@ class NPUPlatform(Platform):
             )
             vllm_config.parallel_config.cp_kv_cache_interleave_size = cache_config.block_size
 
-        if is_vl_model(vllm_config):
-            if bool(int(os.getenv("VLLM_ASCEND_ENABLE_FLASHCOMM", "0"))) or bool(
-                int(os.getenv("VLLM_ASCEND_ENABLE_FLASHCOMM1", "0"))
-            ):
-                raise ValueError(
-                    "Currently, VL models doesn't support "
-                    "FLASHCOMM in vllm-ascend. We will fix this in the future. "
-                    "Please set VLLM_ASCEND_ENABLE_FLASHCOMM1=0."
-                )
+        if enable_flash_comm_v1():
+            assert not is_vl_model(vllm_config), """Flash Comm V1 is not supported for VL models. \
+                Please disable it by setting VLLM_ASCEND_ENABLE_FLASHCOMM1=0. \
+                For optimal performance with VL models, we recommend enabling Sequence Parallelism \
+                via --compilation-config '{"pass_config": {"enable_sp": true}}'."""
+
+            assert vllm_config.parallel_config.tensor_parallel_size > 1, (
+                "Flash Comm v1 is only supported when tp_size > 1."
+            )
+
+            assert not is_moe_model(vllm_config) or vllm_config.parallel_config.enable_expert_parallel, (
+                "Flash Comm v1 requires enable_expert_parallel=True for MoE models."
+            )
 
         # Set "PYTORCH_NPU_ALLOC_CONF=expandable_segments:True" by default to optimize NPU memory management.
         # Find more details at https://docs.vllm.ai/projects/ascend/en/latest/faqs.html#how-to-handle-the-out-of-memory-issue
@@ -626,16 +608,16 @@ class NPUPlatform(Platform):
         # communication methods.
         mmrs_fusion = True
         if is_moe_model(vllm_config):
-            sp_enabled = enable_sp(vllm_config) and num_tokens is not None
+            flash_comm_v1_enabled = enable_sp(vllm_config) and num_tokens is not None
             mmrs_fusion = False
         else:
-            sp_enabled = enable_sp(vllm_config) and num_tokens is not None and num_tokens > 1000
+            flash_comm_v1_enabled = enable_sp(vllm_config) and num_tokens is not None and num_tokens > 1000
 
         # TODO(Levi-JQ): another PR to normalize the enabling logic for sp/fc2
         flashcomm_v2_enabled = flashcomm2_enable() and tp_world_size > 1 and num_tokens is not None
         pad_size = None
         padded_length = None
-        if sp_enabled or flashcomm_v2_enabled:
+        if flash_comm_v1_enabled or flashcomm_v2_enabled:
             pad_size = (tp_world_size - (num_tokens % tp_world_size)) % tp_world_size
 
         if num_tokens is None and attn_metadata is not None:
@@ -643,7 +625,7 @@ class NPUPlatform(Platform):
         dp_world_size = get_dp_group().world_size
         if dp_world_size > 1 and dp_metadata is not None:
             max_tokens_across_dp = dp_metadata.max_tokens_across_dp_cpu.item()
-            if sp_enabled or flashcomm_v2_enabled:
+            if flash_comm_v1_enabled or flashcomm_v2_enabled:
                 padded_length = (max_tokens_across_dp + tp_world_size - 1) // tp_world_size * tp_world_size
                 pad_size = padded_length - num_tokens
         else:
@@ -664,7 +646,7 @@ class NPUPlatform(Platform):
             "capturing": capturing,
             "mmrs_fusion": mmrs_fusion,
             "num_tokens": num_tokens,
-            "sp_enabled": sp_enabled,
+            "flash_comm_v1_enabled": flash_comm_v1_enabled,
             "flashcomm_v2_enabled": flashcomm_v2_enabled,
             "pad_size": pad_size,
             "padded_length": padded_length,