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

vllm_ascend/ops/linear_op.py

@@ -70,7 +70,7 @@ from vllm_ascend.ops.flashcomm2_oshard_manager import flashcomm2_oshard_manager
 from vllm_ascend.utils import (
     enable_dsa_cp,
     enable_dsa_cp_with_layer_shard,
-    enable_sp,
+    enable_flash_comm_v1,
     flashcomm2_enable,
     get_flashcomm2_reorgnized_batch_ids,
     get_weight_prefetch_method,
@@ -368,7 +368,7 @@ class Flashcomm2OProjRowParallelOp(CustomRowParallelOp):
         else:
             output = output_parallel
 
-        if not forward_context.sp_enabled:
+        if not forward_context.flash_comm_v1_enabled:
             # flashcomm1 not enabled
             output = get_tp_group().all_gather(output, 0)
             if num_padding_tokens > 0:
@@ -466,7 +466,7 @@ class Flashcomm2OshardQKVParallelOp(CustomColumnParallelOp):
         # Matrix multiply.
         assert self.quant_method is not None
 
-        if enable_sp():
+        if enable_flash_comm_v1():
             input_ = torch.ops.vllm.maybe_all_gather_and_maybe_unpad(input_, True)
 
         # Trigger async broadcast before matmul to overlap communication.
@@ -515,15 +515,15 @@ class SequenceRowParallelOp(CustomRowParallelOp):
         assert self.quant_method is not None
         try:
             forward_context = get_forward_context()
-            sp_enabled = forward_context.sp_enabled
+            flash_comm_v1_enabled = forward_context.flash_comm_v1_enabled
             mmrs_fusion = forward_context.mmrs_fusion
         except AssertionError:
-            sp_enabled = False
+            flash_comm_v1_enabled = False
             mmrs_fusion = False
 
         x = input_parallel
 
-        if not sp_enabled:
+        if not flash_comm_v1_enabled:
             output_parallel = self.layer.quant_method.apply(self.layer, x, bias=bias_)
             return tensor_model_parallel_all_reduce(output_parallel)
 
@@ -649,7 +649,7 @@ def _get_column_parallel_op(
     if flashcomm2_oshard_manager.flashcomm2_oshard_enable():
         if any(p in prefix for p in ("qkv_proj", "conv1d", "query_key_value")):
             return Flashcomm2OshardQKVParallelOp(layer)
-    if enable_sp():
+    if enable_flash_comm_v1():
         if "shared_expert" in prefix:
             return None
         sp_column_prefix = [
@@ -688,7 +688,7 @@ def _get_row_parallel_op(
     if flashcomm2_enable():
         if "o_proj" in prefix or "out_proj" in prefix:
             return Flashcomm2OProjRowParallelOp(layer)
-    if enable_sp():
+    if enable_flash_comm_v1():
         if "shared_expert" in prefix:
             return None
         sp_row_prefixes = [