[main][refactor] refactor SequenceRowParallelOp forward (#3616)

### What this PR does / why we need it?
This PR refactors SequenceRowParallelOp forward. In order to further
expand the operator inclusion scope in dynamic judgment scenarios, this
PR customizes the entire matmul computation and communication as a
custom operator masking. With this refactor, it will support directly
writing code such as common operation fusion into the
`SequenceRowParallelOp` class's member function `matmul_and_reduce`,
without the need to register more redundant custom masking operators.

### How was this patch tested?
CI passed with existing test.

Signed-off-by: rjg-lyh <1318825571@qq.com>

vllm_ascend/ops/linear.py

@@ -26,6 +26,7 @@ import torch
 import torch.nn as nn
 import torch_npu
 from torch.nn.parameter import Parameter
+from vllm.config import get_current_vllm_config
 from vllm.distributed import divide
 from vllm.model_executor.layers.linear import (  # noqa
     WEIGHT_LOADER_V2_SUPPORTED, ColumnParallelLinear, LinearBase,
@@ -234,6 +235,13 @@ class AscendRowParallelLinear(RowParallelLinear):
         return_bias: bool = True,
         disable_tp: bool = False,
     ):
+        compilation_config = get_current_vllm_config().compilation_config
+        # TODO(shaopeng-666): Remove the visual check after the mm model reconstruction is complete.
+        if prefix in compilation_config.static_forward_context and \
+            "visual" not in prefix:
+            raise ValueError(f"Duplicate layer name: {prefix}")
+        compilation_config.static_forward_context[prefix] = self
+
         self.custom_op, self.tp_rank, self.tp_size = get_parallel_op(
             disable_tp, prefix, self, "row")
         # TODO(realliujiaxu): Replace the initialization code below with super().__init__ after linear of vllm supports custom comm group