fix deepseek torchair precision (#3635)

### What this PR does / why we need it?
The precision of deepseek torchair is broken by #3465 , which due to the origin patch or rmsnorm in torchair. This PR fixes the precision of deepseek torchair.

### Does this PR introduce _any_ user-facing change?
No

### How was this patch tested?
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Signed-off-by: hust17yixuan <303660421@qq.com>

vllm_ascend/torchair/ops/torchair_layernorm.py

@@ -18,6 +18,32 @@
 from typing import Optional, Tuple, Union
 
 import torch
+from vllm.config import get_current_vllm_config
+from vllm.model_executor.layers.layernorm import RMSNorm
+
+from vllm_ascend.utils import version_check
+
+_original_re_init = RMSNorm.__init__
+
+
+def torchair_rmsnorm_init_(
+    self,
+    hidden_size: int,
+    eps: float = 1e-6,
+    var_hidden_size: Optional[int] = None,
+    has_weight: bool = True,
+    dtype: Optional[torch.dtype] = None,
+) -> None:
+    _original_re_init(self, hidden_size, eps, var_hidden_size, has_weight,
+                      dtype)
+    vllm_config = get_current_vllm_config()
+    self.bias = None
+    self.torch_npu_check = version_check()
+    # quantization with anti_method m4 will generate none-zero norm bias
+    if self.torch_npu_check and vllm_config.quant_config is not None and \
+            any("norm.bias" in name for name in vllm_config.quant_config.quant_description.keys()):
+        self.bias = torch.nn.Parameter(torch.zeros(hidden_size),
+                                       requires_grad=False)
 
 
 def torchair_rmsnorm_forward_oot(
@@ -33,6 +59,7 @@ def torchair_rmsnorm_forward_oot(
     """
 
     import torch_npu
+    torch_npu_check = version_check()
 
     from vllm_ascend.utils import is_310p
     if residual is not None:
@@ -45,7 +72,11 @@ def torchair_rmsnorm_forward_oot(
         else:
             x, _, residual = torch_npu.npu_add_rms_norm(
                 x, residual, self.weight, self.variance_epsilon)
+        if torch_npu_check and self.bias is not None:
+            x.add_(self.bias)
         return x, residual
 
     x, residual = torch_npu.npu_rms_norm(x, self.weight, self.variance_epsilon)
+    if torch_npu_check and self.bias is not None:
+        x.add_(self.bias)
     return x

vllm_ascend/torchair/utils.py

@@ -229,10 +229,12 @@ def torchair_ops_patch():
     AscendDeepseekScalingRotaryEmbedding.__init__ = deepseek_rope_init_func  # type: ignore[method-assign]
     AscendDeepseekScalingRotaryEmbedding.forward = native_rope_deepseek_forward  # type: ignore[method-assign]
 
+    AscendRMSNorm.__init__ = torchair_layernorm.torchair_rmsnorm_init_  # type: ignore[method-assign]
     AscendRMSNorm.forward_oot = torchair_layernorm.torchair_rmsnorm_forward_oot  # type: ignore[method-assign]
+
     AscendSiluAndMul.forward_oot = torchair_activation.torchair_silu_and_mul_forward_oot  # type: ignore[method-assign]
     AscendVocabParallelEmbedding.forward = vocab_embedding_forward  # type: ignore[method-assign]
 
 
 def super_kernel(prefix: str, option: str, enabled: bool = True):
-    return _super_kernel(prefix, option) if enabled else nullcontext()
+    return _super_kernel(prefix, option) if enabled else nullcontext()