Revert "[Feat] Shared expert dp for deepseek and deepseek_mtp (#3495)" (#3586)

### What this PR does / why we need it?
This reverts commit
bf87606932.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
E2E vllm serving with `enable_shared_expert_dp: true` in eager mode as
before.


- vLLM version: v0.11.0rc3
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.0

Signed-off-by: linfeng-yuan <1102311262@qq.com>

tests/ut/ops/test_layernorm.py

@@ -1,5 +1,4 @@
 import unittest
-from unittest.mock import patch
 
 import pytest
 import torch
@@ -54,9 +53,7 @@ class TestAscendRMSNorm(PytestBase):
     # Test case for the most common and basic scenario
     @pytest.mark.parametrize(
         "residual", [None, torch.randn(4, 8, dtype=torch.float16)])
-    @patch("torch.ops.vllm.maybe_chunk_residual")
-    def test_forward_oot_basic(self, mock_maybe_chunk_residual, residual):
-        mock_maybe_chunk_residual.side_effect = lambda x, residual: residual
+    def test_forward_oot_basic(self, residual):
         layer = RMSNorm(hidden_size=8, eps=1e-05)
         x = torch.randn(4, 8, dtype=torch.float16)
         if residual is not None:
@@ -120,8 +117,6 @@ class TestAscendRMSNorm(PytestBase):
         mock_forward_context.layer_idx = 0
         mock_forward_context.num_hidden_layers = num_hidden_layers
         mock_forward_context.fusion_linear = "gate_up_dense"
-        mocker.patch("torch.ops.vllm.maybe_chunk_residual",
-                     lambda x, residual: residual)
 
         # Ensure fusion and layer_idx increment are handled correctly
         x = torch.randn(4, 8, dtype=torch.float16)