[UT]add pcp aclgraph ut (#4804)

### What this PR does / why we need it?
add pcp aclgraph ut

- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c

Signed-off-by: weiguihua2 <weiguihua2@huawei.com>

tests/ut/compilation/test_acl_graph.py

@@ -15,15 +15,21 @@
 
 from unittest.mock import MagicMock, Mock, patch
 
+import numpy as np
 import torch
 from vllm.compilation.cuda_graph import CUDAGraphOptions
 from vllm.config import CUDAGraphMode, VllmConfig
 from vllm.forward_context import BatchDescriptor, ForwardContext
 
 from tests.ut.base import TestBase
+from vllm_ascend.attention.attention_v1 import (AscendMetadata,
+                                                AscendMetadataForDecode)
+from vllm_ascend.attention.mla_v1 import (AscendMLADecodeMetadata,
+                                          AscendMLAMetadata)
 from vllm_ascend.compilation.acl_graph import (
-    ACLGraphEntry, ACLGraphWrapper, get_mtp_graph_params, set_mtp_graph_params,
-    update_mtp_graph_params_workspaces)
+    ACLGraphEntry, ACLGraphWrapper, get_graph_params, get_mtp_graph_params,
+    set_graph_params, set_mtp_graph_params, update_attn_dcp_pcp_params,
+    update_mla_attn_dcp_pcp_params, update_mtp_graph_params_workspaces)
 
 
 class TestACLGraphEntry(TestBase):
@@ -726,3 +732,116 @@ class TestMTPGraphParams(TestBase):
     def test_get_mtp_graph_params(self, mtp_graph_params_mock):
         graph_params = get_mtp_graph_params()
         self.assertIs(mtp_graph_params_mock, graph_params)
+
+
+class TestPCPDCPGraphParams(TestBase):
+
+    def setUp(self):
+        self.update_stream = MagicMock(name="FakeStream")
+        graph_params = get_graph_params()
+        if graph_params is None:
+            set_graph_params(set([4]))
+            self.graph_params = get_graph_params()
+        else:
+            self.graph_params = graph_params
+        mock_event = torch.npu.ExternalEvent()
+        mock_event.record = MagicMock()
+        self.graph_params.events[4] = []
+        self.graph_params.handles[4] = []
+        self.graph_params.events[4].append(mock_event)
+        self.graph_params.handles[4].append(MagicMock())
+
+    @patch('torch.npu.graph_task_update_end', )
+    @patch('torch.npu.graph_task_update_begin', MagicMock())
+    @patch('torch_npu.atb.npu_multi_head_latent_attention', MagicMock())
+    def test_update_mla_dcp_pcp_params(self, _mock_graph_task_end):
+        input_positions = torch.tensor([1, 2, 3, 4, 5, 6, 7, 8])
+        block_table = torch.zeros(2, 5, dtype=torch.long)
+        seq_lens = torch.tensor([4, 4])
+        cp_seq_len = torch.tensor([2, 2])
+        max_seq_lens = 4
+        seq_lens_list = [4, 4]
+        slot_mapping = torch.zeros(8, dtype=torch.long)
+        query_start_loc = torch.tensor([0, 4])
+        block_tables = torch.zeros(2, 5, dtype=torch.long)
+
+        decode = AscendMLADecodeMetadata(input_positions,
+                                         block_table,
+                                         seq_lens,
+                                         max_seq_lens,
+                                         seq_lens_list,
+                                         cp_seq_len=cp_seq_len)
+        metadata = AscendMLAMetadata(8,
+                                     8,
+                                     slot_mapping,
+                                     query_start_loc,
+                                     seq_lens,
+                                     block_tables,
+                                     4,
+                                     4,
+                                     0,
+                                     decode=decode)
+        forward_context = MagicMock()
+        forward_context.attn_metadata = {"attn_layer_0": metadata}
+        forward_context.is_mtp_model = False
+
+        num_heads = 256
+        scale = 0.1
+        num_kv_heads = 8
+        qk_head_dim = 96
+        qk_rope_head_dim = 32
+        qk_nope_head_dim = 64
+        query = torch.randn(4, num_heads, qk_head_dim)
+        q_pe = query[..., qk_nope_head_dim:]
+        q_nope = query[..., :qk_nope_head_dim]
+        k_nope = torch.randn(4, num_heads, qk_nope_head_dim)
+        k_pe = torch.randn(4, num_heads, qk_rope_head_dim)
+        out = torch.randn(2, 16, 128)
+        lse = torch.randn(2, 16, 8)
+        self.graph_params.attn_params[4] = []
+        self.graph_params.attn_params[4].append(
+            (q_nope, q_pe, k_nope, k_pe, block_table, seq_lens, num_heads,
+             scale, num_kv_heads, out, lse))
+
+        update_mla_attn_dcp_pcp_params(self.update_stream, forward_context, 4)
+
+        _mock_graph_task_end.assert_called_once()
+
+    @patch('torch.npu.graph_task_update_end', )
+    @patch('torch.npu.graph_task_update_begin', MagicMock())
+    @patch('torch_npu.npu_fused_infer_attention_score.out', MagicMock())
+    def test_update_attn_dcp_pcp_params(self, _mock_graph_task_end):
+        block_table = torch.zeros(2, 5, dtype=torch.long)
+        num_heads = 256
+        scale = 0.1
+        num_kv_heads = 8
+        qk_head_dim = 96
+        qk_nope_head_dim = 64
+        query = torch.randn(4, num_heads, qk_head_dim)
+        q_nope = query[..., :qk_nope_head_dim]
+        k_nope = torch.randn(4, num_heads, qk_nope_head_dim)
+        actual_seq_lengths_kv = [1, 1]
+        actual_seq_lengths_q = np.array([1, 1])
+        out = torch.randn(2, 16, 128)
+        lse = torch.randn(2, 16, 8)
+
+        num_computed_tokens_of_pcp_dcp = np.array([[[1, 1], [1, 1]],
+                                                   [[1, 1], [1, 1]]])
+        decode = AscendMetadataForDecode(num_computed_tokens_of_pcp_dcp)
+        metadata = AscendMetadata(num_actual_tokens_pcp_padded=[1, 1],
+                                  actual_seq_lengths_q=actual_seq_lengths_q,
+                                  num_decode_tokens=1,
+                                  decode_meta=decode)
+        forward_context = MagicMock()
+        forward_context.attn_metadata = {"attn_layer_0": metadata}
+        forward_context.is_mtp_model = False
+
+        self.graph_params.attn_params[4] = []
+        self.graph_params.attn_params[4].append(
+            (q_nope, k_nope, k_nope, num_heads, num_kv_heads, scale,
+             block_table, 128, actual_seq_lengths_kv, actual_seq_lengths_q,
+             out, lse, 2, 0, 0))
+
+        update_attn_dcp_pcp_params(self.update_stream, forward_context, 4)
+
+        _mock_graph_task_end.assert_called_once()