[CI]Fixed the spell check function in typos.toml (#6753)

### What this PR does / why we need it?
The incorrect regular expression syntax `.*[UE4M3|ue4m3].*` actually
ignores all words containing any of the following characters: `u, e, 4,
m, 3, |`

```yaml
extend-ignore-identifiers-re = [".*Unc.*", ".*_thw",
    ".*UE8M0.*", ".*[UE4M3|ue4m3].*", ".*eles.*", ".*fo.*", ".*ba.*",
    ".*ot.*", ".*[Tt]h[rR].*"]
```
===fix===>
```yaml
extend-ignore-identifiers-re = [".*Unc.*", ".*_thw",
    ".*UE8M0.*", ".*(UE4M3|ue4m3]).*", ".*eles.*", ".*fo.*", ".*ba.*",
    ".*ot.*", ".*[Tt]h[rR].*"]
```

### Does this PR introduce _any_ user-facing change?

### How was this patch tested?

- vLLM version: v0.15.0
- vLLM main:
9562912cea

Signed-off-by: MrZ20 <2609716663@qq.com>

tests/e2e/nightly/multi_node/scripts/multi_node_config.py

@@ -10,7 +10,7 @@ import yaml
 # isort: off
 from tests.e2e.nightly.multi_node.scripts.utils import (
     CONFIG_BASE_PATH, DEFAULT_SERVER_PORT, get_all_ipv4, get_cluster_ips,
-    get_net_interface, setup_logger, get_avaliable_port)
+    get_net_interface, setup_logger, get_available_port)
 # isort: on
 setup_logger()
 logger = logging.getLogger(__name__)
@@ -202,7 +202,7 @@ class MultiNodeConfig:
         master_ip = (self.disagg_cfg.master_ip_for_node(
             self.cur_index, self.nodes)
                      if self.disagg_cfg else self.nodes[0].ip)
-        self.proxy_port = get_avaliable_port()
+        self.proxy_port = get_available_port()
 
         self.envs = DistEnvBuilder(
             cur_node=self.cur_node,

tests/e2e/nightly/multi_node/scripts/utils.py

@@ -75,7 +75,7 @@ def get_cluster_ips(word_size: int = 2) -> list[str]:
     return [resolver(dns) for dns in get_cluster_dns_list(word_size)]
 
 
-def get_avaliable_port(start_port: int = 6000, end_port: int = 7000) -> int:
+def get_available_port(start_port: int = 6000, end_port: int = 7000) -> int:
     import socket
     for port in range(start_port, end_port):
         with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:

tests/e2e/nightly/single_node/ops/multicard_ops_a3/test_dispatch_ffn_combine.py

@@ -11,7 +11,7 @@ from vllm_ascend.utils import enable_custom_op
 enable_custom_op()
 
 
-class TestDisptachFFNCombine:
+class TestDispatchFFNCombine:
 
     def __init__(self, rank, world_size, port):
         self.rank = rank
@@ -208,7 +208,7 @@ class TestDisptachFFNCombine:
 
 
 def worker(rank: int, world_size: int, port: int, q: mp.SimpleQueue):
-    op = TestDisptachFFNCombine(rank, world_size, port)
+    op = TestDispatchFFNCombine(rank, world_size, port)
     op.generate_hcom()
     out1 = op.run_tensor_list()
     q.put(out1)

tests/e2e/nightly/single_node/ops/multicard_ops_a3/test_dispatch_ffn_combine_bf16.py

@@ -11,7 +11,7 @@ from vllm_ascend.utils import enable_custom_op
 enable_custom_op()
 
 
-class TestDisptachFFNCombine:
+class TestDispatchFFNCombine:
 
     def __init__(self, rank, world_size, port):
         self.rank = rank
@@ -208,7 +208,7 @@ class TestDisptachFFNCombine:
 
 
 def worker(rank: int, world_size: int, port: int, q: mp.SimpleQueue):
-    op = TestDisptachFFNCombine(rank, world_size, port)
+    op = TestDispatchFFNCombine(rank, world_size, port)
     op.generate_hcom()
     out1 = op.run_tensor_list()
     q.put(out1)

tests/e2e/nightly/single_node/ops/singlecard_ops/triton/test_penality.py

@@ -124,10 +124,10 @@ def create_test_data(
 
     logits = torch.randn(num_reqs, vocab_size, device=device, dtype=dtype)
 
-    repetiton_penalty = torch.ones(num_reqs, device=device, dtype=torch.float32)
+    repetition_penalty = torch.ones(num_reqs, device=device, dtype=torch.float32)
     for i in range(num_reqs):
         if torch.rand(1) > 0.3:
-            repetiton_penalty[i] = torch.rand(1, device=device).item() * 0.8 + 0.6
+            repetition_penalty[i] = torch.rand(1, device=device).item() * 0.8 + 0.6
 
     frequency_penalty = torch.zeros(num_reqs, device=device, dtype=torch.float32)
     for i in range(num_reqs):
@@ -168,7 +168,7 @@ def create_test_data(
             output_bin_counts[state_idx, token] = count
 
     sampling_metadata = SamplingMetadata(
-        repetition_penalty=repetiton_penalty,
+        repetition_penalty=repetition_penalty,
         frequency_penalty=frequency_penalty,
         presence_penalty=presence_penalty,
         temperature=temperature,
@@ -217,4 +217,3 @@ def test_apply_penalties_and_temperature(
         atol = 1e-02
         rtol = 1e-02
     assert torch.allclose(logits_triton, logits_pytorch_result, atol=atol, rtol=rtol)
-

tests/ut/ops/test_moe_mlp.py

@@ -18,7 +18,7 @@ class TestCumsumGroupList(unittest.TestCase):
         }
 
     support_combine = [(0, 0), (1, 0), (0, 1)]
-    unsupport_combine = [(0, 2), (2, 1), (1, 2)]
+    unsupported_combine = [(0, 2), (2, 1), (1, 2)]
 
     def test_cumsum_group_list_supported_conversion(self):
         for src_list_type, dst_list_type in self.support_combine:
@@ -38,7 +38,7 @@ class TestCumsumGroupList(unittest.TestCase):
 
     def test_cumsum_group_list_unsupported_conversion_notimplementederror(
             self):
-        for src_list_type, dst_list_type in self.unsupport_combine:
+        for src_list_type, dst_list_type in self.unsupported_combine:
             with self.subTest(src=src_list_type, dst=dst_list_type):
                 with self.assertRaises(NotImplementedError) as excinfo:
                     cumsum_group_list(self.glist_dict[0], src_list_type,