init v0.23.0

Signed-off-by: Sun Ruoxi <sunruoxi@4paradigm.com>

tests/ut/_310p/attention/test_attention_mask_310.py

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+#
+# Copyright (c) 2026 Huawei Technologies Co., Ltd. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from unittest.mock import MagicMock, patch
+
+import torch
+
+from tests.ut.base import TestBase
+from vllm_ascend._310p.attention.attention_mask import AttentionMaskBuilder310
+
+
+class TestAttentionMaskBuilder310(TestBase):
+    def setUp(self):
+        self.max_seqlen = 4096
+        self.attention_mask_builder = AttentionMaskBuilder310(torch.device("cpu"), self.max_seqlen)
+
+    @patch("torch_npu.npu_format_cast")
+    def test_get_attention_mask_310(self, mock_format_cast):
+        mock_format_cast.side_effect = lambda x, y: x
+        self.attention_mask_builder.support_compressed_mask = False
+        model_config = MagicMock()
+        attn_mask = self.attention_mask_builder.get_attention_mask(causal=True, model_config=model_config)
+        self.assertEqual(attn_mask.shape, (1, self.max_seqlen // 16, self.max_seqlen, 16))
+        self.assertEqual(attn_mask[0][-1][0][-1], torch.tensor(float("-inf"), dtype=torch.float16))
+
+    @patch("torch_npu.npu_format_cast")
+    def test_get_splitfuse_attn_mask_310(self, mock_format_cast):
+        mock_format_cast.side_effect = lambda x, y: x
+        attn_metadata = MagicMock()
+        attn_metadata.query_start_loc = torch.tensor([0, 1, 5])
+        attn_metadata.seq_lens = torch.tensor([7, 4])
+        attn_mask = self.attention_mask_builder.get_splitfuse_mask(attn_metadata, torch.device("cpu"))
+        self.assertEqual(attn_mask.shape, (1, self.max_seqlen // 16, 16, 16))