xc-llm-ascend/tests/ut/attention/test_attention_mask.py

#
# Copyright (c) 2025 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.

import torch

from tests.ut.base import TestBase
from vllm_ascend.attention.attention_mask import AttentionMaskBuilder


class TestAttentionMaskBuilder(TestBase):

    def test_get_attn_mask(self):
        # if the len is less than max_seq_len, the attn_mask_cache will not be updated
        attention_mask_builder = AttentionMaskBuilder(torch.device("cpu"))
        attn_mask = attention_mask_builder.get_attn_mask(max_seq_len=512,
                                                         dtype=torch.float16)
        self.assertEqual(attn_mask.shape, (512, 512))
        self.assertEqual(attn_mask[0][-1],
                         torch.tensor(float("-inf"), dtype=torch.float16))
        self.assertEqual(attention_mask_builder._seq_len_cached, 512)
        self.assertEqual(attention_mask_builder.attn_mask_cache.shape,
                         (512, 512))
        self.assertEqual(attention_mask_builder.attn_mask_cache[0][-1],
                         torch.tensor(float("-inf"), dtype=torch.float16))

        # if the len is greater than max_seq_len, the attn_mask_cache will be updated
        attn_mask = attention_mask_builder.get_attn_mask(max_seq_len=2048,
                                                         dtype=torch.float16)
        self.assertEqual(attn_mask.shape, (2048, 2048))
        self.assertEqual(attn_mask[0][-1],
                         torch.tensor(float("-inf"), dtype=torch.float16))
        self.assertEqual(attention_mask_builder._seq_len_cached, 2048)
        self.assertEqual(attention_mask_builder.attn_mask_cache.shape,
                         (2048, 2048))
        self.assertEqual(attention_mask_builder.attn_mask_cache[0][-1],
                         torch.tensor(float("-inf"), dtype=torch.float16))

    def test_get_splitfuse_attn_mask(self):
        attention_mask_builder = AttentionMaskBuilder(torch.device("cpu"))
        attn_mask = attention_mask_builder.get_splitfuse_attn_mask()
        self.assertEqual(attn_mask.shape, (2048, 2048))