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[cherry-pick][Test]repair for test_compute_slot_mapping (#7836)

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### What this PR does / why we need it?
repair for test_compute_slot_mapping

Signed-off-by: ZT-AIA <1028681969@qq.com>
This commit is contained in:
ZT-AIA
2026-03-31 16:52:58 +08:00
committed by GitHub
parent af4278be35
commit 66db070423
1 changed files with 1 additions and 2 deletions
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tests/e2e/nightly/single_node/ops/singlecard_ops/triton/test_compute_slot_mapping.py
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@@ -5,7 +5,6 @@ from vllm.v1.worker.gpu.block_table import _compute_slot_mappings_kernel as \
ref_compute_slot_mappings_kernel ref_compute_slot_mappings_kernel
from vllm_ascend.worker.v2.block_table import _compute_slot_mappings_kernel as \ from vllm_ascend.worker.v2.block_table import _compute_slot_mappings_kernel as \
ascend_compute_slot_mappings_kernel ascend_compute_slot_mappings_kernel
from vllm.v1.worker.gpu.block_table import _load_ptr, _make_ptr_tensor
def test_compute_slot_mapping_npu_kernel(): def test_compute_slot_mapping_npu_kernel():
@@ -52,7 +51,7 @@ def test_compute_slot_mapping_npu_kernel():
for i in range(num_kv_cache_groups): for i in range(num_kv_cache_groups):
block_table = torch.randint(0, 320, (max_num_reqs, max_num_blocks), dtype=torch.int32, device=device) block_table = torch.randint(0, 320, (max_num_reqs, max_num_blocks), dtype=torch.int32, device=device)
block_tables.append(block_table) block_tables.append(block_table)
block_table_ptrs = _make_ptr_tensor(block_tables) block_table_ptrs = torch.tensor([t.data_ptr() for t in block_table], dtype=torch.uint64, device=device)
block_table_strides = torch.tensor([320], dtype=torch.int32, device=device) block_table_strides = torch.tensor([320], dtype=torch.int32, device=device)
block_sizes_tensor = torch.tensor([128], dtype=torch.int32, device=device) block_sizes_tensor = torch.tensor([128], dtype=torch.int32, device=device)