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[Core] Per-group BlockPool for hybrid Mamba/attention models #39031

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[Core] Per-group BlockPool for hybrid Mamba/attention models #39031

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13 changes: 7 additions & 6 deletions tests/v1/core/test_kv_cache_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1741,16 +1741,17 @@ def test_get_kv_cache_config_one_worker():
],
)

# different hidden size that cannot be aligned by using different block size
# different hidden size that can't be evenly divided — handled via page
# padding (page_size_padded) instead of raising NotImplementedError
kv_cache_specs_hybrid = {
"layer_1": new_kv_cache_spec(head_size=64),
"layer_2": new_sliding_window_spec(head_size=96),
}

with pytest.raises(NotImplementedError):
get_kv_cache_configs(
vllm_config, [kv_cache_specs_hybrid], [mem_per_block_per_layer * 2 * 32]
)[0]
kv_cache_config_hybrid = get_kv_cache_configs(
vllm_config, [kv_cache_specs_hybrid], [mem_per_block_per_layer * 2 * 32]
)[0]
# Should succeed with padded page sizes
assert kv_cache_config_hybrid.num_blocks > 0

# Test num_gpu_blocks_override
vllm_config.cache_config.num_gpu_blocks_override = 16
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