rebase: migrate diffusion KV cache to the vLLM 0.29 layout model

vLLM 0.29 removed AttentionSpec.indexes_kv_by_block_stride and reshaped
KVCacheTensor from (size, shared_by) to an explicit layout: layers in L
order plus layer_stride and block_stride. The block-stride decision now
lives on one physical CacheConfig.kv_cache_layout that the engine core
resolves once, and layout.is_block_outermost is the direct successor of
the old per-spec flag.

Diffusion backends subclass the Omni AttentionBackend ABC, so upstream
get_supported_kv_cache_layouts never sees them and the engine core never
resolves a layout for them. Add diffusion_kv/layout.py to pin it before
get_kv_cache_configs runs, defaulting to LBNHC, which reproduces the
indexes_kv_by_block_stride=False that every dense diffusion backend
declared. The backend hook is kept as an enforced contract rather than
deleted: a backend needing block-stride indexing selects a block-outermost
layout, and a contradiction raises instead of mis-addressing K/V.

Workers receive only a KVCacheConfig, so the resolved name travels on it
(KVCacheConfig.kv_cache_layout) and is adopted into each worker CacheConfig
before allocation. Without that, init_kv_cache raises in the worker because
get_resolved_kv_cache_layout has nothing to return.

init_kv_cache also lost attn_groups and cache_dtype in 0.29; the production
caller in model_runner_backend and the test stubs move to the six-argument
form.

Tensor construction goes through one derivation built on the upstream
compute_layout_strides helper, shared by production and tests, so a wrong
stride cannot be masked by a parallel test-only copy.

Also updates the sizing expectation: 0.29 subtracts the null block that
BlockPool permanently holds back before estimating, so sixteen physical
pages now yield fifteen usable ones.

One review point is addressed only in part, deliberately.
build_native_kv_cache_configs now takes indexes_kv_by_block_stride and
propagates a block-outermost layout end to end when it is set, with a test
covering control plane to worker adoption. Automatic discovery of that
requirement from the workers is not added: 0.29 removed the field that used
to carry it, every diffusion backend in tree declares False, and inventing
an executor RPC for a capability nothing requests would ship untestable
plumbing. Until a backend needs it, the seam is explicit and the mismatch
raises at worker init rather than corrupting addressing.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0146Xu5Sgj4vXxLxvLjV5YPj
Signed-off-by: tzhouam <tzhouam@connect.ust.hk>

tests/diffusion/diffusion_kv/test_block_tables.py

@@ -279,17 +279,17 @@ def _install_native_modules(monkeypatch: pytest.MonkeyPatch, events: list[tuple]
         group = SimpleNamespace(get_metadata_builder=lambda _index: SimpleNamespace(reorder_batch_threshold=None))
         return [[group], [group]], "cg-support", [4, 8]
 
+    # vLLM 0.29 dropped attn_groups and cache_dtype from init_kv_cache: the
+    # layout now rides on the resolved CacheConfig.kv_cache_layout instead.
     def init_cache(
         runner_kv_caches,
         forward_context,
         kv_cache_config,
-        attn_groups,
         device,
-        cache_dtype,
         kernel_block_sizes,
         vllm_config,
     ):
-        events.append(("cache", kv_cache_config, attn_groups, kernel_block_sizes))
+        events.append(("cache", kv_cache_config, kernel_block_sizes))
         runner_kv_caches.extend(["cache-0", "cache-1"])
         return {"layer-0": "tensor-0", "layer-1": "tensor-1"}