A symbol scan over every tracked file found 123 top-level definitions in
vllm/ with zero references, including references inside strings. All of
them came from features this fork deleted earlier.
- Delete dead attention helpers: MLADCPManager, split_prefill_chunks, the
reshape helpers, compute_varlen_chunk_metadata, the LINEAR backend's
unused BailingLinearAttentionBackend, and the sparse flash-attn entry
points.
- Delete the CPU and AMX op wrappers from _custom_ops.py: cpu_mla_decode,
cpu_mla_extend, cpu_mla_get_scheduler_metadata,
gather_mla_context_cache_cpu.
- Delete dead quantization helpers: awq_pack, gptq_pack,
gptq_quantize_weights, get_and_maybe_dequant_weights,
marlin_quant_fp8_torch, the rand_marlin_weight_*_like pair,
ocp_mx_weight_dtype_and_rows, get_fp8_block_weight_scale,
input_to_float8.
- Delete dead model helpers: resolve_visual_encoder_outputs,
run_dp_sharded_vision_model, fast_topk, get_layer_index,
is_pp_missing_parameter, skip_spec_layers, KimiK3MergedQKVGateLinear,
selective_scan_fn, causal_conv1d_update_torch.
- Delete dead utils: format_kib, format_mib, chunk_list, prev_power_of_2,
split_host_port, join_host_port, make_zmq_path, make_async_with_semaphore,
is_meta_module, is_non_overlapping_and_dense, supports_xpu_graph,
create_kv_caches_with_random*, and the unused has_* capability probes.
- Delete the unreachable deep-gemm mega-MoE warmup path, which imported
vllm.models.deepseek_v4.nvidia.model and vllm.models.kimi_k3.nvidia.model,
neither of which exists anymore.
- Drop the imports and the two now-empty guards left behind.
Verified statically: every changed file compiles, no unused import
remains, and no deleted name is referenced in vllm, tests or csrc. The
runtime gates still need the Python environment rebuilt.
Co-authored-by: Hinata <hinata@idihore.id>
Signed-off-by: MOVZX <movzx@yahoo.com>
Production runs one static model behind the OpenAI-compatible API. Every
adapter path and non-OpenAI HTTP surface is unreachable there.
- Delete the LoRA stack: vllm/lora, LoRARequest on the engine wire, the
scheduler, worker, cudagraph and MoE plumbing, LoRA metrics, the lora
CLI group, and the LoRA tests.
- Drop the plugin loader in vllm/plugins. Platform resolution is now
CUDA-only and the general/stat-logger plugin hooks are gone.
- Delete the speech-to-text and realtime entrypoints, the scale-out
render routes, and vllm/config/speech_to_text.py. GenerationTask is
generate-only.
- Cut DecodeBenchConnector and the disagg-prefill doc and image. The
Multi, Offloading and Example connectors stay; production uses the
CPU KV offload tier.
- Delete the ROCm-only fused KDA chunk kernel (2346 lines) with its CMake
arch gate, declarations and op registrations. The CUDA build never
defined the guard and no Python caller existed.
- Delete the orphan Mistral and Pixtral chat fixtures and examples/.
- Fix _check_model: removing the LoRA early return made every request
fail with "The model ... does not exist. Valid aliases: ...".
Verified on an RTX 3090: import sweep reports 1242 modules with 7 known
optional-dependency failures; a live server answers chat, completions,
responses, tokenize and detokenize with zero log errors and 404 for the
removed surfaces; collection yields 8558 tests with the 3 pre-existing
errors; ruff adds no new finding; the incremental _C build succeeds.
Co-authored-by: Hinata <hinata@idihore.id>
Signed-off-by: MOVZX <movzx@yahoo.com>
MOVZXandHinata
