MOVZXandHinata
61fbe0b865
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>
48 lines
1.3 KiB
Python
48 lines
1.3 KiB
Python
# SPDX-License-Identifier: Apache-2.0
|
|
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
|
|
|
|
from typing import Protocol, TypeAlias
|
|
|
|
from vllm.config import ModelConfig
|
|
from vllm.entrypoints.openai.chat_completion.protocol import (
|
|
BatchChatCompletionRequest,
|
|
ChatCompletionRequest,
|
|
ChatCompletionResponse,
|
|
)
|
|
from vllm.entrypoints.openai.completion.protocol import (
|
|
CompletionRequest,
|
|
CompletionResponse,
|
|
)
|
|
from vllm.entrypoints.openai.responses.protocol import ResponsesRequest
|
|
from vllm.entrypoints.serve.tokenize.protocol import (
|
|
DetokenizeRequest,
|
|
TokenizeChatRequest,
|
|
TokenizeCompletionRequest,
|
|
TokenizeResponse,
|
|
)
|
|
from vllm.renderers import TokenizeParams
|
|
|
|
|
|
class RendererRequest(Protocol):
|
|
def build_tok_params(self, model_config: ModelConfig) -> TokenizeParams:
|
|
raise NotImplementedError
|
|
|
|
|
|
CompletionLikeRequest: TypeAlias = (
|
|
CompletionRequest
|
|
| TokenizeCompletionRequest
|
|
| DetokenizeRequest
|
|
)
|
|
|
|
ChatLikeRequest: TypeAlias = (
|
|
ChatCompletionRequest
|
|
| BatchChatCompletionRequest
|
|
| TokenizeChatRequest
|
|
)
|
|
|
|
AnyRequest: TypeAlias = CompletionLikeRequest | ChatLikeRequest | ResponsesRequest
|
|
|
|
AnyResponse: TypeAlias = (
|
|
CompletionResponse | ChatCompletionResponse | TokenizeResponse
|
|
)
|