f28223c9da
Replaces all Python PyTorch fallback attention with native ixformer kernels: Decode path: - ≤32K: paged_attention_v1 (5D KV layout, x=8) — verified on real BI-V100 - >32K: paged_attention_v2 (5D→4D permute) — verified 65K+ on real BI-V100 - Removes _forward_decode_pytorch Python fallback entirely Prefill path (profiling): - _run_sdpa_fallback now uses ixformer.flash_attn_varlen_func - head_dim=256 verified correct (diff<0.004) and 1.7x faster than PyTorch - Falls back to Q-tiling pure-math if ixformer unavailable Also includes: MoE kernel integration, GDN C++ kernels, diagnostic scripts, xllm upstream layer/kernel references, .dockerignore cleanup. All changes verified on real BI-V100 hardware (single card).
60 lines
2.1 KiB
C++
60 lines
2.1 KiB
C++
/* Copyright 2025-2026 The xLLM Authors.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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https://github.com/jd-opensource/xllm/blob/main/LICENSE
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#pragma once
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#include <memory>
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#include "models/llm/qwen3_5.h"
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#include "models/llm/qwen3_5_mtp_base.h"
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#include "models/model_registry.h"
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namespace xllm {
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class Qwen3_5MtpModelImpl final : public Qwen3_5MtpModelImplBase {
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public:
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explicit Qwen3_5MtpModelImpl(const ModelContext& context)
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: Qwen3_5MtpModelImplBase(context) {}
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};
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class Qwen3_5MtpForCausalLMImpl final : public Qwen3_5MtpForCausalLMImplBase {
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public:
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explicit Qwen3_5MtpForCausalLMImpl(const ModelContext& context)
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: Qwen3_5MtpForCausalLMImplBase(
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context,
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std::make_shared<Qwen3_5MtpModelImpl>(context)) {}
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};
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TORCH_MODULE(Qwen3_5MtpForCausalLM);
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REGISTER_CAUSAL_MODEL(qwen3_5_mtp, Qwen3_5MtpForCausalLM);
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REGISTER_CAUSAL_MODEL(qwen3_5_moe_mtp, Qwen3_5MtpForCausalLM);
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REGISTER_MODEL_ARGS_LOADER(qwen3_5_mtp,
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[](const JsonReader& json, ModelArgs* args) {
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return qwen3_5_mtp::load_model_args(
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json, args, "qwen3_5_text", "qwen3_5_mtp");
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});
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REGISTER_MODEL_ARGS_LOADER(qwen3_5_moe_mtp,
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[](const JsonReader& json, ModelArgs* args) {
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return qwen3_5_mtp::load_model_args(
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json,
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args,
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"qwen3_5_moe_text",
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"qwen3_5_moe_mtp");
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});
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} // namespace xllm
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