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<h1>Source code for tensorrt_llm.llmapi.llm_utils</h1><div class="highlight"><pre>
<span></span><span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span>
<span class="s1">&#39;LlmArgs&#39;</span><span class="p">,</span>
<span class="s1">&#39;LlmBuildStats&#39;</span><span class="p">,</span>
<span class="s1">&#39;ModelLoader&#39;</span><span class="p">,</span>
<span class="s1">&#39;_ModelRuntimeContext&#39;</span><span class="p">,</span>
<span class="s1">&#39;_ModelInfo&#39;</span><span class="p">,</span>
<span class="s1">&#39;_ParallelConfig&#39;</span><span class="p">,</span>
<span class="s1">&#39;_ModelFormatKind&#39;</span><span class="p">,</span>
<span class="s1">&#39;_ModelWrapper&#39;</span><span class="p">,</span>
<span class="s1">&#39;BatchingType&#39;</span><span class="p">,</span>
<span class="s1">&#39;ExecutorConfig&#39;</span><span class="p">,</span>
<span class="s1">&#39;SchedulerConfig&#39;</span><span class="p">,</span>
<span class="s1">&#39;KvCacheConfig&#39;</span><span class="p">,</span>
<span class="s1">&#39;LookaheadDecodingConfig&#39;</span><span class="p">,</span>
<span class="s1">&#39;MedusaDecodingConfig&#39;</span><span class="p">,</span>
<span class="s1">&#39;ContextChunkingPolicy&#39;</span><span class="p">,</span>
<span class="s1">&#39;CapacitySchedulerPolicy&#39;</span><span class="p">,</span>
<span class="s1">&#39;BuildConfig&#39;</span><span class="p">,</span>
<span class="s1">&#39;BuildCacheConfig&#39;</span><span class="p">,</span>
<span class="s1">&#39;QuantConfig&#39;</span><span class="p">,</span>
<span class="s1">&#39;CalibConfig&#39;</span><span class="p">,</span>
<span class="s1">&#39;CachedModelLoader&#39;</span><span class="p">,</span>
<span class="s1">&#39;ConfigArbitrateError&#39;</span><span class="p">,</span>
<span class="s1">&#39;_ConfigArbitrator&#39;</span><span class="p">,</span>
<span class="p">]</span>
<span class="kn">import</span> <span class="nn">copy</span>
<span class="kn">import</span> <span class="nn">json</span>
<span class="kn">import</span> <span class="nn">os</span>
<span class="kn">import</span> <span class="nn">shutil</span>
<span class="kn">import</span> <span class="nn">tempfile</span>
<span class="kn">import</span> <span class="nn">time</span>
<span class="kn">import</span> <span class="nn">weakref</span>
<span class="kn">from</span> <span class="nn">argparse</span> <span class="kn">import</span> <span class="n">Namespace</span>
<span class="kn">from</span> <span class="nn">dataclasses</span> <span class="kn">import</span> <span class="n">asdict</span><span class="p">,</span> <span class="n">dataclass</span><span class="p">,</span> <span class="n">field</span><span class="p">,</span> <span class="n">fields</span>
<span class="kn">from</span> <span class="nn">enum</span> <span class="kn">import</span> <span class="n">Enum</span>
<span class="kn">from</span> <span class="nn">pathlib</span> <span class="kn">import</span> <span class="n">Path</span>
<span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Any</span><span class="p">,</span> <span class="n">Callable</span><span class="p">,</span> <span class="n">Dict</span><span class="p">,</span> <span class="n">List</span><span class="p">,</span> <span class="n">Literal</span><span class="p">,</span> <span class="n">Optional</span><span class="p">,</span> <span class="n">Tuple</span><span class="p">,</span> <span class="n">Union</span>
<span class="kn">import</span> <span class="nn">torch</span>
<span class="kn">from</span> <span class="nn">tqdm</span> <span class="kn">import</span> <span class="n">tqdm</span>
<span class="kn">from</span> <span class="nn">transformers</span> <span class="kn">import</span> <span class="n">PreTrainedTokenizerBase</span>
<span class="kn">from</span> <span class="nn">.._utils</span> <span class="kn">import</span> <span class="n">mpi_barrier</span><span class="p">,</span> <span class="n">mpi_broadcast</span><span class="p">,</span> <span class="n">mpi_rank</span><span class="p">,</span> <span class="n">release_gc</span>
<span class="kn">from</span> <span class="nn">..auto_parallel</span> <span class="kn">import</span> <span class="n">AutoParallelConfig</span><span class="p">,</span> <span class="n">infer_cluster_config</span>
<span class="kn">from</span> <span class="nn">..bindings.executor</span> <span class="kn">import</span> <span class="p">(</span><span class="n">BatchingType</span><span class="p">,</span> <span class="n">CapacitySchedulerPolicy</span><span class="p">,</span>
<span class="n">ContextChunkingPolicy</span><span class="p">,</span> <span class="n">DecodingConfig</span><span class="p">,</span>
<span class="n">DecodingMode</span><span class="p">,</span> <span class="n">ExecutorConfig</span><span class="p">,</span>
<span class="n">ExtendedRuntimePerfKnobConfig</span><span class="p">,</span> <span class="n">KvCacheConfig</span><span class="p">,</span>
<span class="n">LookaheadDecodingConfig</span><span class="p">,</span> <span class="n">PeftCacheConfig</span><span class="p">,</span>
<span class="n">SchedulerConfig</span><span class="p">)</span>
<span class="kn">from</span> <span class="nn">..builder</span> <span class="kn">import</span> <span class="n">BuildConfig</span><span class="p">,</span> <span class="n">Engine</span><span class="p">,</span> <span class="n">EngineConfig</span><span class="p">,</span> <span class="n">build</span>
<span class="kn">from</span> <span class="nn">..logger</span> <span class="kn">import</span> <span class="n">logger</span>
<span class="kn">from</span> <span class="nn">..mapping</span> <span class="kn">import</span> <span class="n">Mapping</span>
<span class="kn">from</span> <span class="nn">..models.automodel</span> <span class="kn">import</span> <span class="n">MODEL_MAP</span><span class="p">,</span> <span class="n">AutoConfig</span><span class="p">,</span> <span class="n">AutoModelForCausalLM</span>
<span class="kn">from</span> <span class="nn">..models.modeling_utils</span> <span class="kn">import</span> <span class="p">(</span><span class="n">PretrainedConfig</span><span class="p">,</span> <span class="n">QuantAlgo</span><span class="p">,</span> <span class="n">QuantConfig</span><span class="p">,</span>
<span class="n">SpeculativeDecodingMode</span><span class="p">)</span>
<span class="kn">from</span> <span class="nn">..module</span> <span class="kn">import</span> <span class="n">Module</span>
<span class="kn">from</span> <span class="nn">.build_cache</span> <span class="kn">import</span> <span class="p">(</span><span class="n">BuildCache</span><span class="p">,</span> <span class="n">BuildCacheConfig</span><span class="p">,</span> <span class="n">CachedStage</span><span class="p">,</span>
<span class="n">get_build_cache_config_from_env</span><span class="p">)</span>
<span class="kn">from</span> <span class="nn">.mpi_session</span> <span class="kn">import</span> <span class="n">MPINodeState</span><span class="p">,</span> <span class="n">MpiSession</span>
<span class="kn">from</span> <span class="nn">.tokenizer</span> <span class="kn">import</span> <span class="p">(</span><span class="n">TokenizerBase</span><span class="p">,</span> <span class="n">TransformersTokenizer</span><span class="p">,</span> <span class="n">load_hf_tokenizer</span><span class="p">,</span>
<span class="n">tokenizer_factory</span><span class="p">)</span>
<span class="c1"># TODO[chunweiy]: move the following symbols back to utils scope, and remove the following import</span>
<span class="kn">from</span> <span class="nn">.utils</span> <span class="kn">import</span> <span class="p">(</span><span class="n">GpuArch</span><span class="p">,</span> <span class="n">append_docstring</span><span class="p">,</span> <span class="n">download_hf_model</span><span class="p">,</span>
<span class="n">download_hf_pretrained_config</span><span class="p">,</span> <span class="n">enable_llm_debug</span><span class="p">,</span>
<span class="n">get_directory_size_in_gb</span><span class="p">,</span> <span class="n">print_colored</span><span class="p">,</span>
<span class="n">print_traceback_on_error</span><span class="p">)</span>
<span class="nd">@dataclass</span>
<span class="k">class</span> <span class="nc">_ParallelConfig</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&#39;&#39;&#39; The model distribution configs for LLM. &#39;&#39;&#39;</span>
<span class="n">tp_size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1</span>
<span class="n">pp_size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1</span>
<span class="n">cp_size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1</span>
<span class="n">moe_tp_size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1</span>
<span class="n">moe_ep_size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1</span>
<span class="n">cp_config</span><span class="p">:</span> <span class="nb">dict</span> <span class="o">=</span> <span class="n">field</span><span class="p">(</span><span class="n">default_factory</span><span class="o">=</span><span class="nb">dict</span><span class="p">)</span>
<span class="n">auto_parallel</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
<span class="n">_world_size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">field</span><span class="p">(</span><span class="n">default</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">init</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
<span class="n">_devices</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">List</span><span class="p">[</span><span class="nb">int</span><span class="p">]]</span> <span class="o">=</span> <span class="n">field</span><span class="p">(</span><span class="n">default</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">init</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">devices</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">List</span><span class="p">[</span><span class="nb">int</span><span class="p">]:</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_devices</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="k">return</span> <span class="nb">list</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">world_size</span><span class="p">))</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_devices</span>
<span class="nd">@devices</span><span class="o">.</span><span class="n">setter</span>
<span class="k">def</span> <span class="nf">devices</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">devices</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="nb">int</span><span class="p">]):</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">devices</span><span class="p">)</span> <span class="o">!=</span> <span class="bp">self</span><span class="o">.</span><span class="n">world_size</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
<span class="sa">f</span><span class="s2">&quot;devices </span><span class="si">{</span><span class="n">devices</span><span class="si">}</span><span class="s2"> should have the same length as world_size </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">world_size</span><span class="si">}</span><span class="s2">&quot;</span>
<span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_devices</span> <span class="o">=</span> <span class="n">devices</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">world_size</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">bool</span><span class="p">:</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">auto_parallel</span><span class="p">:</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">tp_size</span> <span class="o">&gt;</span> <span class="mi">1</span> <span class="ow">or</span> <span class="bp">self</span><span class="o">.</span><span class="n">pp_size</span> <span class="o">&gt;</span> <span class="mi">1</span> <span class="ow">or</span> <span class="bp">self</span><span class="o">.</span><span class="n">cp_size</span> <span class="o">&gt;</span> <span class="mi">1</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span>
<span class="s2">&quot;manually TP and PP are not supported in auto parallel mode.&quot;</span>
<span class="p">)</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_world_size</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_world_size</span> <span class="o">&gt;</span> <span class="mi">1</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span>
<span class="s2">&quot;world_size &gt; 1 is only supported in auto parallel mode.&quot;</span><span class="p">)</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">tp_size</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">pp_size</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">cp_size</span>
<span class="nd">@world_size</span><span class="o">.</span><span class="n">setter</span>
<span class="k">def</span> <span class="nf">world_size</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">world_size</span><span class="p">:</span> <span class="nb">int</span><span class="p">):</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">auto_parallel</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_world_size</span> <span class="o">=</span> <span class="n">world_size</span>
<span class="k">elif</span> <span class="p">(</span><span class="ow">not</span> <span class="bp">self</span><span class="o">.</span><span class="n">auto_parallel</span>
<span class="p">)</span> <span class="ow">and</span> <span class="n">world_size</span> <span class="o">!=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tp_size</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">pp_size</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">cp_size</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
<span class="sa">f</span><span class="s2">&quot;world_size </span><span class="si">{</span><span class="n">world_size</span><span class="si">}</span><span class="s2"> should be equal to tp_size * pp_size </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">tp_size</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="bp">self</span><span class="o">.</span><span class="n">pp_size</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="bp">self</span><span class="o">.</span><span class="n">cp_size</span><span class="si">}</span><span class="s2"> &quot;</span>
<span class="p">)</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">is_multi_gpu</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">bool</span><span class="p">:</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">world_size</span> <span class="o">&gt;</span> <span class="mi">1</span>
<span class="k">def</span> <span class="nf">to_mapping</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Mapping</span><span class="p">:</span>
<span class="k">return</span> <span class="n">Mapping</span><span class="p">(</span><span class="n">world_size</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">world_size</span><span class="p">,</span>
<span class="n">rank</span><span class="o">=</span><span class="n">mpi_rank</span><span class="p">(),</span>
<span class="n">tp_size</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">tp_size</span><span class="p">,</span>
<span class="n">pp_size</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">pp_size</span><span class="p">,</span>
<span class="n">cp_size</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">cp_size</span><span class="p">,</span>
<span class="n">cp_config</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">cp_config</span><span class="p">,</span>
<span class="n">moe_tp_size</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">moe_tp_size</span><span class="p">,</span>
<span class="n">moe_ep_size</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">moe_ep_size</span><span class="p">,</span>
<span class="n">auto_parallel</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">auto_parallel</span><span class="p">)</span>
<div class="viewcode-block" id="CalibConfig">
<a class="viewcode-back" href="../../../llm-api/reference.html#tensorrt_llm.llmapi.CalibConfig">[docs]</a>
<span class="nd">@dataclass</span><span class="p">(</span><span class="n">slots</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="k">class</span> <span class="nc">CalibConfig</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Calibration configuration.</span>
<span class="sd"> Args:</span>
<span class="sd"> device (Literal[&#39;cuda&#39;, &#39;cpu&#39;], default=&#39;cuda&#39;): The device to run calibration.</span>
<span class="sd"> calib_dataset (str, default=&#39;cnn_dailymail&#39;): The name or local path of calibration dataset.</span>
<span class="sd"> calib_batches (int, default=512): The number of batches that the calibration runs.</span>
<span class="sd"> calib_batch_size (int, default=1): The batch size that the calibration runs.</span>
<span class="sd"> calib_max_seq_length (int, default=512): The maximum sequence length that the calibration runs.</span>
<span class="sd"> random_seed (int, default=1234): The random seed used for calibration.</span>
<span class="sd"> tokenizer_max_seq_length (int, default=2048): The maximum sequence length to initialize tokenizer for calibration.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">device</span><span class="p">:</span> <span class="n">Literal</span><span class="p">[</span><span class="s1">&#39;cuda&#39;</span><span class="p">,</span> <span class="s1">&#39;cpu&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="s1">&#39;cuda&#39;</span>
<span class="n">calib_dataset</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s1">&#39;cnn_dailymail&#39;</span>
<span class="n">calib_batches</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">512</span>
<span class="n">calib_batch_size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1</span>
<span class="n">calib_max_seq_length</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">512</span>
<span class="n">random_seed</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1234</span>
<span class="n">tokenizer_max_seq_length</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">2048</span>
<div class="viewcode-block" id="CalibConfig.from_dict">
<a class="viewcode-back" href="../../../llm-api/reference.html#tensorrt_llm.llmapi.CalibConfig.from_dict">[docs]</a>
<span class="nd">@classmethod</span>
<span class="k">def</span> <span class="nf">from_dict</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="n">config</span><span class="p">:</span> <span class="nb">dict</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">cls</span><span class="p">(</span><span class="o">**</span><span class="n">config</span><span class="p">)</span></div>
<div class="viewcode-block" id="CalibConfig.to_dict">
<a class="viewcode-back" href="../../../llm-api/reference.html#tensorrt_llm.llmapi.CalibConfig.to_dict">[docs]</a>
<span class="k">def</span> <span class="nf">to_dict</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">asdict</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span></div>
</div>
<span class="k">class</span> <span class="nc">_ModelFormatKind</span><span class="p">(</span><span class="n">Enum</span><span class="p">):</span>
<span class="n">HF</span> <span class="o">=</span> <span class="mi">0</span>
<span class="n">TLLM_CKPT</span> <span class="o">=</span> <span class="mi">1</span>
<span class="n">TLLM_ENGINE</span> <span class="o">=</span> <span class="mi">2</span>
<span class="nd">@dataclass</span>
<span class="k">class</span> <span class="nc">_ModelInfo</span><span class="p">:</span>
<span class="n">dtype</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">architecture</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">model_name</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">str</span><span class="p">:</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">architecture</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="s2">&quot;The architecture is not set yet.&quot;</span><span class="p">)</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">architecture</span>
<span class="nd">@classmethod</span>
<span class="k">def</span> <span class="nf">from_pretrained_config</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="n">config</span><span class="p">:</span> <span class="n">PretrainedConfig</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">cls</span><span class="p">(</span><span class="n">dtype</span><span class="o">=</span><span class="n">config</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span> <span class="n">architecture</span><span class="o">=</span><span class="n">config</span><span class="o">.</span><span class="n">architecture</span><span class="p">)</span>
<span class="nd">@classmethod</span>
<span class="k">def</span> <span class="nf">from_builder_config_json</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="n">config</span><span class="p">:</span> <span class="nb">dict</span><span class="p">):</span>
<span class="k">if</span> <span class="s1">&#39;version&#39;</span> <span class="ow">in</span> <span class="n">config</span><span class="p">:</span>
<span class="c1"># The Dict format is { &#39;builder_config&#39;:..., &#39;plugin_config&#39;:...}</span>
<span class="n">dtype</span> <span class="o">=</span> <span class="n">config</span><span class="p">[</span><span class="s1">&#39;plugin_config&#39;</span><span class="p">][</span><span class="s1">&#39;gpt_attention_plugin&#39;</span><span class="p">]</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">dtype</span> <span class="o">=</span> <span class="n">config</span><span class="p">[</span><span class="s1">&#39;pretrained_config&#39;</span><span class="p">][</span><span class="s1">&#39;dtype&#39;</span><span class="p">]</span>
<span class="k">return</span> <span class="bp">cls</span><span class="p">(</span><span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">,</span> <span class="n">architecture</span><span class="o">=</span><span class="n">config</span><span class="p">[</span><span class="s1">&#39;builder_config&#39;</span><span class="p">][</span><span class="s1">&#39;name&#39;</span><span class="p">])</span>
<span class="nd">@classmethod</span>
<span class="k">def</span> <span class="nf">from_module</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="n">module</span><span class="p">:</span> <span class="n">Module</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">()</span>
<div class="viewcode-block" id="MedusaDecodingConfig">
<a class="viewcode-back" href="../../../llm-api/reference.html#tensorrt_llm.llmapi.MedusaDecodingConfig">[docs]</a>
<span class="nd">@dataclass</span>
<span class="k">class</span> <span class="nc">MedusaDecodingConfig</span><span class="p">:</span>
<span class="n">medusa_choices</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">List</span><span class="p">[</span><span class="n">List</span><span class="p">[</span><span class="nb">int</span><span class="p">]]]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">num_medusa_heads</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span></div>
<span class="nd">@dataclass</span>
<span class="k">class</span> <span class="nc">_ModelWrapper</span><span class="p">:</span>
<span class="n">model</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Path</span><span class="p">]</span>
<span class="k">def</span> <span class="nf">__post_init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">if</span> <span class="ow">not</span> <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">&quot;model should be provided.&quot;</span><span class="p">)</span>
<span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">,</span>
<span class="p">(</span><span class="nb">str</span><span class="p">,</span> <span class="n">Path</span><span class="p">)),</span> <span class="sa">f</span><span class="s2">&quot;Invalid model: </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="si">}</span><span class="s2">&quot;</span>
<span class="n">model_dir</span> <span class="o">=</span> <span class="n">Path</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">)</span>
<span class="k">if</span> <span class="n">model_dir</span><span class="o">.</span><span class="n">exists</span><span class="p">()</span> <span class="ow">and</span> <span class="n">model_dir</span><span class="o">.</span><span class="n">is_dir</span><span class="p">():</span>
<span class="bp">self</span><span class="o">.</span><span class="n">model</span> <span class="o">=</span> <span class="n">model_dir</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">is_hub_model</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">bool</span><span class="p">:</span>
<span class="k">return</span> <span class="ow">not</span> <span class="bp">self</span><span class="o">.</span><span class="n">is_local_model</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">is_local_model</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">bool</span><span class="p">:</span>
<span class="k">return</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">,</span> <span class="n">Path</span><span class="p">)</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">model_dir</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Path</span><span class="p">:</span>
<span class="k">assert</span> <span class="bp">self</span><span class="o">.</span><span class="n">is_local_model</span><span class="p">,</span> <span class="sa">f</span><span class="s2">&quot;model_dir is only available for local model, </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="si">}</span><span class="s2">.&quot;</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">model</span>
<span class="nd">@model_dir</span><span class="o">.</span><span class="n">setter</span>
<span class="k">def</span> <span class="nf">model_dir</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">model_dir</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Path</span><span class="p">]):</span>
<span class="n">model_dir</span> <span class="o">=</span> <span class="n">Path</span><span class="p">(</span><span class="n">model_dir</span><span class="p">)</span>
<span class="k">assert</span> <span class="n">model_dir</span><span class="o">.</span><span class="n">exists</span><span class="p">()</span> <span class="ow">and</span> <span class="n">model_dir</span><span class="o">.</span><span class="n">is_dir</span><span class="p">(</span>
<span class="p">),</span> <span class="sa">f</span><span class="s2">&quot;model_dir is not a valid path, </span><span class="si">{</span><span class="n">model_dir</span><span class="si">}</span><span class="s2">&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">model</span> <span class="o">=</span> <span class="n">model_dir</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">model_name</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Path</span><span class="p">]:</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">model</span> <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">,</span> <span class="nb">str</span><span class="p">)</span> <span class="k">else</span> <span class="kc">None</span>
<span class="c1"># The docstring for LlmArgs and LLM; will be appended to the two classes&#39; apidocs.</span>
<span class="n">LLMARGS_DOCSTRING</span> <span class="o">=</span> <span class="sa">r</span><span class="s2">&quot;&quot;&quot;</span>
<span class="s2"> model (str or Path): The model name or a local model directory.</span>
<span class="s2"> Note that if the value could be both a model name or a local model directory,</span>
<span class="s2"> the local model directory will be prioritized.</span>
<span class="s2"> tokenizer (str, Path, TokenizerBase, PreTrainedTokenizerBase, optional):</span>
<span class="s2"> The name or path of a HuggingFace Transformers tokenizer, or the loaded tokenizer.</span>
<span class="s2"> Defaults to None.</span>
<span class="s2"> tokenizer_mode (Literal[&#39;auto&#39;, &#39;slow&#39;]): The tokenizer mode.</span>
<span class="s2"> &#39;auto&#39; will use the fast tokenizer if available, and &#39;slow&#39; will always use the slow tokenizer.</span>
<span class="s2"> The fast tokenizer is based on Huggingface&#39;s Rust library tokenizers, which achieves a significant speed-up compared to its slow counterpart.</span>
<span class="s2"> Defaults to &#39;auto&#39;.</span>
<span class="s2"> skip_tokenizer_init (bool):</span>
<span class="s2"> If true, skip initialization of tokenizer and detokenizer.</span>
<span class="s2"> LLM.generate and LLM.generate_async will accept prompt token ids as input only.</span>
<span class="s2"> Defaults to False.</span>
<span class="s2"> trust_remote_code (bool): Whether to trust remote code when downloading model and tokenizer from Hugging Face. Defaults to False.</span>
<span class="s2"> tensor_parallel_size(int): The number of processes for tensor parallelism. Defaults to 1.</span>
<span class="s2"> dtype (str): The data type for the model weights and activations.</span>
<span class="s2"> Can be &quot;float16&quot;, &quot;bfloat16&quot;, &quot;float32&quot;, or &quot;auto&quot;. If &quot;auto&quot;, the data type</span>
<span class="s2"> will be automatically inferred from the source model. If the source data type</span>
<span class="s2"> is &quot;float32&quot;, it will be converted to &quot;float16&quot;. Defaults to &quot;auto&quot;.</span>
<span class="s2"> revision (str, optional): The revision of the model to use. Defaults to None.</span>
<span class="s2"> tokenizer_revision (str, optional): The revision of the tokenizer to use. Defaults to None.</span>
<span class="s2"> pipeline_parallel_size (int): The pipeline parallel size. Defaults to 1.</span>
<span class="s2"> context_parallel_size (int): The context parallel size. Defaults to 1.</span>
<span class="s2"> load_format (Literal[&#39;auto&#39;, &#39;dummy&#39;]): The format of the model weights to load.</span>
<span class="s2"> * &#39;auto&#39; will try to load the weights from the provided checkpoint.</span>
<span class="s2"> * &#39;dummy&#39; will initialize the weights with random values, which is mainly for profiling.</span>
<span class="s2"> Defaults to &#39;auto&#39;.</span>
<span class="s2"> enable_tqdm (bool): Whether to display a progress bar during model building. Defaults to False.</span>
<span class="s2"> enable_lora (bool): Enable LoRA adapters. Defaults to False.</span>
<span class="s2"> max_lora_rank (int, optional): Maximum LoRA rank. If specified, it overrides `build_config.lora_config.max_lora_rank`. Defaults to None.</span>
<span class="s2"> max_loras (int): Maximum number of LoRA adapters to be stored in GPU memory. Defaults to 4.</span>
<span class="s2"> max_cpu_loras (int): Maximum number of LoRA adapters to be stored in CPU memory. Defaults to 4.</span>
<span class="s2"> enable_prompt_adapter (bool): Enable prompt adapters. Defaults to False.</span>
<span class="s2"> max_prompt_adapter_token (int): Maximum number of prompt adapter tokens. Defaults to 0.</span>
<span class="s2"> quant_config (QuantConfig, optional): The quantization configuration for the model. Defaults to None.</span>
<span class="s2"> calib_config (CalibConfig, optional): The calibration configuration for the model. Defaults to None.</span>
<span class="s2"> build_config (BuildConfig, optional)): The build configuration for the model. Defaults to None.</span>
<span class="s2"> kv_cache_config (KvCacheConfig, optional): The key-value cache configuration for the model. Defaults to None.</span>
<span class="s2"> enable_chunked_prefill (bool): Whether to enable chunked prefill. Defaults to False.</span>
<span class="s2"> decoding_config (DecodingConfig, optional): The decoding configuration for the model. Defaults to None.</span>
<span class="s2"> guided_decoding_backend (str, optional): The guided decoding backend, currently supports &#39;xgrammar&#39;. Defaults to None.</span>
<span class="s2"> logits_post_processor_map (Dict[str, Callable], optional): A map of logit post-processing functions. Defaults to None.</span>
<span class="s2"> iter_stats_max_iterations (int, optional): The maximum number of iterations for iteration statistics. Defaults to None.</span>
<span class="s2"> request_stats_max_iterations (int, optional): The maximum number of iterations for request statistics. Defaults to None.</span>
<span class="s2"> workspace(str, optional): The directory to store intermediate files. Defaults to None.</span>
<span class="s2"> embedding_parallel_mode (str): The parallel mode for embeddings. Defaults to &#39;SHARDING_ALONG_VOCAB&#39;.</span>
<span class="s2"> auto_parallel (bool): Enable auto parallel mode. Defaults to False.</span>
<span class="s2"> auto_parallel_world_size (int): The MPI world size for auto parallel. Defaults to 1.</span>
<span class="s2"> moe_tensor_parallel_size (int, optional): The tensor parallel size for MoE models&#39;s expert weights.</span>
<span class="s2"> moe_expert_parallel_size (int, optional): The expert parallel size for MoE models&#39;s expert weights.</span>
<span class="s2"> fast_build: (bool): Enable features for faster engine building.</span>
<span class="s2"> This may cause some performance degradation and is currently incompatible with int8/int4 quantization.</span>
<span class="s2"> Defaults to False.</span>
<span class="s2"> enable_build_cache (bool, BuildCacheConfig, optional): Whether to enable build caching for the model. Defaults to None.</span>
<span class="s2"> peft_cache_config (PeftCacheConfig, optional): The PEFT cache configuration for the model. Defaults to None.</span>
<span class="s2"> scheduler_config (SchedulerConfig, optional): The scheduler configuration for the model. Defaults to None.</span>
<span class="s2"> speculative_config (LookaheadDecodingConfig or other speculative configurations, optional): The speculative decoding configuration. Defaults to None.</span>
<span class="s2"> batching_type (BatchingType, optional): The batching type for the model. Defaults to None.</span>
<span class="s2"> normalize_log_probs (bool): Whether to normalize log probabilities for the model. Defaults to False.</span>
<span class="s2"> max_batch_size (int, optional): The maximum batch size for runtime. Defaults to None.</span>
<span class="s2"> max_num_tokens (int, optional): The maximum number of tokens for runtime. Defaults to None.</span>
<span class="s2"> extended_runtime_perf_knob_config (ExtendedRuntimePerfKnobConfig, optional): The extended runtime performance knob configuration for the model. Defaults to None.</span>
<span class="s2">&quot;&quot;&quot;</span>
<span class="nd">@append_docstring</span><span class="p">(</span><span class="n">LLMARGS_DOCSTRING</span><span class="p">)</span>
<span class="nd">@dataclass</span>
<span class="k">class</span> <span class="nc">LlmArgs</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;The arguments for constructing a LLM instance.</span>
<span class="sd"> Parameters:</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="c1"># Explicit arguments</span>
<span class="n">model</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Path</span><span class="p">]</span>
<span class="n">speculative_model</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Path</span><span class="p">]]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">tokenizer</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Path</span><span class="p">,</span> <span class="n">TokenizerBase</span><span class="p">,</span>
<span class="n">PreTrainedTokenizerBase</span><span class="p">]]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">tokenizer_mode</span><span class="p">:</span> <span class="n">Literal</span><span class="p">[</span><span class="s1">&#39;auto&#39;</span><span class="p">,</span> <span class="s1">&#39;slow&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="s1">&#39;auto&#39;</span>
<span class="n">skip_tokenizer_init</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
<span class="n">trust_remote_code</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
<span class="n">tensor_parallel_size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1</span>
<span class="n">dtype</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">&quot;auto&quot;</span>
<span class="n">revision</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">tokenizer_revision</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="c1"># Below are all remaining arguments</span>
<span class="n">pipeline_parallel_size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1</span>
<span class="n">context_parallel_size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1</span>
<span class="n">moe_tensor_parallel_size</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">moe_expert_parallel_size</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">cp_config</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">dict</span><span class="p">]</span> <span class="o">=</span> <span class="n">field</span><span class="p">(</span><span class="n">default_factory</span><span class="o">=</span><span class="nb">dict</span><span class="p">)</span>
<span class="n">auto_parallel</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
<span class="n">auto_parallel_world_size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1</span>
<span class="n">load_format</span><span class="p">:</span> <span class="n">Literal</span><span class="p">[</span><span class="s1">&#39;auto&#39;</span><span class="p">,</span> <span class="s1">&#39;dummy&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="s1">&#39;auto&#39;</span>
<span class="n">enable_tqdm</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
<span class="c1"># LoRA arguments</span>
<span class="n">enable_lora</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
<span class="n">max_lora_rank</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">max_loras</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">4</span>
<span class="n">max_cpu_loras</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">4</span>
<span class="c1"># Prompt adapter arguments</span>
<span class="n">enable_prompt_adapter</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
<span class="n">max_prompt_adapter_token</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">0</span>
<span class="c1"># Quantization and calibration configurations</span>
<span class="n">quant_config</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">QuantConfig</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">calib_config</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">CalibConfig</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="c1"># BuildConfig is introduced to give users a familiar interface to configure the model building.</span>
<span class="n">build_config</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">BuildConfig</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="c1"># Several options from ExecutorConfig, expanded here for less hierarchy</span>
<span class="n">kv_cache_config</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">KvCacheConfig</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">enable_chunked_prefill</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
<span class="c1"># TODO[enweiz]: this might affect medusa, and could be removed in the future for API consistency</span>
<span class="n">decoding_config</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">DecodingConfig</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">guided_decoding_backend</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">logits_post_processor_map</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Callable</span><span class="p">]]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">iter_stats_max_iterations</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">request_stats_max_iterations</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">workspace</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="c1"># A handful of options from PretrainedConfig</span>
<span class="n">embedding_parallel_mode</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s1">&#39;SHARDING_ALONG_VOCAB&#39;</span>
<span class="n">fast_build</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
<span class="c1"># Once set, the model will reuse the build_cache</span>
<span class="n">enable_build_cache</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="n">BuildCacheConfig</span><span class="p">,</span> <span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="kc">False</span>
<span class="n">peft_cache_config</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">PeftCacheConfig</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">scheduler_config</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">SchedulerConfig</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="c1"># Speculative decoding parameters</span>
<span class="n">speculative_config</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="n">LookaheadDecodingConfig</span><span class="p">]]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">batching_type</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">BatchingType</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">normalize_log_probs</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
<span class="n">extended_runtime_perf_knob_config</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span>
<span class="n">ExtendedRuntimePerfKnobConfig</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="c1"># TODO: remove this option in the future</span>
<span class="n">use_runtime_defaults</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span>
<span class="n">max_batch_size</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">max_num_tokens</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="c1"># PIVOT_TO_PYTHON_START</span>
<span class="c1"># backend to use</span>
<span class="n">backend</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="c1"># Extra PyTorch backend options, ignored if backend != &quot;pytorch&quot;.</span>
<span class="kn">from</span> <span class="nn">tensorrt_llm.pyexecutor.config</span> <span class="kn">import</span> <span class="n">PyTorchConfig</span>
<span class="n">pytorch_backend_config</span><span class="p">:</span> <span class="n">PyTorchConfig</span> <span class="o">=</span> <span class="n">field</span><span class="p">(</span><span class="n">default_factory</span><span class="o">=</span><span class="n">PyTorchConfig</span><span class="p">)</span>
<span class="c1"># PIVOT_TO_PYTHON_END</span>
<span class="c1"># private options</span>
<span class="n">_num_postprocess_workers</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">0</span> <span class="c1"># Number of postprocess worker processes</span>
<span class="n">_postprocess_tokenizer_dir</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">_postprocess_result_handler</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Callable</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="k">def</span> <span class="nf">__post_init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="c1"># TODO[chunweiy]: Enable this option in the future</span>
<span class="c1"># Currently we want LLMAPI to be consistent with the lower APIs in the model building, thus disable this to avoid</span>
<span class="c1"># magics.</span>
<span class="bp">self</span><span class="o">.</span><span class="n">perform_config_arbitration</span> <span class="o">=</span> <span class="kc">False</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">skip_tokenizer_init</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">tokenizer</span> <span class="o">=</span> <span class="kc">None</span>
<span class="k">else</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">tokenizer</span> <span class="o">=</span> <span class="n">tokenizer_factory</span><span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">tokenizer</span><span class="p">,</span>
<span class="n">rust_remote_code</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">trust_remote_code</span><span class="p">,</span>
<span class="n">use_fast</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">tokenizer_mode</span> <span class="o">!=</span> <span class="s1">&#39;slow&#39;</span><span class="p">)</span>
<span class="k">if</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">get_device_properties</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">major</span> <span class="o">&lt;</span> <span class="mi">8</span><span class="p">:</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">dtype</span> <span class="o">==</span> <span class="s1">&#39;auto&#39;</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">dtype</span> <span class="o">=</span> <span class="s1">&#39;float16&#39;</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">dtype</span> <span class="o">==</span> <span class="s1">&#39;bfloat16&#39;</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="s2">&quot;Pre SM 80 GPUs do not support bfloat16&quot;</span><span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">moe_tensor_parallel_size</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">moe_tensor_parallel_size</span> <span class="o">=</span> <span class="o">-</span><span class="mi">1</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">moe_expert_parallel_size</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">moe_expert_parallel_size</span> <span class="o">=</span> <span class="o">-</span><span class="mi">1</span>
<span class="bp">self</span><span class="o">.</span><span class="n">parallel_config</span> <span class="o">=</span> <span class="n">_ParallelConfig</span><span class="p">(</span>
<span class="n">tp_size</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">tensor_parallel_size</span><span class="p">,</span>
<span class="n">pp_size</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">pipeline_parallel_size</span><span class="p">,</span>
<span class="n">cp_size</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">context_parallel_size</span><span class="p">,</span>
<span class="n">moe_tp_size</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">moe_tensor_parallel_size</span><span class="p">,</span>
<span class="n">moe_ep_size</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">moe_expert_parallel_size</span><span class="p">,</span>
<span class="n">cp_config</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">cp_config</span><span class="p">,</span>
<span class="n">auto_parallel</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">auto_parallel</span><span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">parallel_config</span><span class="o">.</span><span class="n">auto_parallel</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">parallel_config</span><span class="o">.</span><span class="n">world_size</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">auto_parallel_world_size</span>
<span class="bp">self</span><span class="o">.</span><span class="n">auto_parallel_config</span> <span class="o">=</span> <span class="n">AutoParallelConfig</span><span class="p">(</span>
<span class="n">sharded_io_allowlist</span><span class="o">=</span><span class="p">[</span>
<span class="s2">&quot;past_key_value_</span><span class="se">\\</span><span class="s2">d+&quot;</span><span class="p">,</span>
<span class="s2">&quot;present_key_value_</span><span class="se">\\</span><span class="s2">d*&quot;</span><span class="p">,</span>
<span class="p">],</span>
<span class="n">same_buffer_io</span><span class="o">=</span><span class="p">{</span>
<span class="s2">&quot;past_key_value_(</span><span class="se">\\</span><span class="s2">d+)&quot;</span><span class="p">:</span> <span class="s2">&quot;present_key_value_</span><span class="se">\\</span><span class="s2">1&quot;</span><span class="p">,</span>
<span class="p">},</span>
<span class="o">**</span><span class="n">infer_cluster_config</span><span class="p">(),</span>
<span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">kv_cache_config</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">kv_cache_config</span> <span class="ow">or</span> <span class="n">KvCacheConfig</span><span class="p">()</span>
<span class="bp">self</span><span class="o">.</span><span class="n">scheduler_config</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">scheduler_config</span> <span class="ow">or</span> <span class="n">SchedulerConfig</span><span class="p">()</span>
<span class="c1"># This is used to hold th options for convert_checkpoint</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_convert_checkpoint_options</span> <span class="o">=</span> <span class="p">{}</span>
<span class="nd">@classmethod</span>
<span class="k">def</span> <span class="nf">from_kwargs</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="s2">&quot;LlmArgs&quot;</span><span class="p">:</span>
<span class="n">LlmArgs</span><span class="o">.</span><span class="n">_check_executor_config_options_consistency</span><span class="p">()</span>
<span class="n">ret</span> <span class="o">=</span> <span class="bp">cls</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="n">ret</span><span class="o">.</span><span class="n">setup</span><span class="p">()</span>
<span class="k">return</span> <span class="n">ret</span>
<span class="k">def</span> <span class="nf">to_dict</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="nb">dict</span><span class="p">(</span>
<span class="p">(</span><span class="n">field</span><span class="o">.</span><span class="n">name</span><span class="p">,</span> <span class="nb">getattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">field</span><span class="o">.</span><span class="n">name</span><span class="p">))</span> <span class="k">for</span> <span class="n">field</span> <span class="ow">in</span> <span class="n">fields</span><span class="p">(</span><span class="bp">self</span><span class="p">))</span>
<span class="nd">@staticmethod</span>
<span class="k">def</span> <span class="nf">_check_executor_config_options_consistency</span><span class="p">():</span>
<span class="c1"># max_beam_width is not included since vague behavior due to lacking the support for dynamic beam width during</span>
<span class="c1"># generation</span>
<span class="n">black_list</span> <span class="o">=</span> <span class="nb">set</span><span class="p">([</span><span class="s2">&quot;max_beam_width&quot;</span><span class="p">])</span>
<span class="n">executor_config_attrs</span> <span class="o">=</span> <span class="nb">set</span><span class="p">(</span><span class="n">attr</span> <span class="k">for</span> <span class="n">attr</span> <span class="ow">in</span> <span class="nb">dir</span><span class="p">(</span><span class="n">ExecutorConfig</span><span class="p">)</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">attr</span><span class="o">.</span><span class="n">startswith</span><span class="p">(</span><span class="s1">&#39;_&#39;</span><span class="p">)</span>
<span class="ow">and</span> <span class="nb">callable</span><span class="p">(</span><span class="nb">getattr</span><span class="p">(</span><span class="n">ExecutorConfig</span><span class="p">,</span> <span class="n">attr</span><span class="p">)))</span>
<span class="n">executor_config_attrs</span> <span class="o">-=</span> <span class="n">black_list</span>
<span class="n">llm_args_attr</span> <span class="o">=</span> <span class="nb">set</span><span class="p">([</span><span class="n">f</span><span class="o">.</span><span class="n">name</span> <span class="k">for</span> <span class="n">f</span> <span class="ow">in</span> <span class="n">fields</span><span class="p">(</span><span class="n">LlmArgs</span><span class="p">)])</span>
<span class="c1"># NOTE: When cpp ExecutorConfig add new options, please add the new options into `_LlmArgs` with docs as well</span>
<span class="c1"># ASK chunweiy for help if you are not sure about the new options.</span>
<span class="k">assert</span> <span class="n">executor_config_attrs</span><span class="o">.</span><span class="n">issubset</span><span class="p">(</span>
<span class="n">llm_args_attr</span>
<span class="p">),</span> <span class="sa">f</span><span class="s2">&quot;New options found in underlying ExecutorConfig: </span><span class="si">{</span><span class="n">llm_args_attr</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="n">executor_config_attrs</span><span class="si">}</span><span class="s2">&quot;</span>
<span class="k">def</span> <span class="nf">setup</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="w"> </span><span class="sd">&#39;&#39;&#39; This method will setup the configs right before building the model.</span>
<span class="sd"> It will check the consistency of the configs and arbitrate the conflicts.</span>
<span class="sd"> &#39;&#39;&#39;</span>
<span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">,</span>
<span class="p">(</span><span class="nb">str</span><span class="p">,</span> <span class="n">Path</span><span class="p">)),</span> <span class="sa">f</span><span class="s2">&quot;Invalid model: </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="si">}</span><span class="s2">&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_setup_embedding_parallel_mode</span><span class="p">()</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">enable_build_cache</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">enable_build_cache</span> <span class="o">=</span> <span class="n">BuildCacheConfig</span><span class="p">()</span> <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">enable_build_cache</span><span class="p">,</span> <span class="nb">bool</span><span class="p">)</span> <span class="k">else</span> <span class="bp">self</span><span class="o">.</span><span class="n">enable_build_cache</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">enable_build_cache</span><span class="p">,</span> <span class="n">BuildCacheConfig</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
<span class="sa">f</span><span class="s2">&quot;Invalid build_cache_config: </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">enable_build_cache</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
<span class="n">model_obj</span> <span class="o">=</span> <span class="n">_ModelWrapper</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">)</span>
<span class="n">speculative_model_obj</span> <span class="o">=</span> <span class="n">_ModelWrapper</span><span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">speculative_model</span>
<span class="p">)</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">speculative_model</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="k">else</span> <span class="kc">None</span>
<span class="k">if</span> <span class="n">model_obj</span><span class="o">.</span><span class="n">is_local_model</span> <span class="ow">and</span> <span class="nb">getattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;backend&#39;</span><span class="p">,</span>
<span class="kc">None</span><span class="p">)</span> <span class="o">!=</span> <span class="s1">&#39;pytorch&#39;</span><span class="p">:</span>
<span class="c1"># Load parallel_config from the engine.</span>
<span class="bp">self</span><span class="o">.</span><span class="n">model_format</span> <span class="o">=</span> <span class="n">ModelLoader</span><span class="o">.</span><span class="n">get_model_format</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">model_format</span> <span class="ow">is</span> <span class="n">_ModelFormatKind</span><span class="o">.</span><span class="n">TLLM_ENGINE</span><span class="p">:</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">build_config</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">logger</span><span class="o">.</span><span class="n">warning</span><span class="p">(</span>
<span class="s2">&quot;The build_config is ignored for model format of TLLM_ENGINE.&quot;</span>
<span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_load_config_from_engine</span><span class="p">(</span><span class="n">model_obj</span><span class="o">.</span><span class="n">model_dir</span><span class="p">)</span>
<span class="n">runtime_defaults</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_pretrained_config</span><span class="o">.</span><span class="n">runtime_defaults</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">use_runtime_defaults</span> <span class="ow">and</span> <span class="n">runtime_defaults</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">kv_cache_config</span><span class="o">.</span><span class="n">fill_empty_fields_from_runtime_defaults</span><span class="p">(</span>
<span class="n">runtime_defaults</span><span class="p">)</span>
<span class="c1"># Load parallel_config from the checkpoint.</span>
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">model_format</span> <span class="ow">is</span> <span class="n">_ModelFormatKind</span><span class="o">.</span><span class="n">TLLM_CKPT</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_load_config_from_ckpt</span><span class="p">(</span><span class="n">model_obj</span><span class="o">.</span><span class="n">model_dir</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">model_format</span> <span class="o">=</span> <span class="n">_ModelFormatKind</span><span class="o">.</span><span class="n">HF</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">speculative_model</span> <span class="ow">and</span> <span class="n">speculative_model_obj</span><span class="o">.</span><span class="n">is_local_model</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">speculative_model_format</span> <span class="o">=</span> <span class="n">_ModelFormatKind</span><span class="o">.</span><span class="n">HF</span>
<span class="bp">self</span><span class="o">.</span><span class="n">quant_config</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">quant_config</span> <span class="ow">or</span> <span class="n">QuantConfig</span><span class="p">()</span>
<span class="bp">self</span><span class="o">.</span><span class="n">calib_config</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">calib_config</span> <span class="ow">or</span> <span class="n">CalibConfig</span><span class="p">()</span>
<span class="bp">self</span><span class="o">.</span><span class="n">build_config</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">build_config</span> <span class="ow">or</span> <span class="n">BuildConfig</span><span class="p">()</span>
<span class="c1"># TODO(xiweny): remove the checker when manage weights support all data types</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">fast_build</span> <span class="ow">and</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">quant_config</span><span class="o">.</span><span class="n">quant_algo</span> <span class="ow">is</span> <span class="n">QuantAlgo</span><span class="o">.</span><span class="n">FP8</span>
<span class="ow">or</span> <span class="bp">self</span><span class="o">.</span><span class="n">quant_config</span><span class="o">.</span><span class="n">quant_algo</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_update_plugin_config</span><span class="p">(</span><span class="s2">&quot;manage_weights&quot;</span><span class="p">,</span> <span class="kc">True</span><span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">parallel_config</span><span class="o">.</span><span class="n">_world_size</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">build_config</span><span class="o">.</span><span class="n">plugin_config</span><span class="o">.</span><span class="n">nccl_plugin</span> <span class="o">=</span> <span class="kc">None</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">enable_lora</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">build_config</span><span class="o">.</span><span class="n">plugin_config</span><span class="o">.</span><span class="n">lora_plugin</span> <span class="o">=</span> <span class="s1">&#39;auto&#39;</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_lora_rank</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">build_config</span><span class="o">.</span><span class="n">lora_config</span><span class="o">.</span><span class="n">max_lora_rank</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_lora_rank</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">enable_prompt_adapter</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">build_config</span><span class="o">.</span><span class="n">max_prompt_embedding_table_size</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_prompt_adapter_token</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">build_config</span><span class="o">.</span><span class="n">max_batch_size</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">perform_config_arbitration</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_perform_config_arbitration</span><span class="p">()</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">speculative_config</span><span class="p">:</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">speculative_config</span><span class="p">,</span> <span class="n">LookaheadDecodingConfig</span><span class="p">):</span>
<span class="n">lookahead_config</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">speculative_config</span>
<span class="c1"># Update the build config</span>
<span class="n">_</span><span class="p">,</span> <span class="n">_</span><span class="p">,</span> <span class="n">max_draft_tokens</span><span class="p">,</span> <span class="n">_</span> <span class="o">=</span> <span class="n">lookahead_config</span><span class="o">.</span><span class="n">calculate_speculative_resource</span><span class="p">(</span>
<span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">build_config</span><span class="o">.</span><span class="n">speculative_decoding_mode</span> <span class="o">=</span> <span class="n">SpeculativeDecodingMode</span><span class="o">.</span><span class="n">LOOKAHEAD_DECODING</span>
<span class="k">if</span> <span class="n">max_draft_tokens</span> <span class="o">&gt;</span> <span class="bp">self</span><span class="o">.</span><span class="n">build_config</span><span class="o">.</span><span class="n">max_draft_len</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">build_config</span><span class="o">.</span><span class="n">max_draft_len</span> <span class="o">=</span> <span class="n">max_draft_tokens</span>
<span class="bp">self</span><span class="o">.</span><span class="n">decoding_config</span> <span class="o">=</span> <span class="n">DecodingConfig</span><span class="p">(</span>
<span class="n">decoding_mode</span><span class="o">=</span><span class="n">DecodingMode</span><span class="o">.</span><span class="n">Lookahead</span><span class="p">(),</span>
<span class="n">lookahead_decoding_config</span><span class="o">=</span><span class="n">lookahead_config</span><span class="p">)</span>
<span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">speculative_config</span><span class="p">,</span> <span class="n">MedusaDecodingConfig</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">decoding_config</span> <span class="o">=</span> <span class="n">DecodingConfig</span><span class="p">(</span>
<span class="n">decoding_mode</span><span class="o">=</span><span class="n">DecodingMode</span><span class="o">.</span><span class="n">Medusa</span><span class="p">(),</span>
<span class="n">medusa_choices</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">speculative_config</span><span class="o">.</span><span class="n">medusa_choices</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Speculative config type not recognized&quot;</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">_perform_config_arbitration</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="w"> </span><span class="sd">&#39;&#39;&#39;</span>
<span class="sd"> Arbitrate the configurations for the model building. The configs between different functional or performance</span>
<span class="sd"> features might be conflicted, and this method will arbitrate the conflicts and raise errors if necessary.</span>
<span class="sd"> &#39;&#39;&#39;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_config_arbitrator</span> <span class="o">=</span> <span class="n">_ConfigArbitrator</span><span class="p">()</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">build_config_mutable</span><span class="p">:</span>
<span class="k">if</span> <span class="ow">not</span> <span class="bp">self</span><span class="o">.</span><span class="n">build_config</span><span class="o">.</span><span class="n">max_num_tokens</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">build_config</span><span class="o">.</span><span class="n">max_num_tokens</span> <span class="o">=</span> <span class="mi">2048</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">GpuArch</span><span class="o">.</span><span class="n">is_post_ampere</span><span class="p">():</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_config_arbitrator</span><span class="o">.</span><span class="n">setup</span><span class="p">(</span><span class="s2">&quot;pre-ampere not supported&quot;</span><span class="p">,</span>
<span class="n">config_name</span><span class="o">=</span><span class="s2">&quot;plugin_config&quot;</span><span class="p">,</span>
<span class="n">use_paged_context_fmha</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_setup_enable_chunked_context</span><span class="p">()</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_setup_enable_streaming_llm</span><span class="p">()</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_setup_quant_config</span><span class="p">()</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">build_config</span><span class="o">.</span><span class="n">max_beam_width</span> <span class="o">&gt;</span> <span class="mi">1</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_config_arbitrator</span><span class="o">.</span><span class="n">claim_func</span><span class="p">(</span>
<span class="s2">&quot;beam_search (beam_width &gt; 1)&quot;</span><span class="p">,</span>
<span class="n">config_name</span><span class="o">=</span><span class="s2">&quot;kv_cache_config&quot;</span><span class="p">,</span>
<span class="n">enable_block_reuse</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_setup_build_config_into_config_arbitrator</span><span class="p">()</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_setup_kv_cache_config</span><span class="p">()</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_config_arbitrator</span><span class="p">(</span><span class="n">plugin_config</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">build_config</span><span class="o">.</span><span class="n">plugin_config</span><span class="p">,</span>
<span class="n">kv_cache_config</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">kv_cache_config</span><span class="p">,</span>
<span class="n">build_config</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">build_config</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_config_arbitrator</span> <span class="o">=</span> <span class="kc">None</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">build_config_mutable</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">bool</span><span class="p">:</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">model_format</span> <span class="ow">is</span> <span class="ow">not</span> <span class="n">_ModelFormatKind</span><span class="o">.</span><span class="n">TLLM_ENGINE</span>
<span class="k">def</span> <span class="nf">_update_plugin_config</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">key</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">value</span><span class="p">:</span> <span class="n">Any</span><span class="p">):</span>
<span class="nb">setattr</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">build_config</span><span class="o">.</span><span class="n">plugin_config</span><span class="p">,</span> <span class="n">key</span><span class="p">,</span> <span class="n">value</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">_load_config_from_engine</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">engine_dir</span><span class="p">:</span> <span class="n">Path</span><span class="p">):</span>
<span class="n">engine_config</span> <span class="o">=</span> <span class="n">EngineConfig</span><span class="o">.</span><span class="n">from_json_file</span><span class="p">(</span><span class="n">engine_dir</span> <span class="o">/</span> <span class="s2">&quot;config.json&quot;</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_pretrained_config</span> <span class="o">=</span> <span class="n">engine_config</span><span class="o">.</span><span class="n">pretrained_config</span>
<span class="bp">self</span><span class="o">.</span><span class="n">build_config</span> <span class="o">=</span> <span class="n">engine_config</span><span class="o">.</span><span class="n">build_config</span>
<span class="c1"># load and check parallel_config</span>
<span class="n">mapping</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_pretrained_config</span><span class="o">.</span><span class="n">mapping</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">parallel_config</span><span class="o">.</span><span class="n">tp_size</span> <span class="ow">not</span> <span class="ow">in</span> <span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">mapping</span><span class="o">.</span><span class="n">tp_size</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
<span class="sa">f</span><span class="s2">&quot;tp_size </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">parallel_config</span><span class="o">.</span><span class="n">tp_size</span><span class="si">}</span><span class="s2"> is not consistent with the engine&#39;s tp_size </span><span class="si">{</span><span class="n">mapping</span><span class="o">.</span><span class="n">tp_size</span><span class="si">}</span><span class="s2">&quot;</span>
<span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">parallel_config</span><span class="o">.</span><span class="n">pp_size</span> <span class="ow">not</span> <span class="ow">in</span> <span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">mapping</span><span class="o">.</span><span class="n">pp_size</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
<span class="sa">f</span><span class="s2">&quot;pp_size </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">parallel_config</span><span class="o">.</span><span class="n">pp_size</span><span class="si">}</span><span class="s2"> is not consistent with the engine&#39;s pp_size </span><span class="si">{</span><span class="n">mapping</span><span class="o">.</span><span class="n">pp_size</span><span class="si">}</span><span class="s2">&quot;</span>
<span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">parallel_config</span><span class="o">.</span><span class="n">cp_size</span> <span class="ow">not</span> <span class="ow">in</span> <span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">mapping</span><span class="o">.</span><span class="n">cp_size</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
<span class="sa">f</span><span class="s2">&quot;cp_size </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">parallel_config</span><span class="o">.</span><span class="n">cp_size</span><span class="si">}</span><span class="s2"> is not consistent with the engine&#39;s cp_size </span><span class="si">{</span><span class="n">mapping</span><span class="o">.</span><span class="n">cp_size</span><span class="si">}</span><span class="s2">&quot;</span>
<span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">parallel_config</span> <span class="o">=</span> <span class="n">_ParallelConfig</span><span class="p">(</span><span class="n">tp_size</span><span class="o">=</span><span class="n">mapping</span><span class="o">.</span><span class="n">tp_size</span><span class="p">,</span>
<span class="n">pp_size</span><span class="o">=</span><span class="n">mapping</span><span class="o">.</span><span class="n">pp_size</span><span class="p">,</span>
<span class="n">cp_size</span><span class="o">=</span><span class="n">mapping</span><span class="o">.</span><span class="n">cp_size</span><span class="p">,</span>
<span class="n">moe_tp_size</span><span class="o">=</span><span class="n">mapping</span><span class="o">.</span><span class="n">moe_tp_size</span><span class="p">,</span>
<span class="n">moe_ep_size</span><span class="o">=</span><span class="n">mapping</span><span class="o">.</span><span class="n">moe_ep_size</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">_load_config_from_ckpt</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ckpt_dir</span><span class="p">:</span> <span class="n">Path</span><span class="p">):</span>
<span class="n">pretrained_config</span> <span class="o">=</span> <span class="n">PretrainedConfig</span><span class="o">.</span><span class="n">from_json_file</span><span class="p">(</span><span class="n">ckpt_dir</span> <span class="o">/</span>
<span class="s2">&quot;config.json&quot;</span><span class="p">)</span>
<span class="n">tp_size</span> <span class="o">=</span> <span class="n">pretrained_config</span><span class="o">.</span><span class="n">mapping</span><span class="o">.</span><span class="n">tp_size</span>
<span class="n">pp_size</span> <span class="o">=</span> <span class="n">pretrained_config</span><span class="o">.</span><span class="n">mapping</span><span class="o">.</span><span class="n">pp_size</span>
<span class="n">cp_size</span> <span class="o">=</span> <span class="n">pretrained_config</span><span class="o">.</span><span class="n">mapping</span><span class="o">.</span><span class="n">cp_size</span>
<span class="n">moe_tp_size</span> <span class="o">=</span> <span class="n">pretrained_config</span><span class="o">.</span><span class="n">mapping</span><span class="o">.</span><span class="n">moe_tp_size</span>
<span class="n">moe_ep_size</span> <span class="o">=</span> <span class="n">pretrained_config</span><span class="o">.</span><span class="n">mapping</span><span class="o">.</span><span class="n">moe_ep_size</span>
<span class="n">world_size</span> <span class="o">=</span> <span class="n">pretrained_config</span><span class="o">.</span><span class="n">mapping</span><span class="o">.</span><span class="n">world_size</span>
<span class="c1"># load parallel_config</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">parallel_config</span><span class="o">.</span><span class="n">tp_size</span> <span class="o">!=</span> <span class="mi">1</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">parallel_config</span><span class="o">.</span><span class="n">tp_size</span> <span class="o">!=</span> <span class="n">tp_size</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
<span class="sa">f</span><span class="s2">&quot;tp_size </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">parallel_config</span><span class="o">.</span><span class="n">tp_size</span><span class="si">}</span><span class="s2"> is not consistent with the checkpoint&#39;s tp_size </span><span class="si">{</span><span class="n">tp_size</span><span class="si">}</span><span class="s2">&quot;</span>
<span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">parallel_config</span><span class="o">.</span><span class="n">pp_size</span> <span class="o">!=</span> <span class="mi">1</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">parallel_config</span><span class="o">.</span><span class="n">pp_size</span> <span class="o">!=</span> <span class="n">pp_size</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
<span class="sa">f</span><span class="s2">&quot;pp_size </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">parallel_config</span><span class="o">.</span><span class="n">pp_size</span><span class="si">}</span><span class="s2"> is not consistent with the checkpoint&#39;s pp_size </span><span class="si">{</span><span class="n">pp_size</span><span class="si">}</span><span class="s2">&quot;</span>
<span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">parallel_config</span><span class="o">.</span><span class="n">cp_size</span> <span class="o">!=</span> <span class="mi">1</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">parallel_config</span><span class="o">.</span><span class="n">cp_size</span> <span class="o">!=</span> <span class="n">cp_size</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
<span class="sa">f</span><span class="s2">&quot;cp_size </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">parallel_config</span><span class="o">.</span><span class="n">cp_size</span><span class="si">}</span><span class="s2"> is not consistent with the checkpoint&#39;s cp_size </span><span class="si">{</span><span class="n">cp_size</span><span class="si">}</span><span class="s2">&quot;</span>
<span class="p">)</span>
<span class="k">if</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">parallel_config</span><span class="o">.</span><span class="n">auto_parallel</span>
<span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">parallel_config</span><span class="o">.</span><span class="n">world_size</span> <span class="o">!=</span> <span class="mi">1</span> <span class="ow">and</span> <span class="n">world_size</span> <span class="o">!=</span> <span class="mi">1</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
<span class="sa">f</span><span class="s2">&quot;auto parallel with world_size </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">parallel_config</span><span class="o">.</span><span class="n">world_size</span><span class="si">}</span><span class="s2"> does not support checkpoint with &quot;</span>
<span class="s2">&quot;world_size </span><span class="si">{world_size}</span><span class="s2"> &gt; 1&quot;</span><span class="p">)</span>
<span class="k">if</span> <span class="ow">not</span> <span class="bp">self</span><span class="o">.</span><span class="n">parallel_config</span><span class="o">.</span><span class="n">auto_parallel</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">parallel_config</span> <span class="o">=</span> <span class="n">_ParallelConfig</span><span class="p">(</span><span class="n">tp_size</span><span class="o">=</span><span class="n">tp_size</span><span class="p">,</span>
<span class="n">pp_size</span><span class="o">=</span><span class="n">pp_size</span><span class="p">,</span>
<span class="n">cp_size</span><span class="o">=</span><span class="n">cp_size</span><span class="p">,</span>
<span class="n">moe_tp_size</span><span class="o">=</span><span class="n">moe_tp_size</span><span class="p">,</span>
<span class="n">moe_ep_size</span><span class="o">=</span><span class="n">moe_ep_size</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">_setup_embedding_parallel_mode</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">embedding_parallel_mode</span> <span class="o">==</span> <span class="s1">&#39;NONE&#39;</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_convert_checkpoint_options</span><span class="p">[</span><span class="s1">&#39;use_parallel_embedding&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="kc">False</span>
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">embedding_parallel_mode</span> <span class="o">==</span> <span class="s1">&#39;SHARDING_ALONG_VOCAB&#39;</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_convert_checkpoint_options</span><span class="p">[</span><span class="s1">&#39;use_parallel_embedding&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="kc">True</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_convert_checkpoint_options</span><span class="p">[</span><span class="s1">&#39;embedding_sharding_dim&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">embedding_parallel_mode</span> <span class="o">==</span> <span class="s1">&#39;SHARDING_ALONG_HIDDEN&#39;</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_convert_checkpoint_options</span><span class="p">[</span><span class="s1">&#39;use_parallel_embedding&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="kc">True</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_convert_checkpoint_options</span><span class="p">[</span><span class="s1">&#39;embedding_sharding_dim&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="mi">1</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
<span class="sa">f</span><span class="s2">&quot;Invalid embedding_parallel_mode: </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">embedding_parallel_mode</span><span class="si">}</span><span class="s2">&quot;</span>
<span class="p">)</span>
<span class="k">def</span> <span class="nf">_setup_build_config_into_config_arbitrator</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="c1"># Setup the ConfigArbitrator with the plugin_config, the runtime configs such as KvCacheConfig should not be</span>
<span class="c1"># conflict with it.</span>
<span class="n">build_config</span> <span class="o">=</span> <span class="n">asdict</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">build_config</span><span class="p">)</span>
<span class="k">del</span> <span class="n">build_config</span><span class="p">[</span><span class="s1">&#39;plugin_config&#39;</span><span class="p">]</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_config_arbitrator</span><span class="o">.</span><span class="n">setup</span><span class="p">(</span><span class="s2">&quot;BuildConfig is readonly&quot;</span><span class="p">,</span>
<span class="n">config_name</span><span class="o">=</span><span class="s2">&quot;build_config&quot;</span><span class="p">,</span>
<span class="o">**</span><span class="n">build_config</span><span class="p">)</span>
<span class="n">plugin_config</span> <span class="o">=</span> <span class="n">asdict</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">build_config</span><span class="o">.</span><span class="n">plugin_config</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_config_arbitrator</span><span class="o">.</span><span class="n">setup</span><span class="p">(</span><span class="s2">&quot;PluginConfig is readonly&quot;</span><span class="p">,</span>
<span class="n">config_name</span><span class="o">=</span><span class="s2">&quot;plugin_config&quot;</span><span class="p">,</span>
<span class="o">**</span><span class="n">plugin_config</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">_setup_enable_chunked_context</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">fallback</span><span class="p">():</span>
<span class="n">logger</span><span class="o">.</span><span class="n">warning</span><span class="p">(</span>
<span class="sa">f</span><span class="s2">&quot;Disabling chunked context due to configuration conflict.&quot;</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">enable_chunked_prefill</span> <span class="o">=</span> <span class="kc">False</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">enable_chunked_prefill</span><span class="p">:</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">build_config_mutable</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_config_arbitrator</span><span class="o">.</span><span class="n">claim_perf</span><span class="p">(</span><span class="s2">&quot;chunked_context&quot;</span><span class="p">,</span>
<span class="n">config_name</span><span class="o">=</span><span class="s2">&quot;plugin_config&quot;</span><span class="p">,</span>
<span class="n">use_paged_context_fmha</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
<span class="n">fallback</span><span class="o">=</span><span class="n">fallback</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">_setup_enable_streaming_llm</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">build_config</span><span class="o">.</span><span class="n">plugin_config</span><span class="o">.</span><span class="n">streamingllm</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_validate_kv_cache_config</span><span class="p">()</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_config_arbitrator</span><span class="o">.</span><span class="n">claim_func</span><span class="p">(</span><span class="s2">&quot;streamingllm&quot;</span><span class="p">,</span>
<span class="n">config_name</span><span class="o">=</span><span class="s2">&quot;plugin_config&quot;</span><span class="p">,</span>
<span class="n">streamingllm</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
<span class="n">use_paged_context_fmha</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_config_arbitrator</span><span class="o">.</span><span class="n">claim_func</span><span class="p">(</span><span class="s2">&quot;streamingllm&quot;</span><span class="p">,</span>
<span class="n">config_name</span><span class="o">=</span><span class="s2">&quot;kv_cache_config&quot;</span><span class="p">,</span>
<span class="n">enable_block_reuse</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">_validate_kv_cache_config</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">kv_cache_config</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">&quot;KvCacheConfig is required for streaming LLM.&quot;</span><span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">kv_cache_config</span><span class="o">.</span><span class="n">max_attention_window</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
<span class="s2">&quot;KvCacheConfig.max_attention_window should be set for streaming LLM.&quot;</span>
<span class="p">)</span>
<span class="k">if</span> <span class="nb">any</span><span class="p">(</span><span class="n">i</span> <span class="o">&lt;=</span> <span class="mi">0</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">kv_cache_config</span><span class="o">.</span><span class="n">max_attention_window</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
<span class="s2">&quot;Elements in KvCacheConfig.max_attention_window should be greater than 0.&quot;</span>
<span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">kv_cache_config</span><span class="o">.</span><span class="n">sink_token_length</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
<span class="s2">&quot;KvCacheConfig.sink_token_length should be set for streaming LLM.&quot;</span>
<span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">kv_cache_config</span><span class="o">.</span><span class="n">sink_token_length</span> <span class="o">&lt;=</span> <span class="mi">0</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
<span class="s2">&quot;KvCacheConfig.sink_token_length should be greater than 0.&quot;</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">_setup_kv_cache_config</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">assert</span> <span class="bp">self</span><span class="o">.</span><span class="n">kv_cache_config</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">GpuArch</span><span class="o">.</span><span class="n">is_post_ampere</span><span class="p">():</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_config_arbitrator</span><span class="o">.</span><span class="n">setup</span><span class="p">(</span><span class="s2">&quot;pre-ampere not supported&quot;</span><span class="p">,</span>
<span class="n">config_name</span><span class="o">=</span><span class="s2">&quot;kv_cache_config&quot;</span><span class="p">,</span>
<span class="n">enable_block_reuse</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">kv_cache_config</span><span class="o">.</span><span class="n">enable_block_reuse</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_config_arbitrator</span><span class="o">.</span><span class="n">claim_func</span><span class="p">(</span><span class="s2">&quot;enable_block_reuse&quot;</span><span class="p">,</span>
<span class="n">config_name</span><span class="o">=</span><span class="s2">&quot;kv_cache_config&quot;</span><span class="p">,</span>
<span class="n">enable_block_reuse</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_config_arbitrator</span><span class="o">.</span><span class="n">claim_func</span><span class="p">(</span><span class="s2">&quot;enable_block_reuse&quot;</span><span class="p">,</span>
<span class="n">config_name</span><span class="o">=</span><span class="s2">&quot;plugin_config&quot;</span><span class="p">,</span>
<span class="n">use_paged_context_fmha</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">_setup_quant_config</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">quant_config</span><span class="o">.</span><span class="n">quant_algo</span> <span class="ow">is</span> <span class="n">QuantAlgo</span><span class="o">.</span><span class="n">FP8</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_config_arbitrator</span><span class="o">.</span><span class="n">claim_func</span><span class="p">(</span><span class="s2">&quot;fp8_quant&quot;</span><span class="p">,</span>
<span class="n">config_name</span><span class="o">=</span><span class="s2">&quot;plugin_config&quot;</span><span class="p">,</span>
<span class="n">use_paged_context_fmha</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">__setstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">state</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="vm">__dict__</span><span class="o">.</span><span class="n">update</span><span class="p">(</span><span class="n">state</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">__getstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="n">state</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="vm">__dict__</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
<span class="k">if</span> <span class="s1">&#39;_config_arbitrator&#39;</span> <span class="ow">in</span> <span class="n">state</span><span class="p">:</span>
<span class="k">del</span> <span class="n">state</span><span class="p">[</span><span class="s1">&#39;_config_arbitrator&#39;</span><span class="p">]</span>
<span class="k">return</span> <span class="n">state</span>
<span class="k">class</span> <span class="nc">ConfigArbitrateError</span><span class="p">(</span><span class="ne">Exception</span><span class="p">):</span>
<span class="w"> </span><span class="sd">&#39;&#39;&#39; Exception raised when there is a conflict in configurations. &#39;&#39;&#39;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">message</span><span class="p">):</span>
<span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">message</span><span class="p">)</span>
<span class="k">class</span> <span class="nc">_ConfigArbitrator</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&#39;&#39;&#39; The ConfigArbitrator will arbitrate the options from different sources and raise errors if there are conflicts. &#39;&#39;&#39;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="c1"># Dict of configs, the format is {config_name: {option: value}}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">virtual_configs</span><span class="p">:</span> <span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]]</span> <span class="o">=</span> <span class="p">{}</span>
<span class="c1"># The claims for functionalities, the format is {config_name: [(func_name, {option: value})]}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">func_claims</span><span class="p">:</span> <span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">List</span><span class="p">[</span><span class="n">Tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">dict</span><span class="p">]]]</span> <span class="o">=</span> <span class="p">{}</span>
<span class="c1"># The claims for performances, the format is {perf_name: [(config_name, {option: value}, fallback)]},</span>
<span class="c1"># the fallback is a callback function to be called when the performance is abandoned.</span>
<span class="bp">self</span><span class="o">.</span><span class="n">perf_claims</span><span class="p">:</span> <span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">List</span><span class="p">[</span><span class="n">Tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">dict</span><span class="p">,</span>
<span class="n">Optional</span><span class="p">[</span><span class="n">Callable</span><span class="p">[[],</span>
<span class="kc">None</span><span class="p">]]]]]</span> <span class="o">=</span> <span class="p">{}</span>
<span class="c1"># Track where the option settings came from, this will be used for messages when encountered conflicts.</span>
<span class="c1"># The format is {config_name: {option: error_information}}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">option_sources</span><span class="p">:</span> <span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">str</span><span class="p">]]</span> <span class="o">=</span> <span class="p">{}</span>
<span class="k">def</span> <span class="fm">__call__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">configs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&#39;&#39;&#39;</span>
<span class="sd"> Args:</span>
<span class="sd"> configs: name to config instance for each config need to be arbitrated.</span>
<span class="sd"> &#39;&#39;&#39;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_arbitrate</span><span class="p">()</span>
<span class="c1"># Apply the successfully arbitrated virtual configs to the real configs</span>
<span class="k">for</span> <span class="n">name</span><span class="p">,</span> <span class="n">config</span> <span class="ow">in</span> <span class="n">configs</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
<span class="k">if</span> <span class="n">name</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">virtual_configs</span><span class="p">:</span>
<span class="n">virtual_config</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">virtual_configs</span><span class="p">[</span><span class="n">name</span><span class="p">]</span>
<span class="k">for</span> <span class="n">option</span><span class="p">,</span> <span class="n">value</span> <span class="ow">in</span> <span class="n">virtual_config</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
<span class="nb">setattr</span><span class="p">(</span><span class="n">config</span><span class="p">,</span> <span class="n">option</span><span class="p">,</span> <span class="n">value</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">setup</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">info</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">config_name</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="w"> </span><span class="sd">&#39;&#39;&#39; Setup with some pre-defined configs comes from environment such as GPU arch. &#39;&#39;&#39;</span>
<span class="n">config</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">virtual_configs</span><span class="o">.</span><span class="n">setdefault</span><span class="p">(</span><span class="n">config_name</span><span class="p">,</span> <span class="p">{})</span>
<span class="n">option_sources</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">option_sources</span><span class="o">.</span><span class="n">setdefault</span><span class="p">(</span><span class="n">config_name</span><span class="p">,</span> <span class="p">{})</span>
<span class="k">for</span> <span class="n">option</span><span class="p">,</span> <span class="n">value</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
<span class="k">assert</span> <span class="n">config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">option</span><span class="p">,</span> <span class="n">value</span><span class="p">)</span> <span class="o">==</span> <span class="n">value</span>
<span class="n">config</span><span class="p">[</span><span class="n">option</span><span class="p">]</span> <span class="o">=</span> <span class="n">value</span>
<span class="n">option_sources</span><span class="p">[</span><span class="n">option</span><span class="p">]</span> <span class="o">=</span> <span class="n">info</span>
<span class="k">def</span> <span class="nf">claim_func</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">func</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">config_name</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="o">**</span><span class="n">options</span><span class="p">):</span>
<span class="w"> </span><span class="sd">&#39;&#39;&#39; Claim a functionality demanding with configs and options.</span>
<span class="sd"> The functionality should be fulfilled, or errors will be raised. &#39;&#39;&#39;</span>
<span class="n">claims</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">func_claims</span><span class="o">.</span><span class="n">setdefault</span><span class="p">(</span><span class="n">config_name</span><span class="p">,</span> <span class="p">[])</span>
<span class="n">claims</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">func</span><span class="p">,</span> <span class="n">options</span><span class="p">))</span>
<span class="k">def</span> <span class="nf">claim_perf</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span>
<span class="n">perf</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span>
<span class="n">config_name</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span>
<span class="n">fallback</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Callable</span><span class="p">[[],</span> <span class="kc">None</span><span class="p">]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
<span class="o">**</span><span class="n">options</span><span class="p">):</span>
<span class="w"> </span><span class="sd">&#39;&#39;&#39; Claim a performance demanding for configs and options.</span>
<span class="sd"> The performance could be abandoned if the demanding is not available.&#39;&#39;&#39;</span>
<span class="n">claims</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">perf_claims</span><span class="o">.</span><span class="n">setdefault</span><span class="p">(</span><span class="n">perf</span><span class="p">,</span> <span class="p">[])</span>
<span class="n">claims</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">config_name</span><span class="p">,</span> <span class="n">options</span><span class="p">,</span> <span class="n">fallback</span><span class="p">))</span>
<span class="k">def</span> <span class="nf">_arbitrate</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="w"> </span><span class="sd">&#39;&#39;&#39; Arbitrate the configs for all the functionalities and performances. &#39;&#39;&#39;</span>
<span class="c1"># Resolve functionality claims</span>
<span class="k">for</span> <span class="n">config_name</span><span class="p">,</span> <span class="n">funcs</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">func_claims</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
<span class="n">virtual_config</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">virtual_configs</span><span class="o">.</span><span class="n">setdefault</span><span class="p">(</span><span class="n">config_name</span><span class="p">,</span> <span class="p">{})</span>
<span class="n">option_sources</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">option_sources</span><span class="o">.</span><span class="n">setdefault</span><span class="p">(</span><span class="n">config_name</span><span class="p">,</span> <span class="p">{})</span>
<span class="k">for</span> <span class="n">func</span><span class="p">,</span> <span class="n">options</span> <span class="ow">in</span> <span class="n">funcs</span><span class="p">:</span>
<span class="k">for</span> <span class="n">option</span><span class="p">,</span> <span class="n">value</span> <span class="ow">in</span> <span class="n">options</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
<span class="k">if</span> <span class="n">option</span> <span class="ow">in</span> <span class="n">virtual_config</span><span class="p">:</span>
<span class="k">if</span> <span class="n">virtual_config</span><span class="p">[</span><span class="n">option</span><span class="p">]</span> <span class="o">!=</span> <span class="n">value</span><span class="p">:</span>
<span class="n">existing_func</span> <span class="o">=</span> <span class="n">option_sources</span><span class="p">[</span><span class="n">option</span><span class="p">]</span>
<span class="k">raise</span> <span class="n">ConfigArbitrateError</span><span class="p">(</span>
<span class="sa">f</span><span class="s2">&quot;Cannot set &#39;</span><span class="si">{</span><span class="n">option</span><span class="si">}</span><span class="s2">&#39; to be &#39;</span><span class="si">{</span><span class="n">value</span><span class="si">}</span><span class="s2">&#39; when enabling &#39;</span><span class="si">{</span><span class="n">func</span><span class="si">}</span><span class="s2">&#39;, &quot;</span>
<span class="sa">f</span><span class="s2">&quot;since &#39;</span><span class="si">{</span><span class="n">existing_func</span><span class="si">}</span><span class="s2">&#39; has set it to be &#39;</span><span class="si">{</span><span class="n">virtual_config</span><span class="p">[</span><span class="n">option</span><span class="p">]</span><span class="si">}</span><span class="s2">&#39;.&quot;</span>
<span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">virtual_config</span><span class="p">[</span><span class="n">option</span><span class="p">]</span> <span class="o">=</span> <span class="n">value</span>
<span class="c1"># Track where the setting came from</span>
<span class="n">option_sources</span><span class="p">[</span><span class="n">option</span><span class="p">]</span> <span class="o">=</span> <span class="n">func</span>
<span class="c1"># copy for restore</span>
<span class="c1"># Resolve performance claims</span>
<span class="k">for</span> <span class="n">perf</span><span class="p">,</span> <span class="n">options</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">perf_claims</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
<span class="n">option_sources</span> <span class="o">=</span> <span class="n">copy</span><span class="o">.</span><span class="n">copy</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">option_sources</span><span class="p">)</span>
<span class="n">virtual_configs</span> <span class="o">=</span> <span class="n">copy</span><span class="o">.</span><span class="n">copy</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">virtual_configs</span><span class="p">)</span>
<span class="n">restore</span> <span class="o">=</span> <span class="kc">False</span>
<span class="k">for</span> <span class="n">config_name</span><span class="p">,</span> <span class="n">options</span><span class="p">,</span> <span class="n">fallback</span> <span class="ow">in</span> <span class="n">options</span><span class="p">:</span>
<span class="n">virtual_config</span> <span class="o">=</span> <span class="n">virtual_configs</span><span class="o">.</span><span class="n">setdefault</span><span class="p">(</span><span class="n">config_name</span><span class="p">,</span> <span class="p">{})</span>
<span class="n">option_source</span> <span class="o">=</span> <span class="n">option_sources</span><span class="o">.</span><span class="n">setdefault</span><span class="p">(</span><span class="n">config_name</span><span class="p">,</span> <span class="p">{})</span>
<span class="k">for</span> <span class="n">option</span><span class="p">,</span> <span class="n">value</span> <span class="ow">in</span> <span class="n">options</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
<span class="k">if</span> <span class="n">option</span> <span class="ow">in</span> <span class="n">virtual_config</span> <span class="ow">and</span> <span class="n">virtual_config</span><span class="p">[</span>
<span class="n">option</span><span class="p">]</span> <span class="o">!=</span> <span class="n">value</span><span class="p">:</span>
<span class="n">logger</span><span class="o">.</span><span class="n">warning</span><span class="p">(</span>
<span class="sa">f</span><span class="s2">&quot;Ignoring performance claim &#39;</span><span class="si">{</span><span class="n">perf</span><span class="si">}</span><span class="s2">&#39; for option &#39;</span><span class="si">{</span><span class="n">option</span><span class="si">}</span><span class="s2">&#39; due to conflict.&quot;</span>
<span class="p">)</span>
<span class="n">restore</span> <span class="o">=</span> <span class="kc">True</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">virtual_config</span><span class="p">[</span><span class="n">option</span><span class="p">]</span> <span class="o">=</span> <span class="n">value</span>
<span class="n">option_source</span><span class="p">[</span><span class="n">option</span><span class="p">]</span> <span class="o">=</span> <span class="n">perf</span>
<span class="k">if</span> <span class="n">restore</span><span class="p">:</span> <span class="k">break</span>
<span class="k">if</span> <span class="n">restore</span><span class="p">:</span>
<span class="k">if</span> <span class="n">fallback</span><span class="p">:</span> <span class="n">fallback</span><span class="p">()</span>
<span class="k">break</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">restore</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">option_sources</span> <span class="o">=</span> <span class="n">option_sources</span>
<span class="bp">self</span><span class="o">.</span><span class="n">virtual_configs</span> <span class="o">=</span> <span class="n">virtual_configs</span>
<span class="nd">@dataclass</span>
<span class="k">class</span> <span class="nc">_ModelRuntimeContext</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&#39;&#39;&#39; _ModelRuntimeContext holds the minimum runtime resources for running a model.</span>
<span class="sd"> It could be a runtime cache in MPI nodes.</span>
<span class="sd"> &#39;&#39;&#39;</span>
<span class="n">engine</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Engine</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">mapping</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Mapping</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">model_info</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">_ModelInfo</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="c1"># This is only used when build-cache is enabled</span>
<span class="n">engine_path</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">model_arch</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">str</span><span class="p">:</span>
<span class="c1"># &quot;LlaMACausalForLM&quot; or &quot;OPTForCausalLM&quot; and so on</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">engine</span><span class="o">.</span><span class="n">config</span><span class="o">.</span><span class="n">pretrained_config</span><span class="p">[</span><span class="s1">&#39;architecture&#39;</span><span class="p">]</span>
<span class="k">class</span> <span class="nc">ModelLoader</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&#39;&#39;&#39; The ModelLoader is used to build an end-to-end model for a single-gpu.</span>
<span class="sd"> It accepts model name or a local model dir, and will download the model if necessary.</span>
<span class="sd"> &#39;&#39;&#39;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span>
<span class="n">llm_args</span><span class="p">:</span> <span class="n">LlmArgs</span><span class="p">,</span>
<span class="n">workspace</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">str</span> <span class="o">|</span> <span class="n">tempfile</span><span class="o">.</span><span class="n">TemporaryDirectory</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
<span class="n">llm_build_stats</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="s2">&quot;LlmBuildStats&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span> <span class="o">=</span> <span class="n">llm_args</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_workspace</span> <span class="o">=</span> <span class="n">workspace</span> <span class="ow">or</span> <span class="n">tempfile</span><span class="o">.</span><span class="n">TemporaryDirectory</span><span class="p">()</span>
<span class="bp">self</span><span class="o">.</span><span class="n">llm_build_stats</span> <span class="o">=</span> <span class="n">llm_build_stats</span> <span class="ow">or</span> <span class="n">LlmBuildStats</span><span class="p">()</span>
<span class="k">assert</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">build_config</span>
<span class="bp">self</span><span class="o">.</span><span class="n">build_config</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">build_config</span>
<span class="bp">self</span><span class="o">.</span><span class="n">model_obj</span> <span class="o">=</span> <span class="n">_ModelWrapper</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">model</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">speculative_model_obj</span> <span class="o">=</span> <span class="n">_ModelWrapper</span><span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">speculative_model</span>
<span class="p">)</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">speculative_model</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="k">else</span> <span class="kc">None</span>
<span class="bp">self</span><span class="o">.</span><span class="n">convert_checkpoint_options</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">_convert_checkpoint_options</span>
<span class="bp">self</span><span class="o">.</span><span class="n">rank</span> <span class="o">=</span> <span class="n">mpi_rank</span><span class="p">()</span>
<span class="bp">self</span><span class="o">.</span><span class="n">mapping</span> <span class="o">=</span> <span class="n">llm_args</span><span class="o">.</span><span class="n">parallel_config</span><span class="o">.</span><span class="n">to_mapping</span><span class="p">()</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_build_pipeline</span> <span class="o">=</span> <span class="p">[]</span>
<span class="c1"># For model from hub, the _model_dir is None, and will updated once downloaded</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_model_dir</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span>
<span class="n">Path</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">model_obj</span><span class="o">.</span><span class="n">model_dir</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">model_obj</span><span class="o">.</span><span class="n">is_local_model</span> <span class="k">else</span> <span class="kc">None</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_speculative_model_dir</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span>
<span class="n">Path</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">speculative_model_obj</span><span class="o">.</span><span class="n">model_dir</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">speculative_model_obj</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">model_obj</span><span class="o">.</span><span class="n">is_local_model</span> <span class="k">else</span> <span class="kc">None</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_model_info</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">_ModelInfo</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_model_format</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">model_format</span>
<span class="bp">self</span><span class="o">.</span><span class="n">auto_parallel_config</span> <span class="o">=</span> <span class="n">AutoParallelConfig</span><span class="p">(</span>
<span class="n">world_size</span><span class="o">=</span><span class="n">llm_args</span><span class="o">.</span><span class="n">parallel_config</span><span class="o">.</span><span class="n">world_size</span> <span class="k">if</span> <span class="n">llm_args</span><span class="o">.</span>
<span class="n">parallel_config</span><span class="o">.</span><span class="n">auto_parallel</span> <span class="k">else</span> <span class="mi">1</span><span class="p">)</span>
<span class="n">default_config</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">auto_parallel_config</span>
<span class="bp">self</span><span class="o">.</span><span class="n">auto_parallel_config</span><span class="o">.</span><span class="n">set_defaults</span><span class="p">(</span>
<span class="n">cluster_key</span><span class="o">=</span><span class="n">default_config</span><span class="o">.</span><span class="n">cluster_key</span><span class="p">,</span>
<span class="n">cluster_info</span><span class="o">=</span><span class="n">default_config</span><span class="o">.</span><span class="n">cluster_info</span><span class="p">,</span>
<span class="n">same_buffer_io</span><span class="o">=</span><span class="n">default_config</span><span class="o">.</span><span class="n">same_buffer_io</span><span class="p">,</span>
<span class="n">sharded_io_allowlist</span><span class="o">=</span><span class="n">default_config</span><span class="o">.</span><span class="n">sharded_io_allowlist</span><span class="p">,</span>
<span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_gather_build_steps</span><span class="p">()</span>
<span class="k">def</span> <span class="nf">_gather_build_steps</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="c1"># Prepare the model processing pipeline</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">model</span><span class="p">,</span> <span class="n">Module</span><span class="p">):</span>
<span class="c1"># Build engine from user provided model</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_build_pipeline</span><span class="o">.</span><span class="n">append</span><span class="p">(</span>
<span class="p">(</span><span class="s2">&quot;Build TensorRT-LLM engine&quot;</span><span class="p">,</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_build_engine_from_inmemory_model</span><span class="p">))</span>
<span class="k">return</span>
<span class="k">if</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">model_obj</span><span class="o">.</span><span class="n">is_hub_model</span>
<span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">_model_format</span> <span class="ow">is</span> <span class="ow">not</span> <span class="n">_ModelFormatKind</span><span class="o">.</span><span class="n">TLLM_ENGINE</span><span class="p">)</span> <span class="ow">or</span> <span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">speculative_model_obj</span>
<span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">speculative_model_obj</span><span class="o">.</span><span class="n">is_hub_model</span><span class="p">):</span>
<span class="c1"># Download HF model if necessary</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">model_obj</span><span class="o">.</span><span class="n">model_name</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
<span class="s2">&quot;Either model_dir or model should be provided to ModelConfig.&quot;</span>
<span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_build_pipeline</span><span class="o">.</span><span class="n">append</span><span class="p">(</span>
<span class="p">(</span><span class="s2">&quot;Downloading HF model&quot;</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_download_hf_model</span><span class="p">))</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_model_format</span> <span class="ow">is</span> <span class="n">_ModelFormatKind</span><span class="o">.</span><span class="n">HF</span><span class="p">:</span>
<span class="c1"># HF -&gt; TRT checkpoints -&gt; engine</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_build_pipeline</span><span class="o">.</span><span class="n">append</span><span class="p">(</span>
<span class="p">(</span><span class="s2">&quot;Loading HF model to memory&quot;</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_load_model_from_hf</span><span class="p">))</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_build_pipeline</span><span class="o">.</span><span class="n">append</span><span class="p">(</span>
<span class="p">(</span><span class="s2">&quot;Building TRT-LLM engine&quot;</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_build_engine</span><span class="p">))</span>
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">_model_format</span> <span class="ow">is</span> <span class="n">_ModelFormatKind</span><span class="o">.</span><span class="n">TLLM_CKPT</span><span class="p">:</span>
<span class="c1"># TRT checkpoints -&gt; engine</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_build_pipeline</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="s2">&quot;Loading TRT checkpoints to memory&quot;</span><span class="p">,</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_load_model_from_ckpt</span><span class="p">))</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_build_pipeline</span><span class="o">.</span><span class="n">append</span><span class="p">(</span>
<span class="p">(</span><span class="s2">&quot;Build TRT-LLM engine&quot;</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_build_engine</span><span class="p">))</span>
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">_model_format</span> <span class="ow">is</span> <span class="n">_ModelFormatKind</span><span class="o">.</span><span class="n">TLLM_ENGINE</span><span class="p">:</span>
<span class="c1"># Nothing need to do</span>
<span class="k">pass</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Unknown model format </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">_model_format</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
<span class="k">class</span> <span class="nc">BuildPipeline</span><span class="p">:</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">enable_tqdm</span><span class="p">:</span> <span class="nb">bool</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="nb">str</span><span class="p">],</span>
<span class="n">step_handlers</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="n">Callable</span><span class="p">],</span>
<span class="n">llm_build_stats</span><span class="p">:</span> <span class="s2">&quot;LlmBuildStats&quot;</span><span class="p">):</span>
<span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">labels</span><span class="p">)</span> <span class="o">==</span> <span class="nb">len</span><span class="p">(</span><span class="n">step_handlers</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">labels</span> <span class="o">=</span> <span class="n">labels</span>
<span class="bp">self</span><span class="o">.</span><span class="n">step_handlers</span> <span class="o">=</span> <span class="n">step_handlers</span>
<span class="bp">self</span><span class="o">.</span><span class="n">llm_build_stats</span> <span class="o">=</span> <span class="n">llm_build_stats</span>
<span class="bp">self</span><span class="o">.</span><span class="n">to_log</span> <span class="o">=</span> <span class="n">mpi_rank</span><span class="p">()</span> <span class="o">==</span> <span class="mi">0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">counter</span> <span class="o">=</span> <span class="mi">0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">progress_bar</span> <span class="o">=</span> <span class="n">tqdm</span><span class="p">(</span>
<span class="n">total</span><span class="o">=</span><span class="nb">len</span><span class="p">(</span><span class="n">labels</span><span class="p">))</span> <span class="k">if</span> <span class="n">enable_tqdm</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">to_log</span> <span class="k">else</span> <span class="kc">None</span>
<span class="k">def</span> <span class="fm">__call__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="n">start_time</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">labels</span><span class="p">)):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">step_forward</span><span class="p">()</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">to_log</span><span class="p">:</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">progress_bar</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">progress_bar</span><span class="o">.</span><span class="n">close</span><span class="p">()</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">overall_latency</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span> <span class="o">-</span> <span class="n">start_time</span>
<span class="n">print_colored</span><span class="p">(</span><span class="s2">&quot;Loading model done.</span><span class="se">\n</span><span class="s2">&quot;</span><span class="p">,</span> <span class="s1">&#39;bold_green&#39;</span><span class="p">)</span>
<span class="n">print_colored</span><span class="p">(</span>
<span class="s1">&#39;Total latency: </span><span class="si">{:.3f}</span><span class="s1">s</span><span class="se">\n</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">overall_latency</span><span class="p">),</span>
<span class="s1">&#39;grey&#39;</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">step_forward</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="n">n_steps</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">labels</span><span class="p">)</span>
<span class="n">label</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">labels</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">counter</span><span class="p">]</span>
<span class="c1"># display step information</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">to_log</span><span class="p">:</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">progress_bar</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">progress_bar</span><span class="o">.</span><span class="n">set_description</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">labels</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">counter</span><span class="p">])</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">print_colored</span><span class="p">(</span><span class="s2">&quot;Loading Model: &quot;</span><span class="p">)</span>
<span class="n">print_colored</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;[</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">counter</span><span class="o">+</span><span class="mi">1</span><span class="si">}</span><span class="s2">/</span><span class="si">{</span><span class="n">n_steps</span><span class="si">}</span><span class="s2">]</span><span class="se">\t</span><span class="s2">&quot;</span><span class="p">,</span>
<span class="s1">&#39;bold_green&#39;</span><span class="p">)</span>
<span class="n">print_colored</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">label</span><span class="si">}</span><span class="se">\n</span><span class="s2">&quot;</span><span class="p">)</span>
<span class="c1"># execute the step</span>
<span class="n">start_time</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span>
<span class="bp">self</span><span class="o">.</span><span class="n">step_handlers</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">counter</span><span class="p">]()</span>
<span class="c1"># release resource after each step</span>
<span class="n">release_gc</span><span class="p">()</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">progress_bar</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">progress_bar</span><span class="o">.</span><span class="n">update</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
<span class="n">latency</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span> <span class="o">-</span> <span class="n">start_time</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">to_log</span> <span class="ow">and</span> <span class="ow">not</span> <span class="bp">self</span><span class="o">.</span><span class="n">progress_bar</span><span class="p">:</span>
<span class="n">print_colored</span><span class="p">(</span><span class="s2">&quot;Time: </span><span class="si">{:.3f}</span><span class="s2">s</span><span class="se">\n</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">latency</span><span class="p">),</span> <span class="s1">&#39;grey&#39;</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">llm_build_stats</span><span class="o">.</span><span class="n">build_steps_info</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">label</span><span class="p">,</span> <span class="n">latency</span><span class="p">))</span>
<span class="bp">self</span><span class="o">.</span><span class="n">counter</span> <span class="o">+=</span> <span class="mi">1</span>
<span class="k">def</span> <span class="fm">__call__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">engine_dir</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Path</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Path</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&#39;&#39;&#39;</span>
<span class="sd"> The engine_dir is the path to save the built engine.</span>
<span class="sd"> &#39;&#39;&#39;</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">model_format</span> <span class="ow">is</span> <span class="n">_ModelFormatKind</span><span class="o">.</span><span class="n">TLLM_ENGINE</span><span class="p">:</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">model_obj</span><span class="o">.</span><span class="n">model_dir</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">parallel_config</span><span class="o">.</span><span class="n">is_multi_gpu</span><span class="p">:</span>
<span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">set_device</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">rank</span><span class="p">)</span>
<span class="n">pipeline</span> <span class="o">=</span> <span class="n">ModelLoader</span><span class="o">.</span><span class="n">BuildPipeline</span><span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">enable_tqdm</span><span class="p">,</span>
<span class="p">[</span><span class="n">label</span> <span class="k">for</span> <span class="n">label</span><span class="p">,</span> <span class="n">_</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">_build_pipeline</span><span class="p">],</span>
<span class="p">[</span><span class="n">handler</span> <span class="k">for</span> <span class="n">_</span><span class="p">,</span> <span class="n">handler</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">_build_pipeline</span><span class="p">],</span>
<span class="n">llm_build_stats</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">llm_build_stats</span><span class="p">,</span>
<span class="p">)</span>
<span class="n">pipeline</span><span class="p">()</span>
<span class="k">assert</span> <span class="n">engine_dir</span>
<span class="n">runtime_context</span> <span class="o">=</span> <span class="n">_ModelRuntimeContext</span><span class="p">(</span>
<span class="n">engine</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">_engine</span><span class="p">,</span>
<span class="n">mapping</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">mapping</span><span class="p">,</span>
<span class="n">model_info</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">_model_info</span><span class="p">,</span>
<span class="p">)</span>
<span class="n">ModelLoader</span><span class="o">.</span><span class="n">save</span><span class="p">(</span><span class="n">runtime_context</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">model_obj</span><span class="o">.</span><span class="n">model_dir</span><span class="p">,</span> <span class="n">engine_dir</span><span class="p">)</span>
<span class="k">return</span> <span class="n">engine_dir</span>
<span class="k">def</span> <span class="fm">__enter__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span>
<span class="k">def</span> <span class="fm">__exit__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">exc_type</span><span class="p">,</span> <span class="n">exc_value</span><span class="p">,</span> <span class="n">traceback</span><span class="p">):</span>
<span class="k">for</span> <span class="n">attr_name</span> <span class="ow">in</span> <span class="nb">dir</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">callable</span><span class="p">(</span><span class="nb">getattr</span><span class="p">(</span>
<span class="bp">self</span><span class="p">,</span> <span class="n">attr_name</span><span class="p">))</span> <span class="ow">and</span> <span class="ow">not</span> <span class="n">attr_name</span><span class="o">.</span><span class="n">startswith</span><span class="p">(</span><span class="s2">&quot;__&quot;</span><span class="p">):</span>
<span class="k">if</span> <span class="n">attr_name</span> <span class="ow">not</span> <span class="ow">in</span> <span class="p">(</span><span class="s1">&#39;model_format&#39;</span><span class="p">,</span> <span class="s1">&#39;workspace&#39;</span><span class="p">):</span>
<span class="nb">setattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">attr_name</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
<span class="n">release_gc</span><span class="p">()</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">workspace</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">str</span><span class="p">:</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_workspace</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">model_format</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">_ModelFormatKind</span><span class="p">:</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_model_format</span>
<span class="nd">@staticmethod</span>
<span class="k">def</span> <span class="nf">save</span><span class="p">(</span>
<span class="n">model</span><span class="p">:</span> <span class="n">_ModelRuntimeContext</span><span class="p">,</span>
<span class="n">model_dir</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span>
<span class="n">engine_dir</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span>
<span class="p">):</span>
<span class="w"> </span><span class="sd">&#39;&#39;&#39; Save the built engine on a single GPU to the given path. &#39;&#39;&#39;</span>
<span class="n">mapping</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">mapping</span>
<span class="n">rank</span> <span class="o">=</span> <span class="n">mapping</span><span class="o">.</span><span class="n">rank</span>
<span class="k">def</span> <span class="nf">copy_hf_tokenizer_data_to_engine_dir</span><span class="p">():</span>
<span class="c1"># Copy the HF tokenizer stuff to the engine dir so that we can use the engine dir as a standalone model dir</span>
<span class="c1"># supports end-to-end task.</span>
<span class="c1"># This is only for HF model for now, not available for users&#39; customized tokenizers.</span>
<span class="kn">import</span> <span class="nn">shutil</span>
<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">os</span><span class="o">.</span><span class="n">listdir</span><span class="p">(</span><span class="n">model_dir</span><span class="p">):</span>
<span class="n">src</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">model_dir</span><span class="p">,</span> <span class="n">name</span><span class="p">)</span>
<span class="n">dst</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">engine_dir</span><span class="p">,</span> <span class="n">name</span><span class="p">)</span>
<span class="k">if</span> <span class="n">name</span><span class="o">.</span><span class="n">startswith</span><span class="p">(</span><span class="s1">&#39;tokenizer&#39;</span><span class="p">):</span>
<span class="n">src</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">realpath</span><span class="p">(</span><span class="n">src</span><span class="p">)</span> <span class="k">if</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">islink</span><span class="p">(</span><span class="n">src</span><span class="p">)</span> <span class="k">else</span> <span class="n">src</span>
<span class="k">if</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">isdir</span><span class="p">(</span><span class="n">src</span><span class="p">):</span>
<span class="n">shutil</span><span class="o">.</span><span class="n">copytree</span><span class="p">(</span><span class="n">src</span><span class="p">,</span> <span class="n">dst</span><span class="p">,</span> <span class="n">dirs_exist_ok</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">shutil</span><span class="o">.</span><span class="n">copy2</span><span class="p">(</span><span class="n">src</span><span class="p">,</span> <span class="n">dst</span><span class="p">)</span>
<span class="n">model</span><span class="o">.</span><span class="n">engine</span><span class="o">.</span><span class="n">save</span><span class="p">(</span><span class="n">engine_dir</span><span class="p">)</span>
<span class="k">if</span> <span class="n">rank</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
<span class="n">copy_hf_tokenizer_data_to_engine_dir</span><span class="p">()</span>
<span class="nd">@staticmethod</span>
<span class="k">def</span> <span class="nf">get_model_format</span><span class="p">(</span><span class="n">model_dir</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">_ModelFormatKind</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&#39;&#39;&#39; Get the format of the model. &#39;&#39;&#39;</span>
<span class="k">if</span> <span class="ow">not</span> <span class="p">(</span><span class="n">Path</span><span class="p">(</span><span class="n">model_dir</span><span class="p">)</span> <span class="o">/</span> <span class="s1">&#39;config.json&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">exists</span><span class="p">():</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
<span class="sa">f</span><span class="s2">&quot;Failed to infer model format because no config.json exists in </span><span class="si">{</span><span class="n">model_dir</span><span class="si">}</span><span class="s2">&quot;</span>
<span class="p">)</span>
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">Path</span><span class="p">(</span><span class="n">model_dir</span><span class="p">)</span> <span class="o">/</span> <span class="s1">&#39;config.json&#39;</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
<span class="n">config</span> <span class="o">=</span> <span class="n">json</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">f</span><span class="p">)</span>
<span class="k">try</span><span class="p">:</span>
<span class="k">if</span> <span class="s1">&#39;pretrained_config&#39;</span> <span class="ow">in</span> <span class="n">config</span> <span class="ow">and</span> <span class="s1">&#39;build_config&#39;</span> <span class="ow">in</span> <span class="n">config</span><span class="p">:</span>
<span class="n">model_format</span> <span class="o">=</span> <span class="n">_ModelFormatKind</span><span class="o">.</span><span class="n">TLLM_ENGINE</span>
<span class="n">EngineConfig</span><span class="o">.</span><span class="n">from_json_file</span><span class="p">(</span><span class="n">Path</span><span class="p">(</span><span class="n">model_dir</span><span class="p">)</span> <span class="o">/</span> <span class="s1">&#39;config.json&#39;</span><span class="p">)</span>
<span class="k">elif</span> <span class="s1">&#39;architecture&#39;</span> <span class="ow">in</span> <span class="n">config</span> <span class="ow">and</span> <span class="s1">&#39;dtype&#39;</span> <span class="ow">in</span> <span class="n">config</span><span class="p">:</span>
<span class="n">model_format</span> <span class="o">=</span> <span class="n">_ModelFormatKind</span><span class="o">.</span><span class="n">TLLM_CKPT</span>
<span class="n">PretrainedConfig</span><span class="o">.</span><span class="n">from_checkpoint</span><span class="p">(</span><span class="n">model_dir</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">model_format</span> <span class="o">=</span> <span class="n">_ModelFormatKind</span><span class="o">.</span><span class="n">HF</span>
<span class="n">AutoConfig</span><span class="o">.</span><span class="n">from_hugging_face</span><span class="p">(</span><span class="n">model_dir</span><span class="p">)</span>
<span class="k">except</span> <span class="ne">Exception</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
<span class="sa">f</span><span class="s2">&quot;Inferred model format </span><span class="si">{</span><span class="n">model_format</span><span class="si">}</span><span class="s2">, but failed to load config.json: </span><span class="si">{</span><span class="n">e</span><span class="si">}</span><span class="s2">&quot;</span>
<span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">model_format</span>
<span class="k">def</span> <span class="nf">_download_hf_model</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="w"> </span><span class="sd">&#39;&#39;&#39; Download HF model from third-party model hub like www.modelscope.cn or huggingface. &#39;&#39;&#39;</span>
<span class="n">model_dir</span> <span class="o">=</span> <span class="kc">None</span>
<span class="c1"># Only the rank0 are allowed to download model</span>
<span class="k">if</span> <span class="n">mpi_rank</span><span class="p">()</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
<span class="k">assert</span> <span class="bp">self</span><span class="o">.</span><span class="n">_workspace</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span>
<span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">model_obj</span><span class="o">.</span><span class="n">model_name</span><span class="p">,</span> <span class="nb">str</span><span class="p">)</span>
<span class="c1"># this will download only once when multiple MPI processes are running</span>
<span class="n">model_dir</span> <span class="o">=</span> <span class="n">download_hf_model</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">model_obj</span><span class="o">.</span><span class="n">model_name</span><span class="p">,</span>
<span class="n">revision</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">revision</span><span class="p">)</span>
<span class="n">print_colored</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Downloaded model to </span><span class="si">{</span><span class="n">model_dir</span><span class="si">}</span><span class="se">\n</span><span class="s2">&quot;</span><span class="p">,</span> <span class="s1">&#39;grey&#39;</span><span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">speculative_model_obj</span><span class="p">:</span>
<span class="n">speculative_model_dir</span> <span class="o">=</span> <span class="n">download_hf_model</span><span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">speculative_model_obj</span><span class="o">.</span><span class="n">model_name</span><span class="p">)</span>
<span class="n">print_colored</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Downloaded model to </span><span class="si">{</span><span class="n">speculative_model_dir</span><span class="si">}</span><span class="se">\n</span><span class="s2">&quot;</span><span class="p">,</span>
<span class="s1">&#39;grey&#39;</span><span class="p">)</span>
<span class="c1"># Make all the processes got the same model_dir</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_model_dir</span> <span class="o">=</span> <span class="n">mpi_broadcast</span><span class="p">(</span><span class="n">model_dir</span><span class="p">,</span> <span class="n">root</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">model_obj</span><span class="o">.</span><span class="n">model_dir</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_model_dir</span> <span class="c1"># mark as a local model</span>
<span class="k">assert</span> <span class="bp">self</span><span class="o">.</span><span class="n">model_obj</span><span class="o">.</span><span class="n">is_local_model</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">speculative_model_obj</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_speculative_model_dir</span> <span class="o">=</span> <span class="n">mpi_broadcast</span><span class="p">(</span><span class="n">speculative_model_dir</span><span class="p">,</span>
<span class="n">root</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">speculative_model_obj</span><span class="o">.</span><span class="n">model_dir</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_speculative_model_dir</span>
<span class="k">assert</span> <span class="bp">self</span><span class="o">.</span><span class="n">speculative_model_obj</span><span class="o">.</span><span class="n">is_local_model</span>
<span class="k">def</span> <span class="nf">_load_model_from_hf</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="w"> </span><span class="sd">&#39;&#39;&#39; Load a TRT-LLM model from a HF model. &#39;&#39;&#39;</span>
<span class="k">assert</span> <span class="bp">self</span><span class="o">.</span><span class="n">_model_dir</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span>
<span class="n">model_cls</span> <span class="o">=</span> <span class="n">AutoModelForCausalLM</span><span class="o">.</span><span class="n">get_trtllm_model_class</span><span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_model_dir</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">trust_remote_code</span><span class="p">,</span>
<span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="p">,</span> <span class="s2">&quot;speculative_model&quot;</span><span class="p">)</span>
<span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">speculative_model</span><span class="p">)</span>
<span class="c1"># Update quant_config if it&#39;s ModelOpt quantized ckpt</span>
<span class="n">hf_quant_config_path</span> <span class="o">=</span> <span class="n">Path</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_model_dir</span><span class="p">)</span> <span class="o">/</span> <span class="s2">&quot;hf_quant_config.json&quot;</span>
<span class="k">if</span> <span class="n">hf_quant_config_path</span><span class="o">.</span><span class="n">exists</span><span class="p">():</span>
<span class="n">already_quantized</span> <span class="o">=</span> <span class="kc">True</span>
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">hf_quant_config_path</span><span class="p">,</span> <span class="s2">&quot;r&quot;</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
<span class="n">hf_quant_config</span> <span class="o">=</span> <span class="n">json</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">f</span><span class="p">)</span>
<span class="k">for</span> <span class="n">key</span><span class="p">,</span> <span class="n">value</span> <span class="ow">in</span> <span class="n">hf_quant_config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;quantization&quot;</span><span class="p">,</span>
<span class="p">{})</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
<span class="k">if</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">quant_config</span><span class="p">,</span> <span class="n">key</span><span class="p">):</span>
<span class="nb">setattr</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">quant_config</span><span class="p">,</span> <span class="n">key</span><span class="p">,</span> <span class="n">value</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">already_quantized</span> <span class="o">=</span> <span class="kc">False</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">load_format</span> <span class="o">==</span> <span class="s1">&#39;dummy&#39;</span><span class="p">:</span>
<span class="n">config</span> <span class="o">=</span> <span class="n">model_cls</span><span class="o">.</span><span class="n">config_class</span><span class="o">.</span><span class="n">from_hugging_face</span><span class="p">(</span>
<span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_model_dir</span><span class="p">),</span>
<span class="n">dtype</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
<span class="n">mapping</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">mapping</span><span class="p">,</span>
<span class="n">quant_config</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">quant_config</span><span class="p">,</span>
<span class="o">**</span><span class="bp">self</span><span class="o">.</span><span class="n">convert_checkpoint_options</span><span class="p">,</span>
<span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">model</span> <span class="o">=</span> <span class="n">model_cls</span><span class="p">(</span><span class="n">config</span><span class="p">)</span>
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">quant_config</span><span class="o">.</span><span class="n">requires_calibration</span> <span class="ow">and</span> <span class="ow">not</span> <span class="n">already_quantized</span><span class="p">:</span>
<span class="k">assert</span> <span class="bp">self</span><span class="o">.</span><span class="n">workspace</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span>
<span class="n">checkpoint_dir</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">workspace</span><span class="si">}</span><span class="s2">/quantized-checkpoint&quot;</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">rank</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
<span class="n">model_cls</span><span class="o">.</span><span class="n">quantize</span><span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_model_dir</span><span class="p">,</span>
<span class="n">checkpoint_dir</span><span class="p">,</span>
<span class="n">dtype</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
<span class="n">mapping</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">mapping</span><span class="p">,</span>
<span class="n">quant_config</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">quant_config</span><span class="p">,</span>
<span class="o">**</span><span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">calib_config</span><span class="o">.</span><span class="n">to_dict</span><span class="p">(),</span>
<span class="n">trust_remote_code</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">trust_remote_code</span><span class="p">,</span>
<span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">parallel_config</span><span class="o">.</span><span class="n">is_multi_gpu</span><span class="p">:</span>
<span class="n">mpi_barrier</span><span class="p">()</span>
<span class="bp">self</span><span class="o">.</span><span class="n">model</span> <span class="o">=</span> <span class="n">model_cls</span><span class="o">.</span><span class="n">from_checkpoint</span><span class="p">(</span><span class="n">checkpoint_dir</span><span class="p">,</span>
<span class="n">rank</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">mapping</span><span class="o">.</span><span class="n">rank</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">model</span> <span class="o">=</span> <span class="n">model_cls</span><span class="o">.</span><span class="n">from_hugging_face</span><span class="p">(</span>
<span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_model_dir</span><span class="p">),</span>
<span class="n">dtype</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
<span class="n">mapping</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">mapping</span><span class="p">,</span>
<span class="n">quant_config</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">quant_config</span><span class="p">,</span>
<span class="n">load_model_on_cpu</span><span class="o">=</span>
<span class="kc">True</span><span class="p">,</span> <span class="c1"># TODO:TRTLLM-195 to enhance the weights loading memory usage and chose best location</span>
<span class="n">trust_remote_code</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">trust_remote_code</span><span class="p">,</span>
<span class="n">speculative_model</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">_speculative_model_dir</span><span class="p">,</span>
<span class="n">medusa_num_heads</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">speculative_config</span><span class="o">.</span>
<span class="n">num_medusa_heads</span> <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">speculative_config</span><span class="p">,</span>
<span class="n">MedusaDecodingConfig</span><span class="p">)</span> <span class="k">else</span> <span class="kc">None</span><span class="p">,</span>
<span class="o">**</span><span class="bp">self</span><span class="o">.</span><span class="n">convert_checkpoint_options</span><span class="p">,</span>
<span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">pretrained_config</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="o">.</span><span class="n">config</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_model_info</span> <span class="o">=</span> <span class="n">_ModelInfo</span><span class="o">.</span><span class="n">from_pretrained_config</span><span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">pretrained_config</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">_load_model_from_ckpt</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="w"> </span><span class="sd">&#39;&#39;&#39; Load a TRT-LLM model from checkpoint. &#39;&#39;&#39;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">pretrained_config</span> <span class="o">=</span> <span class="n">PretrainedConfig</span><span class="o">.</span><span class="n">from_json_file</span><span class="p">(</span>
<span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_model_dir</span><span class="p">,</span> <span class="s1">&#39;config.json&#39;</span><span class="p">))</span>
<span class="bp">self</span><span class="o">.</span><span class="n">pretrained_config</span><span class="o">.</span><span class="n">mapping</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">mapping</span>
<span class="c1">#TODO: TRTLLM-1091, change the architecture in the checkpoint to TRT-LLM one, not HF one.</span>
<span class="n">architecture</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">pretrained_config</span><span class="o">.</span><span class="n">architecture</span>
<span class="k">assert</span> <span class="n">architecture</span> <span class="ow">in</span> <span class="n">MODEL_MAP</span><span class="p">,</span> \
<span class="sa">f</span><span class="s2">&quot;Unsupported model architecture: </span><span class="si">{</span><span class="n">architecture</span><span class="si">}</span><span class="s2">&quot;</span>
<span class="n">model_cls</span> <span class="o">=</span> <span class="n">MODEL_MAP</span><span class="p">[</span><span class="n">architecture</span><span class="p">]</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">load_format</span> <span class="o">==</span> <span class="s1">&#39;dummy&#39;</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">model</span> <span class="o">=</span> <span class="n">model_cls</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">pretrained_config</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">model</span> <span class="o">=</span> <span class="n">model_cls</span><span class="o">.</span><span class="n">from_checkpoint</span><span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_model_dir</span><span class="p">,</span> <span class="n">config</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">pretrained_config</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_model_info</span> <span class="o">=</span> <span class="n">_ModelInfo</span><span class="o">.</span><span class="n">from_pretrained_config</span><span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">pretrained_config</span><span class="p">)</span>
<span class="c1"># load parallel embedding related options</span>
<span class="bp">self</span><span class="o">.</span><span class="n">convert_checkpoint_options</span><span class="p">[</span>
<span class="s1">&#39;use_parallel_embedding&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">pretrained_config</span><span class="o">.</span><span class="n">use_parallel_embedding</span>
<span class="k">def</span> <span class="nf">_build_engine_from_inmemory_model</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">model</span><span class="p">,</span> <span class="n">Module</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_model_info</span> <span class="o">=</span> <span class="n">_ModelInfo</span><span class="o">.</span><span class="n">from_module</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">_build_engine</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">build_config</span><span class="p">,</span>
<span class="n">BuildConfig</span><span class="p">),</span> <span class="sa">f</span><span class="s2">&quot;build_config is not set yet: </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">build_config</span><span class="si">}</span><span class="s2">&quot;</span>
<span class="c1"># avoid the original build_config is modified, avoid the side effect</span>
<span class="n">copied_build_config</span> <span class="o">=</span> <span class="n">copy</span><span class="o">.</span><span class="n">deepcopy</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">build_config</span><span class="p">)</span>
<span class="n">copied_build_config</span><span class="o">.</span><span class="n">update</span><span class="p">(</span>
<span class="n">auto_parallel_config</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">auto_parallel_config</span><span class="p">)</span>
<span class="n">copied_build_config</span><span class="o">.</span><span class="n">update_kv_cache_type</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_model_info</span><span class="o">.</span><span class="n">architecture</span><span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">auto_parallel_config</span><span class="o">.</span><span class="n">enabled</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="o">.</span><span class="n">config</span><span class="o">.</span><span class="n">mapping</span><span class="o">.</span><span class="n">rank</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">rank</span>
<span class="k">assert</span> <span class="bp">self</span><span class="o">.</span><span class="n">model</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">,</span> <span class="s2">&quot;model is loaded yet.&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_engine</span> <span class="o">=</span> <span class="n">build</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">,</span> <span class="n">copied_build_config</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">mapping</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="o">.</span><span class="n">config</span><span class="o">.</span><span class="n">mapping</span>
<span class="c1"># delete the model explicitly to free all the build-time resources</span>
<span class="bp">self</span><span class="o">.</span><span class="n">model</span> <span class="o">=</span> <span class="kc">None</span>
<span class="k">def</span> <span class="nf">_save_engine_for_runtime</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="w"> </span><span class="sd">&#39;&#39;&#39;</span>
<span class="sd"> Persist the engine to disk for the cpp runtime. Currently, the cpp runtime can accept an engine path,</span>
<span class="sd"> that requires the engine should always be saved to disk.</span>
<span class="sd"> This explicit saving will be removed in the future when the cpp runtime can accept the engine buffer directly.</span>
<span class="sd"> But this is necessary for a build cache, but it can be optimized to async IO.</span>
<span class="sd"> &#39;&#39;&#39;</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">build_cache_enabled</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_model_dir</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">engine_cache_stage</span><span class="o">.</span><span class="n">cache_dir</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_model_format</span> <span class="o">=</span> <span class="n">_ModelFormatKind</span><span class="o">.</span><span class="n">TLLM_ENGINE</span>
<span class="k">return</span>
<span class="k">def</span> <span class="nf">_load_engine_buffer</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="c1"># Load engine buffer from disk</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_engine</span> <span class="o">=</span> <span class="n">Engine</span><span class="o">.</span><span class="n">from_dir</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_model_dir</span><span class="p">)</span>
<span class="nd">@staticmethod</span>
<span class="k">def</span> <span class="nf">load_extra_build_configs_from_engine</span><span class="p">(</span>
<span class="n">model_dir</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Namespace</span><span class="p">]:</span>
<span class="w"> </span><span class="sd">&#39;&#39;&#39; Load the extra build configs from the engine directory, return None if model isn&#39;t an engine. &#39;&#39;&#39;</span>
<span class="k">if</span> <span class="n">ModelLoader</span><span class="o">.</span><span class="n">get_model_format</span><span class="p">(</span>
<span class="n">model_dir</span><span class="p">)</span> <span class="ow">is</span> <span class="ow">not</span> <span class="n">_ModelFormatKind</span><span class="o">.</span><span class="n">TLLM_ENGINE</span><span class="p">:</span>
<span class="k">return</span> <span class="kc">None</span>
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">Path</span><span class="p">(</span><span class="n">model_dir</span><span class="p">)</span> <span class="o">/</span> <span class="s2">&quot;config.json&quot;</span><span class="p">,</span> <span class="s2">&quot;r&quot;</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
<span class="n">engine_config</span> <span class="o">=</span> <span class="n">json</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">f</span><span class="p">)</span>
<span class="n">build_config</span> <span class="o">=</span> <span class="n">engine_config</span><span class="p">[</span><span class="s1">&#39;build_config&#39;</span><span class="p">]</span>
<span class="n">build_config</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s2">&quot;plugin_config&quot;</span><span class="p">)</span>
<span class="k">return</span> <span class="n">Namespace</span><span class="p">(</span><span class="o">**</span><span class="n">build_config</span><span class="p">)</span>
<span class="nd">@staticmethod</span>
<span class="k">def</span> <span class="nf">load_hf_tokenizer</span><span class="p">(</span>
<span class="n">model_dir</span><span class="p">,</span>
<span class="n">trust_remote_code</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
<span class="n">use_fast</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Optional</span><span class="p">[</span><span class="n">TransformersTokenizer</span><span class="p">]:</span>
<span class="k">if</span> <span class="p">(</span><span class="n">tokenizer</span> <span class="o">:=</span> <span class="n">load_hf_tokenizer</span><span class="p">(</span><span class="n">model_dir</span><span class="p">,</span> <span class="n">trust_remote_code</span><span class="p">,</span>
<span class="n">use_fast</span><span class="p">))</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="k">return</span> <span class="n">tokenizer</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Failed to load tokenizer from </span><span class="si">{</span><span class="n">model_dir</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">e</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
<span class="k">return</span> <span class="kc">None</span>
<span class="k">class</span> <span class="nc">CachedModelLoader</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&#39;&#39;&#39;</span>
<span class="sd"> The CacheModelLoader is used to build the model in both single or multi-gpu, with cache might be enabled.</span>
<span class="sd"> &#39;&#39;&#39;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>
<span class="bp">self</span><span class="p">,</span>
<span class="n">llm_args</span><span class="p">:</span> <span class="n">LlmArgs</span><span class="p">,</span>
<span class="n">llm_build_stats</span><span class="p">:</span> <span class="n">weakref</span><span class="o">.</span><span class="n">ReferenceType</span><span class="p">[</span><span class="s2">&quot;LlmBuildStats&quot;</span><span class="p">],</span>
<span class="n">mpi_session</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">MpiSession</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
<span class="n">workspace</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
<span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span> <span class="o">=</span> <span class="n">llm_args</span>
<span class="bp">self</span><span class="o">.</span><span class="n">mpi_session</span> <span class="o">=</span> <span class="n">mpi_session</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_workspace</span> <span class="o">=</span> <span class="n">workspace</span> <span class="ow">or</span> <span class="n">tempfile</span><span class="o">.</span><span class="n">TemporaryDirectory</span><span class="p">()</span>
<span class="bp">self</span><span class="o">.</span><span class="n">llm_build_stats</span> <span class="o">=</span> <span class="n">llm_build_stats</span>
<span class="c1"># This is used for build cache. To compute the cache key, a local HF model is required, it could be download</span>
<span class="c1"># from HF model hub, so this helps to hold the path.</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_hf_model_dir</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Path</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">workspace</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Path</span><span class="p">:</span>
<span class="k">return</span> <span class="n">Path</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_workspace</span><span class="o">.</span><span class="n">name</span><span class="p">)</span> <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_workspace</span><span class="p">,</span> <span class="n">tempfile</span><span class="o">.</span><span class="n">TemporaryDirectory</span><span class="p">)</span> <span class="k">else</span> <span class="n">Path</span><span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_workspace</span><span class="p">)</span>
<span class="k">def</span> <span class="fm">__call__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Tuple</span><span class="p">[</span><span class="n">Path</span><span class="p">,</span> <span class="n">Union</span><span class="p">[</span><span class="n">Path</span><span class="p">,</span> <span class="kc">None</span><span class="p">]]:</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">model_format</span> <span class="ow">is</span> <span class="n">_ModelFormatKind</span><span class="o">.</span><span class="n">TLLM_ENGINE</span><span class="p">:</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">model</span><span class="p">,</span> <span class="kc">None</span>
<span class="bp">self</span><span class="o">.</span><span class="n">engine_cache_stage</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">CachedStage</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_hf_model_dir</span> <span class="o">=</span> <span class="kc">None</span>
<span class="bp">self</span><span class="o">.</span><span class="n">model_loader</span> <span class="o">=</span> <span class="n">ModelLoader</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">build_cache_enabled</span><span class="p">:</span>
<span class="n">print_colored</span><span class="p">(</span><span class="s2">&quot;Build cache is enabled.</span><span class="se">\n</span><span class="s2">&quot;</span><span class="p">,</span> <span class="s1">&#39;yellow&#39;</span><span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">model_loader</span><span class="o">.</span><span class="n">model_obj</span><span class="o">.</span><span class="n">is_hub_model</span><span class="p">:</span>
<span class="c1"># This will download the config.json from HF model hub, this helps to create a PretrainedConfig for</span>
<span class="c1"># cache key.</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_hf_model_dir</span> <span class="o">=</span> <span class="n">download_hf_pretrained_config</span><span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">model_loader</span><span class="o">.</span><span class="n">model_obj</span><span class="o">.</span><span class="n">model_name</span><span class="p">,</span>
<span class="n">revision</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">revision</span><span class="p">)</span>
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">model_loader</span><span class="o">.</span><span class="n">model_obj</span><span class="o">.</span><span class="n">is_local_model</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_hf_model_dir</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">model_loader</span><span class="o">.</span><span class="n">model_obj</span><span class="o">.</span><span class="n">model_dir</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">model_format</span> <span class="ow">is</span> <span class="n">_ModelFormatKind</span><span class="o">.</span><span class="n">HF</span> <span class="k">else</span> <span class="kc">None</span>
<span class="bp">self</span><span class="o">.</span><span class="n">engine_cache_stage</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_get_engine_cache_stage</span><span class="p">()</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">engine_cache_stage</span><span class="o">.</span><span class="n">is_cached</span><span class="p">():</span>
<span class="bp">self</span><span class="o">.</span><span class="n">llm_build_stats</span><span class="o">.</span><span class="n">cache_hitted</span> <span class="o">=</span> <span class="kc">True</span>
<span class="n">print_colored</span><span class="p">(</span>
<span class="sa">f</span><span class="s2">&quot;Reusing cached engine in </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">engine_cache_stage</span><span class="o">.</span><span class="n">get_engine_path</span><span class="p">()</span><span class="si">}</span><span class="se">\n\n</span><span class="s2">&quot;</span><span class="p">,</span>
<span class="s1">&#39;grey&#39;</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">model_loader</span><span class="o">.</span><span class="n">model_obj</span><span class="o">.</span><span class="n">model_dir</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">engine_cache_stage</span><span class="o">.</span><span class="n">get_engine_path</span><span class="p">(</span>
<span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">llm_build_stats</span><span class="o">.</span><span class="n">engine_dir</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">model_loader</span><span class="o">.</span><span class="n">model_obj</span><span class="o">.</span><span class="n">model_dir</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm_build_stats</span><span class="o">.</span><span class="n">engine_dir</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_hf_model_dir</span>
<span class="c1"># PIVOT_TO_PYTHON_START</span>
<span class="kn">from</span> <span class="nn">tensorrt_llm.pyexecutor.backend_registries.backend_registry</span> <span class="kn">import</span> \
<span class="n">get_backend_info</span>
<span class="k">if</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">backend</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">)</span> <span class="ow">and</span> <span class="n">get_backend_info</span><span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">backend</span><span class="p">,</span> <span class="s1">&#39;need_hf_model&#39;</span><span class="p">):</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">model_loader</span><span class="o">.</span><span class="n">model_obj</span><span class="o">.</span><span class="n">is_hub_model</span><span class="p">:</span>
<span class="n">hf_folder</span> <span class="o">=</span> <span class="n">download_hf_model</span><span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">model_loader</span><span class="o">.</span><span class="n">model_obj</span><span class="o">.</span><span class="n">model_name</span><span class="p">,</span>
<span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">revision</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_hf_model_dir</span> <span class="o">=</span> <span class="n">hf_folder</span>
<span class="k">else</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_hf_model_dir</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">model_loader</span><span class="o">.</span><span class="n">model_obj</span><span class="o">.</span><span class="n">model_dir</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">quant_config</span><span class="o">.</span><span class="n">quant_algo</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">logger</span><span class="o">.</span><span class="n">warning</span><span class="p">(</span>
<span class="s2">&quot;QuantConfig for pytorch backend is ignored. You can load&quot;</span>
<span class="s2">&quot;quantized model with hf_quant_config.json directly.&quot;</span><span class="p">)</span>
<span class="k">return</span> <span class="kc">None</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_hf_model_dir</span>
<span class="c1"># PIVOT_TO_PYTHON_END</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_build_model</span><span class="p">(),</span> <span class="bp">self</span><span class="o">.</span><span class="n">_hf_model_dir</span>
<span class="k">def</span> <span class="nf">get_engine_dir</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Path</span><span class="p">:</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">model_format</span> <span class="ow">is</span> <span class="n">_ModelFormatKind</span><span class="o">.</span><span class="n">TLLM_ENGINE</span><span class="p">:</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">model_obj</span><span class="o">.</span><span class="n">model_dir</span>
<span class="c1"># generate a new path for writing the engine</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">build_cache_enabled</span><span class="p">:</span>
<span class="n">cache_stage</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_get_engine_cache_stage</span><span class="p">()</span>
<span class="k">return</span> <span class="n">cache_stage</span><span class="o">.</span><span class="n">get_engine_path</span><span class="p">()</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">workspace</span> <span class="o">/</span> <span class="s2">&quot;tmp.engine&quot;</span>
<span class="nd">@property</span>
<span class="k">def</span> <span class="nf">build_cache_enabled</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">bool</span><span class="p">:</span>
<span class="n">_enable_build_cache</span><span class="p">,</span> <span class="n">_</span> <span class="o">=</span> <span class="n">get_build_cache_config_from_env</span><span class="p">()</span>
<span class="k">return</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">enable_build_cache</span> <span class="ow">or</span> <span class="n">_enable_build_cache</span><span class="p">)</span> <span class="ow">and</span> <span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">model_format</span> <span class="ow">is</span> <span class="n">_ModelFormatKind</span><span class="o">.</span><span class="n">HF</span>
<span class="p">)</span> <span class="ow">and</span> <span class="ow">not</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">parallel_config</span><span class="o">.</span><span class="n">auto_parallel</span>
<span class="k">def</span> <span class="nf">_get_engine_cache_stage</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">CachedStage</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&#39;&#39;&#39; Get the cache stage for engine building. &#39;&#39;&#39;</span>
<span class="n">build_cache</span> <span class="o">=</span> <span class="n">BuildCache</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">enable_build_cache</span><span class="p">)</span>
<span class="k">assert</span> <span class="bp">self</span><span class="o">.</span><span class="n">_hf_model_dir</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">,</span> <span class="s2">&quot;HF model dir is required for cache key.&quot;</span>
<span class="k">def</span> <span class="nf">serialize</span><span class="p">(</span><span class="n">d</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">str</span><span class="p">:</span>
<span class="n">dic</span> <span class="o">=</span> <span class="n">asdict</span><span class="p">(</span><span class="n">d</span><span class="p">)</span> <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span>
<span class="n">d</span><span class="p">,</span> <span class="n">PretrainedConfig</span><span class="p">)</span> <span class="k">else</span> <span class="n">d</span><span class="o">.</span><span class="n">to_dict</span><span class="p">()</span>
<span class="k">return</span> <span class="n">json</span><span class="o">.</span><span class="n">dumps</span><span class="p">(</span><span class="n">dic</span><span class="p">,</span> <span class="n">sort_keys</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">parallel_config</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">parallel_config</span>
<span class="n">force_rebuild</span> <span class="o">=</span> <span class="kc">False</span>
<span class="k">if</span> <span class="n">parallel_config</span><span class="o">.</span><span class="n">auto_parallel</span><span class="p">:</span>
<span class="n">force_rebuild</span> <span class="o">=</span> <span class="kc">True</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">model_format</span> <span class="ow">is</span> <span class="ow">not</span> <span class="n">_ModelFormatKind</span><span class="o">.</span><span class="n">HF</span><span class="p">:</span>
<span class="n">force_rebuild</span> <span class="o">=</span> <span class="kc">True</span>
<span class="k">return</span> <span class="n">build_cache</span><span class="o">.</span><span class="n">get_engine_building_cache_stage</span><span class="p">(</span>
<span class="n">build_config</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">build_config</span><span class="p">,</span>
<span class="n">model_path</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">_hf_model_dir</span><span class="p">,</span>
<span class="n">force_rebuild</span><span class="o">=</span><span class="n">force_rebuild</span><span class="p">,</span>
<span class="c1"># Other configs affecting the engine building</span>
<span class="n">parallel_config</span><span class="o">=</span><span class="n">serialize</span><span class="p">(</span><span class="n">parallel_config</span><span class="p">),</span>
<span class="n">pretrained_config</span><span class="o">=</span><span class="n">serialize</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">get_pretrained_config</span><span class="p">()),</span>
<span class="n">quant_config</span><span class="o">=</span><span class="n">serialize</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">quant_config</span><span class="p">),</span>
<span class="p">)</span>
<span class="k">def</span> <span class="nf">get_pretrained_config</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">PretrainedConfig</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&#39;&#39;&#39; Get the PretrainedConfig for cache key.</span>
<span class="sd"> NOTE, this is not the HF model&#39;s config, but the TRT-LLM&#39;s config. We use this as a generic information for</span>
<span class="sd"> HF and other models. &#39;&#39;&#39;</span>
<span class="k">assert</span> <span class="bp">self</span><span class="o">.</span><span class="n">_hf_model_dir</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span>
<span class="k">return</span> <span class="n">AutoConfig</span><span class="o">.</span><span class="n">from_hugging_face</span><span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_hf_model_dir</span><span class="p">,</span>
<span class="n">mapping</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">parallel_config</span><span class="o">.</span><span class="n">to_mapping</span><span class="p">(),</span>
<span class="n">quant_config</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">quant_config</span><span class="p">,</span>
<span class="n">dtype</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">_build_model</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Path</span><span class="p">:</span>
<span class="n">model_format</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">model_format</span>
<span class="k">def</span> <span class="nf">build_task</span><span class="p">(</span><span class="n">engine_dir</span><span class="p">:</span> <span class="n">Path</span><span class="p">):</span>
<span class="k">if</span> <span class="n">model_format</span> <span class="ow">is</span> <span class="ow">not</span> <span class="n">_ModelFormatKind</span><span class="o">.</span><span class="n">TLLM_ENGINE</span><span class="p">:</span>
<span class="n">model_loader_kwargs</span> <span class="o">=</span> <span class="p">{</span>
<span class="s1">&#39;llm_args&#39;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="p">,</span>
<span class="s1">&#39;workspace&#39;</span><span class="p">:</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">workspace</span><span class="p">),</span>
<span class="s1">&#39;llm_build_stats&#39;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm_build_stats</span><span class="p">,</span>
<span class="p">}</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm_args</span><span class="o">.</span><span class="n">parallel_config</span><span class="o">.</span><span class="n">is_multi_gpu</span><span class="p">:</span>
<span class="k">assert</span> <span class="bp">self</span><span class="o">.</span><span class="n">mpi_session</span>
<span class="c1"># The engine_dir:Path will be stored to MPINodeState.state</span>
<span class="n">build_infos</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">mpi_session</span><span class="o">.</span><span class="n">submit_sync</span><span class="p">(</span>
<span class="n">CachedModelLoader</span><span class="o">.</span><span class="n">_node_build_task</span><span class="p">,</span>
<span class="n">engine_dir</span><span class="o">=</span><span class="n">engine_dir</span><span class="p">,</span>
<span class="o">**</span><span class="n">model_loader_kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">llm_build_stats</span><span class="o">.</span><span class="n">build_steps_info</span> <span class="o">=</span> <span class="n">build_infos</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
<span class="k">else</span><span class="p">:</span> <span class="c1"># single-gpu</span>
<span class="k">with</span> <span class="n">ModelLoader</span><span class="p">(</span><span class="o">**</span><span class="n">model_loader_kwargs</span><span class="p">)</span> <span class="k">as</span> <span class="n">model_loader</span><span class="p">:</span>
<span class="n">model_loader</span><span class="p">(</span><span class="n">engine_dir</span><span class="o">=</span><span class="n">engine_dir</span><span class="p">)</span>
<span class="n">release_gc</span><span class="p">()</span>
<span class="n">has_storage</span> <span class="o">=</span> <span class="kc">True</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">build_cache_enabled</span><span class="p">:</span>
<span class="k">try</span><span class="p">:</span>
<span class="c1"># TODO[chunweiy]: Cover the case when the model is from HF model hub.</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">model_loader</span><span class="o">.</span><span class="n">model_obj</span><span class="o">.</span><span class="n">is_local_model</span><span class="p">:</span>
<span class="c1"># This is not perfect, but will make build-cache much more robust.</span>
<span class="n">free_storage</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">engine_cache_stage</span><span class="o">.</span><span class="n">parent</span><span class="o">.</span><span class="n">free_storage_in_gb</span><span class="p">(</span>
<span class="p">)</span>
<span class="n">model_size</span> <span class="o">=</span> <span class="n">get_directory_size_in_gb</span><span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">model_loader</span><span class="o">.</span><span class="n">model_obj</span><span class="o">.</span><span class="n">model_dir</span><span class="p">)</span>
<span class="n">require_size</span> <span class="o">=</span> <span class="n">model_size</span> <span class="o">*</span> <span class="mf">1.3</span>
<span class="n">has_storage</span> <span class="o">=</span> <span class="n">free_storage</span> <span class="o">&gt;=</span> <span class="n">require_size</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">has_storage</span><span class="p">:</span>
<span class="n">print_colored</span><span class="p">(</span>
<span class="sa">f</span><span class="s2">&quot;Build cache is disabled since the cache storage is too small.</span><span class="se">\n</span><span class="s2"> &quot;</span><span class="p">,</span>
<span class="s1">&#39;yellow&#39;</span><span class="p">)</span>
<span class="n">print_colored</span><span class="p">(</span>
<span class="sa">f</span><span class="s2">&quot;Free storage: </span><span class="si">{</span><span class="n">free_storage</span><span class="si">}</span><span class="s2">GB, Required storage: </span><span class="si">{</span><span class="n">require_size</span><span class="si">}</span><span class="s2">GB</span><span class="se">\n</span><span class="s2">&quot;</span><span class="p">,</span>
<span class="s1">&#39;grey&#39;</span><span class="p">)</span>
<span class="k">except</span> <span class="ne">ValueError</span><span class="p">:</span>
<span class="n">has_storage</span> <span class="o">=</span> <span class="kc">False</span>
<span class="k">except</span> <span class="ne">Exception</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
<span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="p">(</span><span class="n">e</span><span class="p">)</span>
<span class="n">has_storage</span> <span class="o">=</span> <span class="kc">False</span>
<span class="k">if</span> <span class="n">enable_llm_debug</span><span class="p">():</span>
<span class="n">print_colored</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Has cache storage: </span><span class="si">{</span><span class="n">has_storage</span><span class="si">}</span><span class="se">\n</span><span class="s2">&quot;</span><span class="p">,</span> <span class="s1">&#39;yellow&#39;</span><span class="p">)</span>
<span class="k">if</span> <span class="n">has_storage</span><span class="p">:</span>
<span class="k">with</span> <span class="bp">self</span><span class="o">.</span><span class="n">engine_cache_stage</span><span class="o">.</span><span class="n">write_guard</span><span class="p">()</span> <span class="k">as</span> <span class="n">engine_dir</span><span class="p">:</span>
<span class="n">build_task</span><span class="p">(</span><span class="n">engine_dir</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">llm_build_stats</span><span class="o">.</span><span class="n">cache_hitted</span> <span class="o">=</span> <span class="kc">True</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">print_colored</span><span class="p">(</span>
<span class="s2">&quot;The cache directory is too small, build-cache is disabled.</span><span class="se">\n</span><span class="s2">&quot;</span><span class="p">,</span>
<span class="s1">&#39;grey&#39;</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">llm_build_stats</span><span class="o">.</span><span class="n">cache_hitted</span> <span class="o">=</span> <span class="kc">False</span>
<span class="bp">self</span><span class="o">.</span><span class="n">llm_build_stats</span><span class="o">.</span><span class="n">cache_info</span> <span class="o">=</span> <span class="s2">&quot;The cache root directory is too small.&quot;</span>
<span class="k">if</span> <span class="ow">not</span> <span class="p">(</span><span class="n">has_storage</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">build_cache_enabled</span><span class="p">):</span>
<span class="n">build_task</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">get_engine_dir</span><span class="p">())</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_engine_dir</span><span class="p">()</span>
<span class="nd">@print_traceback_on_error</span>
<span class="nd">@staticmethod</span>
<span class="k">def</span> <span class="nf">_node_build_task</span><span class="p">(</span>
<span class="n">llm_args</span><span class="p">:</span> <span class="n">LlmArgs</span><span class="p">,</span>
<span class="n">workspace</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">str</span> <span class="o">|</span> <span class="n">tempfile</span><span class="o">.</span><span class="n">TemporaryDirectory</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
<span class="n">llm_build_stats</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="s1">&#39;LlmBuildStats&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
<span class="n">engine_dir</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Path</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
<span class="p">):</span>
<span class="k">if</span> <span class="n">MPINodeState</span><span class="o">.</span><span class="n">is_initialized</span><span class="p">():</span>
<span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="s2">&quot;The MPI node is already initialized.&quot;</span><span class="p">)</span>
<span class="k">with</span> <span class="n">ModelLoader</span><span class="p">(</span><span class="n">llm_args</span><span class="p">,</span>
<span class="n">workspace</span><span class="o">=</span><span class="n">workspace</span><span class="p">,</span>
<span class="n">llm_build_stats</span><span class="o">=</span><span class="n">llm_build_stats</span><span class="p">)</span> <span class="k">as</span> <span class="n">model_loader</span><span class="p">:</span>
<span class="n">model_loader</span><span class="p">(</span><span class="n">engine_dir</span><span class="o">=</span><span class="n">engine_dir</span><span class="p">)</span>
<span class="k">return</span> <span class="n">model_loader</span><span class="o">.</span><span class="n">llm_build_stats</span><span class="o">.</span><span class="n">build_steps_info</span>
<span class="k">def</span> <span class="nf">save</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">engine_dir</span><span class="p">:</span> <span class="n">Path</span><span class="p">):</span>
<span class="c1"># copy the engine directory to the target directory</span>
<span class="n">shutil</span><span class="o">.</span><span class="n">copytree</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">get_engine_dir</span><span class="p">(),</span> <span class="n">engine_dir</span><span class="p">)</span>
<span class="nd">@dataclass</span>
<span class="k">class</span> <span class="nc">LlmBuildStats</span><span class="p">:</span>
<span class="w"> </span><span class="sd">&#39;&#39;&#39; LlmBuildStats is the statistics for the LLM model building. &#39;&#39;&#39;</span>
<span class="c1"># Whether the cache is hit for the engine</span>
<span class="n">cache_hitted</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
<span class="n">cache_info</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">model_from_hf_hub</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
<span class="n">local_model_dir</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Path</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="c1"># The path to the trt-llm engine</span>
<span class="n">engine_dir</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Path</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
<span class="c1"># The build steps information, including the step name and the latency in seconds.</span>
<span class="n">build_steps_info</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="n">Tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">float</span><span class="p">]]</span> <span class="o">=</span> <span class="n">field</span><span class="p">(</span><span class="n">default_factory</span><span class="o">=</span><span class="nb">list</span><span class="p">)</span>
</pre></div>
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