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<h1>Source code for tensorrt_llm.runtime.model_runner</h1><div class="highlight"><pre>
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<span></span><span class="c1"># SPDX-FileCopyrightText: Copyright (c) 2022-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.</span>
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<span class="c1"># SPDX-License-Identifier: Apache-2.0</span>
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<span class="c1">#</span>
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<span class="c1"># Licensed under the Apache License, Version 2.0 (the "License");</span>
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<span class="c1"># you may not use this file except in compliance with the License.</span>
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<span class="c1"># You may obtain a copy of the License at</span>
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<span class="c1">#</span>
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<span class="c1"># http://www.apache.org/licenses/LICENSE-2.0</span>
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<span class="c1">#</span>
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<span class="c1"># Unless required by applicable law or agreed to in writing, software</span>
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<span class="c1"># distributed under the License is distributed on an "AS IS" BASIS,</span>
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<span class="c1"># WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.</span>
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<span class="c1"># See the License for the specific language governing permissions and</span>
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<span class="c1"># limitations under the License.</span>
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<span class="kn">import</span> <span class="nn">copy</span>
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<span class="kn">import</span> <span class="nn">json</span>
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<span class="kn">from</span> <span class="nn">pathlib</span> <span class="kn">import</span> <span class="n">Path</span>
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<span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">List</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>
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<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
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<span class="kn">import</span> <span class="nn">tensorrt</span> <span class="k">as</span> <span class="nn">trt</span>
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<span class="kn">import</span> <span class="nn">torch</span>
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<span class="kn">from</span> <span class="nn">..</span> <span class="kn">import</span> <span class="n">profiler</span>
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<span class="kn">from</span> <span class="nn">.._utils</span> <span class="kn">import</span> <span class="n">mpi_world_size</span>
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<span class="kn">from</span> <span class="nn">..builder</span> <span class="kn">import</span> <span class="n">Engine</span><span class="p">,</span> <span class="n">get_engine_version</span>
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<span class="kn">from</span> <span class="nn">..logger</span> <span class="kn">import</span> <span class="n">logger</span>
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<span class="kn">from</span> <span class="nn">..mapping</span> <span class="kn">import</span> <span class="n">Mapping</span>
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<span class="kn">from</span> <span class="nn">..quantization</span> <span class="kn">import</span> <span class="n">QuantMode</span>
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<span class="kn">from</span> <span class="nn">.generation</span> <span class="kn">import</span> <span class="p">(</span><span class="n">ChatGLMGenerationSession</span><span class="p">,</span> <span class="n">GenerationSession</span><span class="p">,</span>
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<span class="n">LogitsProcessor</span><span class="p">,</span> <span class="n">LoraManager</span><span class="p">,</span>
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<span class="n">MambaLMHeadModelGenerationSession</span><span class="p">,</span> <span class="n">ModelConfig</span><span class="p">,</span>
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<span class="n">QWenForCausalLMGenerationSession</span><span class="p">,</span> <span class="n">SamplingConfig</span><span class="p">,</span>
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<span class="n">StoppingCriteria</span><span class="p">)</span>
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<span class="k">def</span> <span class="nf">get_engine_name</span><span class="p">(</span><span class="n">model</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">dtype</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">tp_size</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">pp_size</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
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<span class="n">rank</span><span class="p">:</span> <span class="nb">int</span><span class="p">)</span> <span class="o">-></span> <span class="nb">str</span><span class="p">:</span>
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<span class="w"> </span><span class="sd">"""</span>
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<span class="sd"> Get the serialized engine file name.</span>
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<span class="sd"> Args:</span>
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<span class="sd"> model (str):</span>
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<span class="sd"> Model name, e.g., bloom, gpt.</span>
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<span class="sd"> dtype (str):</span>
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<span class="sd"> Data type, e.g., float32, float16, bfloat16,</span>
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<span class="sd"> tp_size (int):</span>
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<span class="sd"> The size of tensor parallel.</span>
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<span class="sd"> pp_size (int):</span>
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<span class="sd"> The size of pipeline parallel.</span>
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<span class="sd"> rank (int):</span>
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<span class="sd"> The rank id.</span>
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<span class="sd"> Returns:</span>
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<span class="sd"> str: The serialized engine file name.</span>
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<span class="sd"> """</span>
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<span class="k">if</span> <span class="n">pp_size</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
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<span class="k">return</span> <span class="s1">'</span><span class="si">{}</span><span class="s1">_</span><span class="si">{}</span><span class="s1">_tp</span><span class="si">{}</span><span class="s1">_rank</span><span class="si">{}</span><span class="s1">.engine'</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">dtype</span><span class="p">,</span> <span class="n">tp_size</span><span class="p">,</span> <span class="n">rank</span><span class="p">)</span>
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<span class="k">return</span> <span class="s1">'</span><span class="si">{}</span><span class="s1">_</span><span class="si">{}</span><span class="s1">_tp</span><span class="si">{}</span><span class="s1">_pp</span><span class="si">{}</span><span class="s1">_rank</span><span class="si">{}</span><span class="s1">.engine'</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">dtype</span><span class="p">,</span> <span class="n">tp_size</span><span class="p">,</span>
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<span class="n">pp_size</span><span class="p">,</span> <span class="n">rank</span><span class="p">)</span>
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<span class="k">def</span> <span class="nf">read_config</span><span class="p">(</span><span class="n">config_path</span><span class="p">:</span> <span class="n">Path</span><span class="p">)</span> <span class="o">-></span> <span class="n">Tuple</span><span class="p">[</span><span class="n">ModelConfig</span><span class="p">,</span> <span class="nb">dict</span><span class="p">]:</span>
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|
<span class="w"> </span><span class="sd">"""</span>
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<span class="sd"> Read the engine config file and create a ModelConfig instance, return the ModelConfig instance</span>
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<span class="sd"> and other config fields in a dict.</span>
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|
|
|
<span class="sd"> Args:</span>
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|
<span class="sd"> config_path (Path):</span>
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|
<span class="sd"> The path of engine config file.</span>
|
|
|
|
<span class="sd"> Returns:</span>
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|
<span class="sd"> Tuple[ModelConfig, dict]: A ModelConfig instance and other config fields.</span>
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|
<span class="sd"> """</span>
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|
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">config_path</span><span class="p">,</span> <span class="s1">'r'</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">return</span> <span class="n">_builder_to_model_config</span><span class="p">(</span><span class="n">config</span><span class="p">)</span>
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<span class="k">def</span> <span class="nf">_builder_to_model_config</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="o">-></span> <span class="n">Tuple</span><span class="p">[</span><span class="n">ModelConfig</span><span class="p">,</span> <span class="nb">dict</span><span class="p">]:</span>
|
|
<span class="n">builder_config</span> <span class="o">=</span> <span class="n">config</span><span class="p">[</span><span class="s1">'builder_config'</span><span class="p">]</span>
|
|
<span class="n">model_name</span> <span class="o">=</span> <span class="n">builder_config</span><span class="p">[</span><span class="s1">'name'</span><span class="p">]</span>
|
|
<span class="n">dtype</span> <span class="o">=</span> <span class="n">builder_config</span><span class="p">[</span><span class="s1">'precision'</span><span class="p">]</span>
|
|
<span class="n">tp_size</span> <span class="o">=</span> <span class="n">builder_config</span><span class="p">[</span><span class="s1">'tensor_parallel'</span><span class="p">]</span>
|
|
<span class="n">pp_size</span> <span class="o">=</span> <span class="n">builder_config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'pipeline_parallel'</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
|
|
<span class="n">world_size</span> <span class="o">=</span> <span class="n">tp_size</span> <span class="o">*</span> <span class="n">pp_size</span>
|
|
<span class="k">assert</span> <span class="n">world_size</span> <span class="o">==</span> <span class="n">mpi_world_size</span><span class="p">(),</span> \
|
|
<span class="sa">f</span><span class="s1">'Engine world size (</span><span class="si">{</span><span class="n">tp_size</span><span class="si">}</span><span class="s1"> * </span><span class="si">{</span><span class="n">pp_size</span><span class="si">}</span><span class="s1">) != Runtime world size (</span><span class="si">{</span><span class="n">mpi_world_size</span><span class="p">()</span><span class="si">}</span><span class="s1">)'</span>
|
|
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|
<span class="n">num_heads</span> <span class="o">=</span> <span class="n">builder_config</span><span class="p">[</span><span class="s1">'num_heads'</span><span class="p">]</span>
|
|
<span class="k">assert</span> <span class="n">num_heads</span> <span class="o">%</span> <span class="n">tp_size</span> <span class="o">==</span> <span class="mi">0</span><span class="p">,</span> \
|
|
<span class="sa">f</span><span class="s2">"The number of heads (</span><span class="si">{</span><span class="n">num_heads</span><span class="si">}</span><span class="s2">) is not a multiple of tp_size (</span><span class="si">{</span><span class="n">tp_size</span><span class="si">}</span><span class="s2">)"</span>
|
|
<span class="n">num_kv_heads</span> <span class="o">=</span> <span class="n">builder_config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'num_kv_heads'</span><span class="p">,</span> <span class="n">num_heads</span><span class="p">)</span>
|
|
<span class="c1"># TODO: multi_query_mode should be removed</span>
|
|
<span class="n">multi_query_mode</span> <span class="o">=</span> <span class="n">builder_config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'multi_query_mode'</span><span class="p">,</span> <span class="kc">False</span><span class="p">)</span>
|
|
<span class="k">if</span> <span class="n">multi_query_mode</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">"`multi_query_mode` config is deprecated. Please rebuild the engine."</span>
|
|
<span class="p">)</span>
|
|
<span class="c1"># num_kv_heads, if exists in config, should override multi_query_mode</span>
|
|
<span class="k">if</span> <span class="n">multi_query_mode</span> <span class="ow">and</span> <span class="p">(</span><span class="s1">'num_kv_heads'</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">builder_config</span><span class="p">):</span>
|
|
<span class="n">num_kv_heads</span> <span class="o">=</span> <span class="mi">1</span>
|
|
<span class="n">num_heads</span> <span class="o">=</span> <span class="n">num_heads</span> <span class="o">//</span> <span class="n">tp_size</span>
|
|
<span class="n">num_kv_heads</span> <span class="o">=</span> <span class="p">(</span><span class="n">num_kv_heads</span> <span class="o">+</span> <span class="n">tp_size</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span> <span class="o">//</span> <span class="n">tp_size</span>
|
|
<span class="n">head_size</span> <span class="o">=</span> <span class="n">builder_config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'head_size'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
|
|
|
<span class="n">hidden_size</span> <span class="o">=</span> <span class="n">builder_config</span><span class="p">[</span><span class="s1">'hidden_size'</span><span class="p">]</span> <span class="o">//</span> <span class="n">tp_size</span>
|
|
<span class="n">vocab_size</span> <span class="o">=</span> <span class="n">builder_config</span><span class="p">[</span><span class="s1">'vocab_size'</span><span class="p">]</span>
|
|
<span class="n">num_layers</span> <span class="o">=</span> <span class="n">builder_config</span><span class="p">[</span><span class="s1">'num_layers'</span><span class="p">]</span>
|
|
<span class="n">max_batch_size</span> <span class="o">=</span> <span class="n">builder_config</span><span class="p">[</span><span class="s1">'max_batch_size'</span><span class="p">]</span>
|
|
<span class="n">max_beam_width</span> <span class="o">=</span> <span class="n">builder_config</span><span class="p">[</span><span class="s1">'max_beam_width'</span><span class="p">]</span>
|
|
|
|
<span class="n">cross_attention</span> <span class="o">=</span> <span class="n">builder_config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'cross_attention'</span><span class="p">,</span> <span class="kc">False</span><span class="p">)</span>
|
|
<span class="n">has_position_embedding</span> <span class="o">=</span> <span class="n">builder_config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'has_position_embedding'</span><span class="p">,</span> <span class="kc">True</span><span class="p">)</span>
|
|
<span class="n">has_token_type_embedding</span> <span class="o">=</span> <span class="n">builder_config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'has_token_type_embedding'</span><span class="p">,</span>
|
|
<span class="kc">False</span><span class="p">)</span>
|
|
<span class="n">gather_context_logits</span> <span class="o">=</span> <span class="n">builder_config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'gather_context_logits'</span><span class="p">,</span> <span class="kc">False</span><span class="p">)</span>
|
|
<span class="n">gather_generation_logits</span> <span class="o">=</span> <span class="n">builder_config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'gather_generation_logits'</span><span class="p">,</span>
|
|
<span class="kc">False</span><span class="p">)</span>
|
|
<span class="n">max_prompt_embedding_table_size</span> <span class="o">=</span> <span class="n">builder_config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span>
|
|
<span class="s1">'max_prompt_embedding_table_size'</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
|
|
<span class="n">quant_mode</span> <span class="o">=</span> <span class="n">QuantMode</span><span class="p">(</span><span class="n">builder_config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'quant_mode'</span><span class="p">,</span> <span class="mi">0</span><span class="p">))</span>
|
|
<span class="n">lora_target_modules</span> <span class="o">=</span> <span class="n">builder_config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'lora_target_modules'</span><span class="p">)</span>
|
|
<span class="n">lora_trtllm_modules_to_hf_modules</span> <span class="o">=</span> <span class="n">builder_config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span>
|
|
<span class="s1">'trtllm_modules_to_hf_modules'</span><span class="p">)</span>
|
|
<span class="n">max_medusa_token_len</span> <span class="o">=</span> <span class="n">builder_config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'max_draft_len'</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
|
|
<span class="n">num_medusa_heads</span> <span class="o">=</span> <span class="n">builder_config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'num_medusa_heads'</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
|
|
|
|
<span class="n">plugin_config</span> <span class="o">=</span> <span class="n">config</span><span class="p">[</span><span class="s1">'plugin_config'</span><span class="p">]</span>
|
|
<span class="n">use_gpt_attention_plugin</span> <span class="o">=</span> <span class="nb">bool</span><span class="p">(</span><span class="n">plugin_config</span><span class="p">[</span><span class="s1">'gpt_attention_plugin'</span><span class="p">])</span>
|
|
<span class="n">mamba_conv1d_plugin</span> <span class="o">=</span> <span class="nb">bool</span><span class="p">(</span><span class="n">plugin_config</span><span class="p">[</span><span class="s1">'mamba_conv1d_plugin'</span><span class="p">])</span>
|
|
<span class="n">remove_input_padding</span> <span class="o">=</span> <span class="n">plugin_config</span><span class="p">[</span><span class="s1">'remove_input_padding'</span><span class="p">]</span>
|
|
<span class="n">paged_kv_cache</span> <span class="o">=</span> <span class="n">plugin_config</span><span class="p">[</span><span class="s1">'paged_kv_cache'</span><span class="p">]</span>
|
|
<span class="n">paged_state</span> <span class="o">=</span> <span class="n">plugin_config</span><span class="p">[</span><span class="s1">'paged_state'</span><span class="p">]</span>
|
|
<span class="n">tokens_per_block</span> <span class="o">=</span> <span class="n">plugin_config</span><span class="p">[</span><span class="s1">'tokens_per_block'</span><span class="p">]</span>
|
|
<span class="n">use_custom_all_reduce</span> <span class="o">=</span> <span class="n">plugin_config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'use_custom_all_reduce'</span><span class="p">,</span> <span class="kc">False</span><span class="p">)</span>
|
|
<span class="n">lora_plugin</span> <span class="o">=</span> <span class="n">plugin_config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'lora_plugin'</span><span class="p">)</span>
|
|
<span class="n">use_context_fmha_for_generation</span> <span class="o">=</span> <span class="n">plugin_config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span>
|
|
<span class="s1">'use_context_fmha_for_generation'</span><span class="p">)</span>
|
|
|
|
<span class="n">model_config</span> <span class="o">=</span> <span class="n">ModelConfig</span><span class="p">(</span>
|
|
<span class="n">max_batch_size</span><span class="o">=</span><span class="n">max_batch_size</span><span class="p">,</span>
|
|
<span class="n">max_beam_width</span><span class="o">=</span><span class="n">max_beam_width</span><span class="p">,</span>
|
|
<span class="n">vocab_size</span><span class="o">=</span><span class="n">vocab_size</span><span class="p">,</span>
|
|
<span class="n">num_layers</span><span class="o">=</span><span class="n">num_layers</span><span class="p">,</span>
|
|
<span class="n">num_heads</span><span class="o">=</span><span class="n">num_heads</span><span class="p">,</span>
|
|
<span class="n">num_kv_heads</span><span class="o">=</span><span class="n">num_kv_heads</span><span class="p">,</span>
|
|
<span class="n">hidden_size</span><span class="o">=</span><span class="n">hidden_size</span><span class="p">,</span>
|
|
<span class="n">head_size</span><span class="o">=</span><span class="n">head_size</span><span class="p">,</span>
|
|
<span class="n">gpt_attention_plugin</span><span class="o">=</span><span class="n">use_gpt_attention_plugin</span><span class="p">,</span>
|
|
<span class="n">mamba_conv1d_plugin</span><span class="o">=</span><span class="n">mamba_conv1d_plugin</span><span class="p">,</span>
|
|
<span class="n">remove_input_padding</span><span class="o">=</span><span class="n">remove_input_padding</span><span class="p">,</span>
|
|
<span class="n">model_name</span><span class="o">=</span><span class="n">model_name</span><span class="p">,</span>
|
|
<span class="n">paged_kv_cache</span><span class="o">=</span><span class="n">paged_kv_cache</span><span class="p">,</span>
|
|
<span class="n">paged_state</span><span class="o">=</span><span class="n">paged_state</span><span class="p">,</span>
|
|
<span class="n">cross_attention</span><span class="o">=</span><span class="n">cross_attention</span><span class="p">,</span>
|
|
<span class="n">has_position_embedding</span><span class="o">=</span><span class="n">has_position_embedding</span><span class="p">,</span>
|
|
<span class="n">has_token_type_embedding</span><span class="o">=</span><span class="n">has_token_type_embedding</span><span class="p">,</span>
|
|
<span class="n">tokens_per_block</span><span class="o">=</span><span class="n">tokens_per_block</span><span class="p">,</span>
|
|
<span class="n">max_prompt_embedding_table_size</span><span class="o">=</span><span class="n">max_prompt_embedding_table_size</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="o">=</span><span class="n">quant_mode</span><span class="p">,</span>
|
|
<span class="n">gather_context_logits</span><span class="o">=</span><span class="n">gather_context_logits</span><span class="p">,</span>
|
|
<span class="n">gather_generation_logits</span><span class="o">=</span><span class="n">gather_generation_logits</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">use_custom_all_reduce</span><span class="o">=</span><span class="n">use_custom_all_reduce</span><span class="p">,</span>
|
|
<span class="n">lora_plugin</span><span class="o">=</span><span class="n">lora_plugin</span><span class="p">,</span>
|
|
<span class="n">lora_target_modules</span><span class="o">=</span><span class="n">lora_target_modules</span><span class="p">,</span>
|
|
<span class="n">use_context_fmha_for_generation</span><span class="o">=</span><span class="n">use_context_fmha_for_generation</span><span class="p">,</span>
|
|
<span class="n">trtllm_modules_to_hf_modules</span><span class="o">=</span><span class="n">lora_trtllm_modules_to_hf_modules</span><span class="p">,</span>
|
|
<span class="n">num_medusa_heads</span><span class="o">=</span><span class="n">num_medusa_heads</span><span class="p">,</span>
|
|
<span class="n">max_medusa_tokens</span><span class="o">=</span><span class="n">max_medusa_token_len</span><span class="p">,</span>
|
|
<span class="p">)</span>
|
|
|
|
<span class="n">other_config</span> <span class="o">=</span> <span class="p">{</span>
|
|
<span class="s1">'world_size'</span><span class="p">:</span> <span class="n">world_size</span><span class="p">,</span>
|
|
<span class="s1">'tp_size'</span><span class="p">:</span> <span class="n">tp_size</span><span class="p">,</span>
|
|
<span class="s1">'pp_size'</span><span class="p">:</span> <span class="n">pp_size</span><span class="p">,</span>
|
|
<span class="s1">'max_batch_size'</span><span class="p">:</span> <span class="n">builder_config</span><span class="p">[</span><span class="s1">'max_batch_size'</span><span class="p">],</span>
|
|
<span class="s1">'max_input_len'</span><span class="p">:</span> <span class="n">builder_config</span><span class="p">[</span><span class="s1">'max_input_len'</span><span class="p">],</span>
|
|
<span class="s1">'max_output_len'</span><span class="p">:</span> <span class="n">builder_config</span><span class="p">[</span><span class="s1">'max_output_len'</span><span class="p">],</span>
|
|
<span class="s1">'max_beam_width'</span><span class="p">:</span> <span class="n">builder_config</span><span class="p">[</span><span class="s1">'max_beam_width'</span><span class="p">]</span>
|
|
<span class="p">}</span>
|
|
<span class="k">return</span> <span class="n">model_config</span><span class="p">,</span> <span class="n">other_config</span>
|
|
|
|
|
|
<span class="k">class</span> <span class="nc">ModelRunnerMixin</span><span class="p">:</span>
|
|
|
|
<span class="k">def</span> <span class="nf">_check_inputs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">batch_input_ids</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">],</span>
|
|
<span class="n">sampling_config</span><span class="p">:</span> <span class="n">SamplingConfig</span><span class="p">):</span>
|
|
<span class="n">batch_size</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">batch_input_ids</span><span class="p">)</span>
|
|
<span class="k">if</span> <span class="n">batch_size</span> <span class="o">></span> <span class="bp">self</span><span class="o">.</span><span class="n">max_batch_size</span><span class="p">:</span>
|
|
<span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span>
|
|
<span class="sa">f</span><span class="s2">"Input batch size (</span><span class="si">{</span><span class="n">batch_size</span><span class="si">}</span><span class="s2">) exceeds the engine or specified limit (</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">max_batch_size</span><span class="si">}</span><span class="s2">)"</span>
|
|
<span class="p">)</span>
|
|
<span class="n">input_lengths</span> <span class="o">=</span> <span class="p">[</span><span class="n">x</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">batch_input_ids</span><span class="p">]</span>
|
|
<span class="n">max_length</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="n">input_lengths</span><span class="p">)</span>
|
|
<span class="k">if</span> <span class="n">max_length</span> <span class="o">></span> <span class="bp">self</span><span class="o">.</span><span class="n">max_input_len</span><span class="p">:</span>
|
|
<span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span>
|
|
<span class="sa">f</span><span class="s2">"Maximum input length (</span><span class="si">{</span><span class="n">max_length</span><span class="si">}</span><span class="s2">) exceeds the engine or specified limit (</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">max_input_len</span><span class="si">}</span><span class="s2">)"</span>
|
|
<span class="p">)</span>
|
|
<span class="k">if</span> <span class="n">max_length</span> <span class="o">+</span> <span class="n">sampling_config</span><span class="o">.</span><span class="n">max_new_tokens</span> <span class="o">></span> <span class="bp">self</span><span class="o">.</span><span class="n">max_seq_len</span><span class="p">:</span>
|
|
<span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span>
|
|
<span class="sa">f</span><span class="s2">"Maximum input length (</span><span class="si">{</span><span class="n">max_length</span><span class="si">}</span><span class="s2">) + maximum new tokens (</span><span class="si">{</span><span class="n">sampling_config</span><span class="o">.</span><span class="n">max_new_tokens</span><span class="si">}</span><span class="s2">) exceeds the engine or specified limit (</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">max_seq_len</span><span class="si">}</span><span class="s2">)"</span>
|
|
<span class="p">)</span>
|
|
<span class="k">if</span> <span class="n">sampling_config</span><span class="o">.</span><span class="n">num_beams</span> <span class="o">></span> <span class="bp">self</span><span class="o">.</span><span class="n">max_beam_width</span><span class="p">:</span>
|
|
<span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span>
|
|
<span class="sa">f</span><span class="s2">"Num beams (</span><span class="si">{</span><span class="n">sampling_config</span><span class="o">.</span><span class="n">num_beams</span><span class="si">}</span><span class="s2">) exceeds the engine or specified limit (</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">max_beam_width</span><span class="si">}</span><span class="s2">)"</span>
|
|
<span class="p">)</span>
|
|
|
|
<span class="k">def</span> <span class="nf">_prepare_inputs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">batch_input_ids</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">],</span>
|
|
<span class="n">pad_id</span><span class="p">:</span> <span class="nb">int</span><span class="p">)</span> <span class="o">-></span> <span class="n">Tuple</span><span class="p">[</span><span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">]:</span>
|
|
<span class="c1"># Cast to int32</span>
|
|
<span class="n">batch_input_ids</span> <span class="o">=</span> <span class="p">[</span><span class="n">x</span><span class="o">.</span><span class="n">type</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">int32</span><span class="p">)</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">batch_input_ids</span><span class="p">]</span>
|
|
<span class="n">input_lengths</span> <span class="o">=</span> <span class="p">[</span><span class="n">x</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">batch_input_ids</span><span class="p">]</span>
|
|
<span class="n">max_length</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="n">input_lengths</span><span class="p">)</span>
|
|
|
|
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">remove_input_padding</span><span class="p">:</span>
|
|
<span class="n">batch_input_ids</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">concat</span><span class="p">(</span><span class="n">batch_input_ids</span><span class="p">)</span>
|
|
<span class="k">else</span><span class="p">:</span>
|
|
<span class="c1"># Right padding for trt-llm</span>
|
|
<span class="n">paddings</span> <span class="o">=</span> <span class="p">[</span>
|
|
<span class="n">torch</span><span class="o">.</span><span class="n">ones</span><span class="p">(</span><span class="n">max_length</span> <span class="o">-</span> <span class="n">l</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">int32</span><span class="p">)</span> <span class="o">*</span> <span class="n">pad_id</span>
|
|
<span class="k">for</span> <span class="n">l</span> <span class="ow">in</span> <span class="n">input_lengths</span>
|
|
<span class="p">]</span>
|
|
<span class="n">batch_input_ids</span> <span class="o">=</span> <span class="p">[</span>
|
|
<span class="n">torch</span><span class="o">.</span><span class="n">cat</span><span class="p">([</span><span class="n">x</span><span class="p">,</span> <span class="n">pad</span><span class="p">])</span> <span class="k">for</span> <span class="n">x</span><span class="p">,</span> <span class="n">pad</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">batch_input_ids</span><span class="p">,</span> <span class="n">paddings</span><span class="p">)</span>
|
|
<span class="p">]</span>
|
|
<span class="n">batch_input_ids</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">stack</span><span class="p">(</span><span class="n">batch_input_ids</span><span class="p">)</span>
|
|
<span class="n">input_lengths</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">(</span><span class="n">input_lengths</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">int32</span><span class="p">)</span>
|
|
<span class="k">return</span> <span class="n">batch_input_ids</span><span class="p">,</span> <span class="n">input_lengths</span>
|
|
|
|
<span class="k">def</span> <span class="nf">_prepare_outputs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">outputs</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="n">input_lengths</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">)</span> <span class="o">-></span> <span class="nb">dict</span><span class="p">:</span>
|
|
<span class="k">if</span> <span class="n">outputs</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
|
<span class="n">batch_size</span> <span class="o">=</span> <span class="n">input_lengths</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
|
|
<span class="k">if</span> <span class="s1">'context_logits'</span> <span class="ow">in</span> <span class="n">outputs</span><span class="p">:</span>
|
|
<span class="n">context_logits</span> <span class="o">=</span> <span class="n">outputs</span><span class="p">[</span><span class="s1">'context_logits'</span><span class="p">]</span>
|
|
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">remove_input_padding</span><span class="p">:</span>
|
|
<span class="n">context_logits</span> <span class="o">=</span> <span class="n">context_logits</span><span class="o">.</span><span class="n">flatten</span><span class="p">(</span><span class="n">end_dim</span><span class="o">=-</span><span class="mi">2</span><span class="p">)</span>
|
|
|
|
<span class="n">seg_points</span> <span class="o">=</span> <span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="n">input_lengths</span><span class="o">.</span><span class="n">cumsum</span><span class="p">(</span><span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
|
|
<span class="n">context_logits</span> <span class="o">=</span> <span class="p">[</span>
|
|
<span class="n">context_logits</span><span class="p">[</span><span class="n">s</span><span class="p">:</span><span class="n">e</span><span class="p">]</span>
|
|
<span class="k">for</span> <span class="n">s</span><span class="p">,</span> <span class="n">e</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">seg_points</span><span class="p">[:</span><span class="o">-</span><span class="mi">1</span><span class="p">],</span> <span class="n">seg_points</span><span class="p">[</span><span class="mi">1</span><span class="p">:])</span>
|
|
<span class="p">]</span>
|
|
<span class="k">else</span><span class="p">:</span>
|
|
<span class="n">context_logits</span> <span class="o">=</span> <span class="p">[</span>
|
|
<span class="n">context_logits</span><span class="p">[</span><span class="n">bidx</span><span class="p">,</span> <span class="p">:</span><span class="n">input_lengths</span><span class="p">[</span><span class="n">bidx</span><span class="p">]]</span>
|
|
<span class="k">for</span> <span class="n">bidx</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">batch_size</span><span class="p">)</span>
|
|
<span class="p">]</span>
|
|
<span class="n">outputs</span><span class="p">[</span><span class="s1">'context_logits'</span><span class="p">]</span> <span class="o">=</span> <span class="n">context_logits</span>
|
|
|
|
<span class="k">if</span> <span class="s1">'generation_logits'</span> <span class="ow">in</span> <span class="n">outputs</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span>
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">session</span><span class="p">,</span> <span class="n">GenerationSession</span><span class="p">):</span>
|
|
<span class="n">generation_logits</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">stack</span><span class="p">(</span><span class="n">outputs</span><span class="p">[</span><span class="s1">'generation_logits'</span><span class="p">],</span>
|
|
<span class="n">dim</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
|
|
<span class="n">batch_x_beam</span><span class="p">,</span> <span class="n">max_gen_len</span><span class="p">,</span> <span class="n">voc_size</span> <span class="o">=</span> <span class="n">generation_logits</span><span class="o">.</span><span class="n">size</span><span class="p">()</span>
|
|
<span class="n">num_beams</span> <span class="o">=</span> <span class="n">batch_x_beam</span> <span class="o">//</span> <span class="n">batch_size</span>
|
|
<span class="n">generation_logits</span> <span class="o">=</span> <span class="n">generation_logits</span><span class="o">.</span><span class="n">view</span><span class="p">(</span>
|
|
<span class="n">batch_size</span><span class="p">,</span> <span class="n">num_beams</span><span class="p">,</span> <span class="n">max_gen_len</span><span class="p">,</span> <span class="n">voc_size</span><span class="p">)</span>
|
|
<span class="n">outputs</span><span class="p">[</span><span class="s1">'generation_logits'</span><span class="p">]</span> <span class="o">=</span> <span class="n">generation_logits</span>
|
|
|
|
<span class="k">return</span> <span class="n">outputs</span>
|
|
|
|
<span class="k">def</span> <span class="nf">_prepare_ptuning</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">prompt_table_path</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">tasks</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span>
|
|
<span class="n">batch_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">max_prompt_embedding_table_size</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
|
|
<span class="k">return</span> <span class="p">{}</span>
|
|
|
|
<span class="k">if</span> <span class="n">prompt_table_path</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
|
<span class="n">prompt_table</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">from_numpy</span><span class="p">(</span>
|
|
<span class="n">np</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">prompt_table_path</span><span class="p">))</span><span class="o">.</span><span class="n">to</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">dtype</span><span class="p">)</span>
|
|
<span class="n">_</span><span class="p">,</span> <span class="n">task_vocab_size</span><span class="p">,</span> <span class="n">hidden_size</span> <span class="o">=</span> <span class="n">prompt_table</span><span class="o">.</span><span class="n">size</span><span class="p">()</span>
|
|
<span class="n">task_vocab_size</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">([</span><span class="n">task_vocab_size</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">int32</span><span class="p">)</span>
|
|
<span class="n">prompt_table</span> <span class="o">=</span> <span class="n">prompt_table</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="n">hidden_size</span><span class="p">)</span>
|
|
<span class="k">else</span><span class="p">:</span>
|
|
<span class="n">prompt_table</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">empty</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">hidden_size</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">dtype</span><span class="p">)</span>
|
|
<span class="n">task_vocab_size</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">zeros</span><span class="p">([</span><span class="mi">1</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">int32</span><span class="p">)</span>
|
|
|
|
<span class="k">if</span> <span class="n">tasks</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
|
<span class="n">tasks</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">([</span><span class="nb">int</span><span class="p">(</span><span class="n">t</span><span class="p">)</span> <span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">tasks</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">','</span><span class="p">)],</span>
|
|
<span class="n">dtype</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">int32</span><span class="p">)</span>
|
|
<span class="k">assert</span> <span class="n">tasks</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> <span class="o">==</span> <span class="n">batch_size</span><span class="p">,</span> \
|
|
<span class="sa">f</span><span class="s2">"Number of supplied tasks (</span><span class="si">{</span><span class="n">tasks</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span><span class="si">}</span><span class="s2">) must match input batch size (</span><span class="si">{</span><span class="n">batch_size</span><span class="si">}</span><span class="s2">)"</span>
|
|
<span class="k">else</span><span class="p">:</span>
|
|
<span class="n">tasks</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">zeros</span><span class="p">([</span><span class="n">batch_size</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">int32</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">session</span><span class="p">,</span> <span class="n">GenerationSession</span><span class="p">):</span>
|
|
<span class="k">return</span> <span class="p">{</span>
|
|
<span class="s1">'prompt_embedding_table'</span><span class="p">:</span> <span class="n">prompt_table</span><span class="o">.</span><span class="n">cuda</span><span class="p">(),</span>
|
|
<span class="s1">'tasks'</span><span class="p">:</span> <span class="n">tasks</span><span class="o">.</span><span class="n">cuda</span><span class="p">(),</span>
|
|
<span class="s1">'prompt_vocab_size'</span><span class="p">:</span> <span class="n">task_vocab_size</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
|
|
<span class="p">}</span>
|
|
<span class="k">else</span><span class="p">:</span>
|
|
<span class="k">return</span> <span class="p">{</span>
|
|
<span class="s1">'embedding_table'</span><span class="p">:</span> <span class="n">prompt_table</span><span class="o">.</span><span class="n">cuda</span><span class="p">(),</span>
|
|
<span class="s1">'tasks'</span><span class="p">:</span> <span class="n">tasks</span><span class="o">.</span><span class="n">cuda</span><span class="p">(),</span>
|
|
<span class="s1">'vocab_size'</span><span class="p">:</span> <span class="n">task_vocab_size</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
|
|
<span class="p">}</span>
|
|
|
|
|
|
<div class="viewcode-block" id="ModelRunner">
|
|
<a class="viewcode-back" href="../../../python-api/tensorrt_llm.runtime.html#tensorrt_llm.runtime.ModelRunner">[docs]</a>
|
|
<span class="k">class</span> <span class="nc">ModelRunner</span><span class="p">(</span><span class="n">ModelRunnerMixin</span><span class="p">):</span>
|
|
<span class="w"> </span><span class="sd">"""</span>
|
|
<span class="sd"> An interface class that wraps GenerationSession and provides generation methods.</span>
|
|
<span class="sd"> """</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">session</span><span class="p">:</span> <span class="n">GenerationSession</span><span class="p">,</span>
|
|
<span class="n">max_batch_size</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
|
|
<span class="n">max_input_len</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
|
|
<span class="n">max_seq_len</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
|
|
<span class="n">max_beam_width</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span>
|
|
<span class="n">lora_manager</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">LoraManager</span><span class="p">]</span> <span class="o">=</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="w"> </span><span class="sd">"""</span>
|
|
<span class="sd"> Create a ModelRunner instance.</span>
|
|
<span class="sd"> You are recommended to use the from_dir method to load the engine and create a ModelRunner instance.</span>
|
|
|
|
<span class="sd"> Args:</span>
|
|
<span class="sd"> session (GenerationSession):</span>
|
|
<span class="sd"> The TensorRT session created from an engine.</span>
|
|
<span class="sd"> max_batch_size (int):</span>
|
|
<span class="sd"> The maximum batch size allowed for the input.</span>
|
|
<span class="sd"> max_input_len (int):</span>
|
|
<span class="sd"> The maximum input length allowed for the input.</span>
|
|
<span class="sd"> max_seq_len (int):</span>
|
|
<span class="sd"> The maximum sequence length (input + new tokens).</span>
|
|
<span class="sd"> max_beam_width (int):</span>
|
|
<span class="sd"> The maximum beam width.</span>
|
|
<span class="sd"> lora_manager (LoraManager):</span>
|
|
<span class="sd"> The LoRA manager to handle LoRA weights.</span>
|
|
<span class="sd"> """</span>
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">session</span> <span class="o">=</span> <span class="n">session</span>
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">max_batch_size</span> <span class="o">=</span> <span class="n">max_batch_size</span>
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">max_input_len</span> <span class="o">=</span> <span class="n">max_input_len</span>
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">max_seq_len</span> <span class="o">=</span> <span class="n">max_seq_len</span>
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">max_beam_width</span> <span class="o">=</span> <span class="n">max_beam_width</span>
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">lora_manager</span> <span class="o">=</span> <span class="n">lora_manager</span>
|
|
|
|
<div class="viewcode-block" id="ModelRunner.from_engine">
|
|
<a class="viewcode-back" href="../../../python-api/tensorrt_llm.runtime.html#tensorrt_llm.runtime.ModelRunner.from_engine">[docs]</a>
|
|
<span class="nd">@classmethod</span>
|
|
<span class="k">def</span> <span class="nf">from_engine</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span>
|
|
<span class="n">engine</span><span class="p">:</span> <span class="n">Engine</span><span class="p">,</span>
|
|
<span class="n">lora_dir</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">str</span><span class="p">]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
|
|
<span class="n">rank</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">0</span><span class="p">,</span>
|
|
<span class="n">debug_mode</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
|
|
<span class="n">lora_ckpt_source</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">"hf"</span><span class="p">,</span>
|
|
<span class="n">medusa_choices</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="p">,</span>
|
|
<span class="n">stream</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">Stream</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-></span> <span class="s1">'ModelRunner'</span><span class="p">:</span>
|
|
<span class="n">pretrained_config</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="n">build_config</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">build_config</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">num_heads</span> <span class="o">=</span> <span class="n">pretrained_config</span><span class="o">.</span><span class="n">num_attention_heads</span> <span class="o">//</span> <span class="n">tp_size</span>
|
|
<span class="n">num_kv_heads</span> <span class="o">=</span> <span class="n">pretrained_config</span><span class="o">.</span><span class="n">num_key_value_heads</span>
|
|
<span class="n">num_kv_heads</span> <span class="o">=</span> <span class="p">(</span><span class="n">num_kv_heads</span> <span class="o">+</span> <span class="n">tp_size</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span> <span class="o">//</span> <span class="n">tp_size</span>
|
|
<span class="n">hidden_size</span> <span class="o">=</span> <span class="n">pretrained_config</span><span class="o">.</span><span class="n">hidden_size</span> <span class="o">//</span> <span class="n">tp_size</span>
|
|
<span class="n">head_size</span> <span class="o">=</span> <span class="n">pretrained_config</span><span class="o">.</span><span class="n">head_size</span>
|
|
|
|
<span class="k">if</span> <span class="n">pretrained_config</span><span class="o">.</span><span class="n">architecture</span> <span class="o">==</span> <span class="s1">'MambaLMHeadModel'</span><span class="p">:</span>
|
|
<span class="n">mamba_d_state</span> <span class="o">=</span> <span class="n">pretrained_config</span><span class="o">.</span><span class="n">ssm_cfg</span><span class="p">[</span><span class="s1">'d_state'</span><span class="p">]</span>
|
|
<span class="n">mamba_expand</span> <span class="o">=</span> <span class="n">pretrained_config</span><span class="o">.</span><span class="n">ssm_cfg</span><span class="p">[</span><span class="s1">'expand'</span><span class="p">]</span>
|
|
<span class="n">mamba_d_conv</span> <span class="o">=</span> <span class="n">pretrained_config</span><span class="o">.</span><span class="n">ssm_cfg</span><span class="p">[</span><span class="s1">'d_conv'</span><span class="p">]</span>
|
|
<span class="k">else</span><span class="p">:</span>
|
|
<span class="n">mamba_d_state</span><span class="p">,</span> <span class="n">mamba_expand</span><span class="p">,</span> <span class="n">mamba_d_conv</span> <span class="o">=</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">0</span>
|
|
|
|
<span class="n">model_config</span> <span class="o">=</span> <span class="n">ModelConfig</span><span class="p">(</span>
|
|
<span class="n">max_batch_size</span><span class="o">=</span><span class="n">build_config</span><span class="o">.</span><span class="n">max_batch_size</span><span class="p">,</span>
|
|
<span class="n">max_beam_width</span><span class="o">=</span><span class="n">build_config</span><span class="o">.</span><span class="n">max_beam_width</span><span class="p">,</span>
|
|
<span class="n">vocab_size</span><span class="o">=</span><span class="n">pretrained_config</span><span class="o">.</span><span class="n">vocab_size</span><span class="p">,</span>
|
|
<span class="n">num_layers</span><span class="o">=</span><span class="n">pretrained_config</span><span class="o">.</span><span class="n">num_hidden_layers</span><span class="p">,</span>
|
|
<span class="n">num_heads</span><span class="o">=</span><span class="n">num_heads</span><span class="p">,</span>
|
|
<span class="n">num_kv_heads</span><span class="o">=</span><span class="n">num_kv_heads</span><span class="p">,</span>
|
|
<span class="n">hidden_size</span><span class="o">=</span><span class="n">hidden_size</span><span class="p">,</span>
|
|
<span class="n">head_size</span><span class="o">=</span><span class="n">head_size</span><span class="p">,</span>
|
|
<span class="n">gpt_attention_plugin</span><span class="o">=</span><span class="nb">bool</span><span class="p">(</span>
|
|
<span class="n">build_config</span><span class="o">.</span><span class="n">plugin_config</span><span class="o">.</span><span class="n">gpt_attention_plugin</span><span class="p">),</span>
|
|
<span class="n">mamba_conv1d_plugin</span><span class="o">=</span><span class="nb">bool</span><span class="p">(</span>
|
|
<span class="n">build_config</span><span class="o">.</span><span class="n">plugin_config</span><span class="o">.</span><span class="n">mamba_conv1d_plugin</span><span class="p">),</span>
|
|
<span class="n">remove_input_padding</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">remove_input_padding</span><span class="p">,</span>
|
|
<span class="n">paged_kv_cache</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">paged_kv_cache</span><span class="p">,</span>
|
|
<span class="n">paged_state</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">paged_state</span><span class="p">,</span>
|
|
<span class="n">tokens_per_block</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">tokens_per_block</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="o">=</span><span class="n">pretrained_config</span><span class="o">.</span><span class="n">quant_mode</span><span class="p">,</span>
|
|
<span class="n">gather_context_logits</span><span class="o">=</span><span class="n">build_config</span><span class="o">.</span><span class="n">gather_context_logits</span><span class="p">,</span>
|
|
<span class="n">gather_generation_logits</span><span class="o">=</span><span class="n">build_config</span><span class="o">.</span><span class="n">gather_generation_logits</span><span class="p">,</span>
|
|
<span class="n">dtype</span><span class="o">=</span><span class="n">pretrained_config</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
|
|
<span class="n">max_prompt_embedding_table_size</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="p">,</span>
|
|
<span class="n">mamba_d_state</span><span class="o">=</span><span class="n">mamba_d_state</span><span class="p">,</span>
|
|
<span class="n">mamba_expand</span><span class="o">=</span><span class="n">mamba_expand</span><span class="p">,</span>
|
|
<span class="n">mamba_d_conv</span><span class="o">=</span><span class="n">mamba_d_conv</span><span class="p">,</span>
|
|
<span class="n">lora_plugin</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="p">,</span>
|
|
<span class="n">lora_target_modules</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">lora_target_modules</span><span class="p">,</span>
|
|
<span class="n">trtllm_modules_to_hf_modules</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">trtllm_modules_to_hf_modules</span><span class="p">,</span>
|
|
<span class="n">max_medusa_tokens</span><span class="o">=</span><span class="n">pretrained_config</span><span class="o">.</span><span class="n">max_draft_len</span> <span class="k">if</span> <span class="nb">hasattr</span><span class="p">(</span>
|
|
<span class="n">pretrained_config</span><span class="p">,</span> <span class="s1">'max_draft_len'</span><span class="p">)</span> <span class="k">else</span> <span class="mi">0</span><span class="p">,</span>
|
|
<span class="n">num_medusa_heads</span><span class="o">=</span><span class="n">pretrained_config</span><span class="o">.</span><span class="n">num_medusa_heads</span> <span class="k">if</span> <span class="nb">hasattr</span><span class="p">(</span>
|
|
<span class="n">pretrained_config</span><span class="p">,</span> <span class="s1">'num_medusa_heads'</span><span class="p">)</span> <span class="k">else</span> <span class="mi">0</span><span class="p">,</span>
|
|
<span class="n">use_custom_all_reduce</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">use_custom_all_reduce</span><span class="p">,</span>
|
|
<span class="p">)</span>
|
|
<span class="n">max_batch_size</span> <span class="o">=</span> <span class="n">build_config</span><span class="o">.</span><span class="n">max_batch_size</span>
|
|
<span class="n">max_input_len</span> <span class="o">=</span> <span class="n">build_config</span><span class="o">.</span><span class="n">max_input_len</span>
|
|
<span class="n">max_output_len</span> <span class="o">=</span> <span class="n">build_config</span><span class="o">.</span><span class="n">max_output_len</span>
|
|
<span class="n">max_beam_width</span> <span class="o">=</span> <span class="n">build_config</span><span class="o">.</span><span class="n">max_beam_width</span>
|
|
<span class="k">if</span> <span class="n">pretrained_config</span><span class="o">.</span><span class="n">architecture</span> <span class="o">==</span> <span class="s1">'ChatGLMForCausalLM'</span> <span class="ow">and</span> <span class="n">pretrained_config</span><span class="o">.</span><span class="n">chatglm_version</span> <span class="ow">in</span> <span class="p">[</span>
|
|
<span class="s1">'glm'</span><span class="p">,</span> <span class="s1">'chatglm'</span>
|
|
<span class="p">]:</span>
|
|
<span class="n">session_cls</span> <span class="o">=</span> <span class="n">ChatGLMGenerationSession</span>
|
|
<span class="k">elif</span> <span class="n">pretrained_config</span><span class="o">.</span><span class="n">architecture</span> <span class="o">==</span> <span class="s1">'MambaLMHeadModel'</span><span class="p">:</span>
|
|
<span class="n">session_cls</span> <span class="o">=</span> <span class="n">MambaLMHeadModelGenerationSession</span>
|
|
<span class="k">else</span><span class="p">:</span>
|
|
<span class="n">session_cls</span> <span class="o">=</span> <span class="n">GenerationSession</span>
|
|
<span class="n">engine_buffer</span> <span class="o">=</span> <span class="n">engine</span><span class="o">.</span><span class="n">engine</span>
|
|
<span class="n">runtime_mapping</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="n">medusa_choices</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
|
<span class="k">assert</span> <span class="n">session_cls</span> <span class="o">==</span> <span class="n">GenerationSession</span><span class="p">,</span> <span class="s2">"Medusa is only supported by GenerationSession"</span>
|
|
|
|
<span class="k">assert</span> <span class="n">model_config</span><span class="o">.</span><span class="n">max_medusa_tokens</span> <span class="o">></span> <span class="mi">0</span><span class="p">,</span> \
|
|
<span class="s2">"medusa_chioce is specified but model_config.max_medusa_tokens is 0."</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="n">rank</span> <span class="o">%</span> <span class="n">runtime_mapping</span><span class="o">.</span><span class="n">gpus_per_node</span><span class="p">)</span>
|
|
<span class="n">session</span> <span class="o">=</span> <span class="n">session_cls</span><span class="p">(</span><span class="n">model_config</span><span class="p">,</span>
|
|
<span class="n">engine_buffer</span><span class="p">,</span>
|
|
<span class="n">runtime_mapping</span><span class="p">,</span>
|
|
<span class="n">debug_mode</span><span class="o">=</span><span class="n">debug_mode</span><span class="p">,</span>
|
|
<span class="n">stream</span><span class="o">=</span><span class="n">stream</span><span class="p">)</span>
|
|
|
|
<span class="k">if</span> <span class="n">session</span><span class="o">.</span><span class="n">use_lora_plugin</span><span class="p">:</span>
|
|
<span class="n">lora_manager</span> <span class="o">=</span> <span class="n">LoraManager</span><span class="p">()</span>
|
|
<span class="k">if</span> <span class="n">lora_dir</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
|
<span class="n">lora_manager</span><span class="o">.</span><span class="n">load_from_ckpt</span><span class="p">(</span><span class="n">model_dir</span><span class="o">=</span><span class="n">lora_dir</span><span class="p">,</span>
|
|
<span class="n">model_config</span><span class="o">=</span><span class="n">model_config</span><span class="p">,</span>
|
|
<span class="n">runtime_mapping</span><span class="o">=</span><span class="n">runtime_mapping</span><span class="p">,</span>
|
|
<span class="n">ckpt_source</span><span class="o">=</span><span class="n">lora_ckpt_source</span><span class="p">)</span>
|
|
<span class="k">else</span><span class="p">:</span>
|
|
<span class="n">lora_manager</span> <span class="o">=</span> <span class="kc">None</span>
|
|
|
|
<span class="k">return</span> <span class="bp">cls</span><span class="p">(</span><span class="n">session</span><span class="o">=</span><span class="n">session</span><span class="p">,</span>
|
|
<span class="n">max_batch_size</span><span class="o">=</span><span class="n">max_batch_size</span><span class="p">,</span>
|
|
<span class="n">max_input_len</span><span class="o">=</span><span class="n">max_input_len</span><span class="p">,</span>
|
|
<span class="n">max_seq_len</span><span class="o">=</span><span class="n">max_input_len</span> <span class="o">+</span> <span class="n">max_output_len</span><span class="p">,</span>
|
|
<span class="n">max_beam_width</span><span class="o">=</span><span class="n">max_beam_width</span><span class="p">,</span>
|
|
<span class="n">lora_manager</span><span class="o">=</span><span class="n">lora_manager</span><span class="p">)</span></div>
|
|
|
|
|
|
<div class="viewcode-block" id="ModelRunner.from_dir">
|
|
<a class="viewcode-back" href="../../../python-api/tensorrt_llm.runtime.html#tensorrt_llm.runtime.ModelRunner.from_dir">[docs]</a>
|
|
<span class="nd">@classmethod</span>
|
|
<span class="k">def</span> <span class="nf">from_dir</span><span class="p">(</span><span class="bp">cls</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="n">lora_dir</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">str</span><span class="p">]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
|
|
<span class="n">rank</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">0</span><span class="p">,</span>
|
|
<span class="n">debug_mode</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
|
|
<span class="n">lora_ckpt_source</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">"hf"</span><span class="p">,</span>
|
|
<span class="n">medusa_choices</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="p">,</span>
|
|
<span class="n">stream</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">Stream</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-></span> <span class="s1">'ModelRunner'</span><span class="p">:</span>
|
|
<span class="w"> </span><span class="sd">"""</span>
|
|
<span class="sd"> Create a ModelRunner instance from an engine directory.</span>
|
|
|
|
<span class="sd"> Args:</span>
|
|
<span class="sd"> engine_dir (str):</span>
|
|
<span class="sd"> The directory that contains the serialized engine files and config files.</span>
|
|
<span class="sd"> lora_dir (Optional[List[str]]):</span>
|
|
<span class="sd"> The directories that contain LoRA weights.</span>
|
|
<span class="sd"> rank (int):</span>
|
|
<span class="sd"> The runtime rank id.</span>
|
|
<span class="sd"> debug_mode (bool):</span>
|
|
<span class="sd"> Whether or not to turn on the debug mode.</span>
|
|
<span class="sd"> medusa_choices (List[List[int]]):</span>
|
|
<span class="sd"> Medusa choices to use when in Medusa decoding</span>
|
|
<span class="sd"> stream (torch.cuda.Stream):</span>
|
|
<span class="sd"> Stream to use.</span>
|
|
<span class="sd"> Returns:</span>
|
|
<span class="sd"> ModelRunner: An instance of ModelRunner.</span>
|
|
<span class="sd"> """</span>
|
|
<span class="n">engine_version</span> <span class="o">=</span> <span class="n">get_engine_version</span><span class="p">(</span><span class="n">engine_dir</span><span class="p">)</span>
|
|
<span class="n">profiler</span><span class="o">.</span><span class="n">start</span><span class="p">(</span><span class="s1">'load tensorrt_llm engine'</span><span class="p">)</span>
|
|
<span class="c1"># the old engine format</span>
|
|
<span class="k">if</span> <span class="n">engine_version</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
|
<span class="n">engine_dir</span> <span class="o">=</span> <span class="n">Path</span><span class="p">(</span><span class="n">engine_dir</span><span class="p">)</span>
|
|
<span class="n">config_path</span> <span class="o">=</span> <span class="n">engine_dir</span> <span class="o">/</span> <span class="s2">"config.json"</span>
|
|
<span class="n">model_config</span><span class="p">,</span> <span class="n">other_config</span> <span class="o">=</span> <span class="n">read_config</span><span class="p">(</span><span class="n">config_path</span><span class="p">)</span>
|
|
<span class="n">world_size</span> <span class="o">=</span> <span class="n">other_config</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'world_size'</span><span class="p">)</span>
|
|
<span class="n">tp_size</span> <span class="o">=</span> <span class="n">other_config</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'tp_size'</span><span class="p">)</span>
|
|
<span class="n">pp_size</span> <span class="o">=</span> <span class="n">other_config</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'pp_size'</span><span class="p">)</span>
|
|
<span class="n">max_batch_size</span> <span class="o">=</span> <span class="n">other_config</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'max_batch_size'</span><span class="p">)</span>
|
|
<span class="n">max_input_len</span> <span class="o">=</span> <span class="n">other_config</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'max_input_len'</span><span class="p">)</span>
|
|
<span class="n">max_output_len</span> <span class="o">=</span> <span class="n">other_config</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'max_output_len'</span><span class="p">)</span>
|
|
<span class="n">max_beam_width</span> <span class="o">=</span> <span class="n">other_config</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'max_beam_width'</span><span class="p">)</span>
|
|
<span class="n">runtime_mapping</span> <span class="o">=</span> <span class="n">Mapping</span><span class="p">(</span><span class="n">world_size</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">rank</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">engine_name</span> <span class="o">=</span> <span class="n">get_engine_name</span><span class="p">(</span><span class="n">model_config</span><span class="o">.</span><span class="n">model_name</span><span class="p">,</span>
|
|
<span class="n">model_config</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span> <span class="n">tp_size</span><span class="p">,</span> <span class="n">pp_size</span><span class="p">,</span>
|
|
<span class="n">rank</span><span class="p">)</span>
|
|
<span class="n">serialize_path</span> <span class="o">=</span> <span class="n">engine_dir</span> <span class="o">/</span> <span class="n">engine_name</span>
|
|
|
|
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">serialize_path</span><span class="p">,</span> <span class="s1">'rb'</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
|
|
<span class="n">engine_buffer</span> <span class="o">=</span> <span class="n">f</span><span class="o">.</span><span class="n">read</span><span class="p">()</span>
|
|
|
|
<span class="k">if</span> <span class="n">model_config</span><span class="o">.</span><span class="n">model_name</span> <span class="ow">in</span> <span class="p">(</span><span class="s1">'chatglm_6b'</span><span class="p">,</span> <span class="s1">'glm_10b'</span><span class="p">):</span>
|
|
<span class="n">session_cls</span> <span class="o">=</span> <span class="n">ChatGLMGenerationSession</span>
|
|
<span class="k">elif</span> <span class="n">model_config</span><span class="o">.</span><span class="n">model_name</span> <span class="o">==</span> <span class="s1">'qwen'</span><span class="p">:</span>
|
|
<span class="n">session_cls</span> <span class="o">=</span> <span class="n">QWenForCausalLMGenerationSession</span>
|
|
<span class="k">else</span><span class="p">:</span>
|
|
<span class="n">session_cls</span> <span class="o">=</span> <span class="n">GenerationSession</span>
|
|
|
|
<span class="k">if</span> <span class="n">medusa_choices</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
|
<span class="k">assert</span> <span class="n">session_cls</span> <span class="o">==</span> <span class="n">GenerationSession</span><span class="p">,</span> <span class="s2">"Medusa is only supported by GenerationSession"</span>
|
|
|
|
<span class="k">assert</span> <span class="n">model_config</span><span class="o">.</span><span class="n">max_medusa_tokens</span> <span class="o">></span> <span class="mi">0</span><span class="p">,</span> \
|
|
<span class="s2">"medusa_chioce is specified but model_config.max_medusa_tokens is 0."</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="n">rank</span> <span class="o">%</span> <span class="n">runtime_mapping</span><span class="o">.</span><span class="n">gpus_per_node</span><span class="p">)</span>
|
|
<span class="n">session</span> <span class="o">=</span> <span class="n">session_cls</span><span class="p">(</span><span class="n">model_config</span><span class="p">,</span>
|
|
<span class="n">engine_buffer</span><span class="p">,</span>
|
|
<span class="n">runtime_mapping</span><span class="p">,</span>
|
|
<span class="n">debug_mode</span><span class="o">=</span><span class="n">debug_mode</span><span class="p">,</span>
|
|
<span class="n">stream</span><span class="o">=</span><span class="n">stream</span><span class="p">)</span>
|
|
<span class="k">if</span> <span class="n">session</span><span class="o">.</span><span class="n">use_lora_plugin</span><span class="p">:</span>
|
|
<span class="n">lora_manager</span> <span class="o">=</span> <span class="n">LoraManager</span><span class="p">()</span>
|
|
<span class="k">if</span> <span class="n">lora_dir</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
|
<span class="n">lora_manager</span><span class="o">.</span><span class="n">load_from_ckpt</span><span class="p">(</span><span class="n">model_dir</span><span class="o">=</span><span class="n">lora_dir</span><span class="p">,</span>
|
|
<span class="n">model_config</span><span class="o">=</span><span class="n">model_config</span><span class="p">,</span>
|
|
<span class="n">runtime_mapping</span><span class="o">=</span><span class="n">runtime_mapping</span><span class="p">,</span>
|
|
<span class="n">ckpt_source</span><span class="o">=</span><span class="n">lora_ckpt_source</span><span class="p">)</span>
|
|
<span class="k">else</span><span class="p">:</span>
|
|
<span class="n">lora_manager</span> <span class="o">=</span> <span class="kc">None</span>
|
|
|
|
<span class="n">profiler</span><span class="o">.</span><span class="n">stop</span><span class="p">(</span><span class="s1">'load tensorrt_llm engine'</span><span class="p">)</span>
|
|
<span class="n">loading_time</span> <span class="o">=</span> <span class="n">profiler</span><span class="o">.</span><span class="n">elapsed_time_in_sec</span><span class="p">(</span>
|
|
<span class="s2">"load tensorrt_llm engine"</span><span class="p">)</span>
|
|
<span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Load engine takes: </span><span class="si">{</span><span class="n">loading_time</span><span class="si">}</span><span class="s1"> sec'</span><span class="p">)</span>
|
|
|
|
<span class="k">return</span> <span class="bp">cls</span><span class="p">(</span><span class="n">session</span><span class="o">=</span><span class="n">session</span><span class="p">,</span>
|
|
<span class="n">max_batch_size</span><span class="o">=</span><span class="n">max_batch_size</span><span class="p">,</span>
|
|
<span class="n">max_input_len</span><span class="o">=</span><span class="n">max_input_len</span><span class="p">,</span>
|
|
<span class="n">max_seq_len</span><span class="o">=</span><span class="n">max_input_len</span> <span class="o">+</span> <span class="n">max_output_len</span><span class="p">,</span>
|
|
<span class="n">max_beam_width</span><span class="o">=</span><span class="n">max_beam_width</span><span class="p">,</span>
|
|
<span class="n">lora_manager</span><span class="o">=</span><span class="n">lora_manager</span><span class="p">)</span>
|
|
<span class="k">else</span><span class="p">:</span>
|
|
<span class="c1"># the new engine format</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="n">engine_dir</span><span class="p">,</span> <span class="n">rank</span><span class="p">)</span>
|
|
<span class="k">if</span> <span class="n">lora_dir</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
|
<span class="n">config_lora_dir</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">build_config</span><span class="o">.</span><span class="n">lora_config</span><span class="o">.</span><span class="n">lora_dir</span>
|
|
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">config_lora_dir</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
|
<span class="n">lora_dir</span> <span class="o">=</span> <span class="p">[</span>
|
|
<span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">engine_dir</span><span class="si">}</span><span class="s2">/</span><span class="si">{</span><span class="nb">dir</span><span class="si">}</span><span class="s2">"</span> <span class="k">for</span> <span class="nb">dir</span> <span class="ow">in</span> <span class="n">config_lora_dir</span>
|
|
<span class="p">]</span>
|
|
<span class="n">lora_ckpt_source</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">build_config</span><span class="o">.</span><span class="n">lora_config</span><span class="o">.</span><span class="n">lora_ckpt_source</span>
|
|
<span class="n">runner</span> <span class="o">=</span> <span class="n">ModelRunner</span><span class="o">.</span><span class="n">from_engine</span><span class="p">(</span><span class="n">engine</span><span class="p">,</span> <span class="n">lora_dir</span><span class="p">,</span> <span class="n">rank</span><span class="p">,</span> <span class="n">debug_mode</span><span class="p">,</span>
|
|
<span class="n">lora_ckpt_source</span><span class="p">,</span> <span class="n">medusa_choices</span><span class="p">,</span>
|
|
<span class="n">stream</span><span class="p">)</span>
|
|
<span class="n">profiler</span><span class="o">.</span><span class="n">stop</span><span class="p">(</span><span class="s1">'load tensorrt_llm engine'</span><span class="p">)</span>
|
|
<span class="n">loading_time</span> <span class="o">=</span> <span class="n">profiler</span><span class="o">.</span><span class="n">elapsed_time_in_sec</span><span class="p">(</span>
|
|
<span class="s2">"load tensorrt_llm engine"</span><span class="p">)</span>
|
|
<span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s1">'Load engine takes: </span><span class="si">{</span><span class="n">loading_time</span><span class="si">}</span><span class="s1"> sec'</span><span class="p">)</span>
|
|
<span class="k">return</span> <span class="n">runner</span></div>
|
|
|
|
|
|
<span class="nd">@property</span>
|
|
<span class="k">def</span> <span class="nf">dtype</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></span> <span class="n">torch</span><span class="o">.</span><span class="n">dtype</span><span class="p">:</span>
|
|
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">session</span><span class="o">.</span><span class="n">dtype</span>
|
|
|
|
<span class="nd">@property</span>
|
|
<span class="k">def</span> <span class="nf">vocab_size</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></span> <span class="nb">int</span><span class="p">:</span>
|
|
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">session</span><span class="o">.</span><span class="n">vocab_size</span>
|
|
|
|
<span class="nd">@property</span>
|
|
<span class="k">def</span> <span class="nf">vocab_size_padded</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></span> <span class="nb">int</span><span class="p">:</span>
|
|
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">session</span><span class="o">.</span><span class="n">vocab_size_padded</span>
|
|
|
|
<span class="nd">@property</span>
|
|
<span class="k">def</span> <span class="nf">hidden_size</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></span> <span class="nb">int</span><span class="p">:</span>
|
|
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">session</span><span class="o">.</span><span class="n">hidden_size</span>
|
|
|
|
<span class="nd">@property</span>
|
|
<span class="k">def</span> <span class="nf">num_heads</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></span> <span class="nb">int</span><span class="p">:</span>
|
|
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">session</span><span class="o">.</span><span class="n">num_heads</span>
|
|
|
|
<span class="nd">@property</span>
|
|
<span class="k">def</span> <span class="nf">num_layers</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></span> <span class="nb">int</span><span class="p">:</span>
|
|
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">session</span><span class="o">.</span><span class="n">num_layers</span>
|
|
|
|
<span class="nd">@property</span>
|
|
<span class="k">def</span> <span class="nf">max_sequence_length</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></span> <span class="nb">int</span><span class="p">:</span>
|
|
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_seq_len</span>
|
|
|
|
<span class="nd">@property</span>
|
|
<span class="k">def</span> <span class="nf">remove_input_padding</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></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">session</span><span class="o">.</span><span class="n">remove_input_padding</span>
|
|
|
|
<span class="nd">@property</span>
|
|
<span class="k">def</span> <span class="nf">use_lora_plugin</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></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">session</span><span class="o">.</span><span class="n">use_lora_plugin</span>
|
|
|
|
<span class="nd">@property</span>
|
|
<span class="k">def</span> <span class="nf">max_prompt_embedding_table_size</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></span> <span class="nb">int</span><span class="p">:</span>
|
|
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">session</span><span class="o">.</span><span class="n">max_prompt_embedding_table_size</span>
|
|
|
|
<span class="nd">@property</span>
|
|
<span class="k">def</span> <span class="nf">gather_context_logits</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></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">session</span><span class="o">.</span><span class="n">gather_context_logits</span>
|
|
|
|
<span class="nd">@property</span>
|
|
<span class="k">def</span> <span class="nf">gather_generation_logits</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></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">session</span><span class="o">.</span><span class="n">gather_generation_logits</span>
|
|
|
|
<div class="viewcode-block" id="ModelRunner.generate">
|
|
<a class="viewcode-back" href="../../../python-api/tensorrt_llm.runtime.html#tensorrt_llm.runtime.ModelRunner.generate">[docs]</a>
|
|
<span class="k">def</span> <span class="nf">generate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span>
|
|
<span class="n">batch_input_ids</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">],</span>
|
|
<span class="n">sampling_config</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">SamplingConfig</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
|
|
<span class="n">prompt_table_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="p">,</span>
|
|
<span class="n">prompt_tasks</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="n">lora_uids</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">list</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
|
|
<span class="n">streaming</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
|
|
<span class="n">stopping_criteria</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">StoppingCriteria</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
|
|
<span class="n">logits_processor</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">LogitsProcessor</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</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="p">,</span>
|
|
<span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-></span> <span class="n">Union</span><span class="p">[</span><span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">,</span> <span class="nb">dict</span><span class="p">]:</span>
|
|
<span class="w"> </span><span class="sd">"""</span>
|
|
<span class="sd"> Generates sequences of token ids.</span>
|
|
<span class="sd"> The generation-controlling parameters are set in the sampling_config; it will be set to a default one if not passed.</span>
|
|
<span class="sd"> You can override any sampling_config's attributes by passing corresponding parameters.</span>
|
|
|
|
<span class="sd"> Args:</span>
|
|
<span class="sd"> batch_input_ids (List[torch.Tensor]):</span>
|
|
<span class="sd"> A list of input id tensors. Each tensor is of shape (sequence_length, ).</span>
|
|
<span class="sd"> sampling_config (SamplingConfig):</span>
|
|
<span class="sd"> The sampling configuration to be used as base parametrization for the generation call.</span>
|
|
<span class="sd"> The passed **kwargs matching the sampling_config's attributes will override them.</span>
|
|
<span class="sd"> If the sampling_config is not provided, a default will be used.</span>
|
|
<span class="sd"> prompt_table_path (str):</span>
|
|
<span class="sd"> The file path of prompt table (.npy format, exported by nemo_prompt_convert.py).</span>
|
|
<span class="sd"> prompt_tasks (str):</span>
|
|
<span class="sd"> The prompt tuning task ids for the input batch, in format of comma-separated list (e.g., 0,3,1,0).</span>
|
|
<span class="sd"> lora_uids (list):</span>
|
|
<span class="sd"> The uids of LoRA weights for the input batch. Use -1 to disable the LoRA module.</span>
|
|
<span class="sd"> streaming (bool):</span>
|
|
<span class="sd"> Whether or not to use streaming mode for generation.</span>
|
|
<span class="sd"> stopping_criteria (StoppingCriteria):</span>
|
|
<span class="sd"> Custom stopping criteria.</span>
|
|
<span class="sd"> logits_processor (LogitsProcessor):</span>
|
|
<span class="sd"> Custom logits processors.</span>
|
|
<span class="sd"> medusa_choices (List[List[int]]):</span>
|
|
<span class="sd"> Medusa decoding choices.</span>
|
|
<span class="sd"> kwargs (Dict[str, Any]:</span>
|
|
<span class="sd"> Ad hoc parametrization of sampling_config.</span>
|
|
<span class="sd"> The passed **kwargs matching the sampling_config's attributes will override them.</span>
|
|
<span class="sd"> Returns:</span>
|
|
<span class="sd"> torch.Tensor or dict:</span>
|
|
<span class="sd"> If return_dict=False, the method returns generated output_ids.</span>
|
|
<span class="sd"> If return_dict=True, the method returns a dict of output_ids,</span>
|
|
<span class="sd"> sequence_lengths (if sampling_config.output_sequence_lengths=True),</span>
|
|
<span class="sd"> context_logits and generation_logits (if self.gather_context_logits=True</span>
|
|
<span class="sd"> and self.gather_generation_logits=True, respectively).</span>
|
|
<span class="sd"> """</span>
|
|
<span class="c1"># Use sampling_config like HF's generation_config</span>
|
|
<span class="k">if</span> <span class="n">sampling_config</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
|
<span class="n">sampling_config</span> <span class="o">=</span> <span class="n">SamplingConfig</span><span class="p">(</span><span class="n">end_id</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">pad_id</span><span class="o">=</span><span class="kc">None</span><span class="p">)</span>
|
|
<span class="k">else</span><span class="p">:</span>
|
|
<span class="n">sampling_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="n">sampling_config</span><span class="p">)</span>
|
|
<span class="n">sampling_config</span><span class="o">.</span><span class="n">update</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">_check_inputs</span><span class="p">(</span><span class="n">batch_input_ids</span><span class="p">,</span> <span class="n">sampling_config</span><span class="p">)</span>
|
|
|
|
<span class="n">batch_size</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">batch_input_ids</span><span class="p">)</span>
|
|
<span class="n">batch_input_ids</span><span class="p">,</span> <span class="n">input_lengths</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_prepare_inputs</span><span class="p">(</span>
|
|
<span class="n">batch_input_ids</span><span class="p">,</span> <span class="n">sampling_config</span><span class="o">.</span><span class="n">pad_id</span><span class="p">)</span>
|
|
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">session</span><span class="o">.</span><span class="n">setup</span><span class="p">(</span>
|
|
<span class="n">batch_size</span><span class="o">=</span><span class="n">batch_size</span><span class="p">,</span>
|
|
<span class="n">max_context_length</span><span class="o">=</span><span class="n">input_lengths</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="o">.</span><span class="n">item</span><span class="p">(),</span>
|
|
<span class="n">max_new_tokens</span><span class="o">=</span><span class="n">sampling_config</span><span class="o">.</span><span class="n">max_new_tokens</span><span class="p">,</span>
|
|
<span class="n">beam_width</span><span class="o">=</span><span class="n">sampling_config</span><span class="o">.</span><span class="n">num_beams</span><span class="p">,</span>
|
|
<span class="n">max_attention_window_size</span><span class="o">=</span><span class="n">sampling_config</span><span class="o">.</span><span class="n">max_attention_window_size</span><span class="p">,</span>
|
|
<span class="n">sink_token_length</span><span class="o">=</span><span class="n">sampling_config</span><span class="o">.</span><span class="n">sink_token_length</span><span class="p">,</span>
|
|
<span class="n">lora_manager</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">lora_manager</span><span class="p">,</span>
|
|
<span class="n">lora_uids</span><span class="o">=</span><span class="n">lora_uids</span><span class="p">,</span>
|
|
<span class="n">medusa_choices</span><span class="o">=</span><span class="n">medusa_choices</span><span class="p">)</span>
|
|
|
|
<span class="n">batch_input_ids</span> <span class="o">=</span> <span class="n">batch_input_ids</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
|
|
<span class="n">input_lengths</span> <span class="o">=</span> <span class="n">input_lengths</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
|
|
<span class="n">ptuning_kwargs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_prepare_ptuning</span><span class="p">(</span><span class="n">prompt_table_path</span><span class="p">,</span> <span class="n">prompt_tasks</span><span class="p">,</span>
|
|
<span class="n">batch_size</span><span class="p">)</span>
|
|
<span class="n">outputs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">session</span><span class="o">.</span><span class="n">decode</span><span class="p">(</span>
|
|
<span class="n">batch_input_ids</span><span class="p">,</span>
|
|
<span class="n">input_lengths</span><span class="p">,</span>
|
|
<span class="n">sampling_config</span><span class="p">,</span>
|
|
<span class="n">stop_words_list</span><span class="o">=</span><span class="n">sampling_config</span><span class="o">.</span><span class="n">stop_words_list</span><span class="p">,</span>
|
|
<span class="n">bad_words_list</span><span class="o">=</span><span class="n">sampling_config</span><span class="o">.</span><span class="n">bad_words_list</span><span class="p">,</span>
|
|
<span class="n">output_sequence_lengths</span><span class="o">=</span><span class="n">sampling_config</span><span class="o">.</span><span class="n">output_sequence_lengths</span><span class="p">,</span>
|
|
<span class="n">return_dict</span><span class="o">=</span><span class="n">sampling_config</span><span class="o">.</span><span class="n">return_dict</span><span class="p">,</span>
|
|
<span class="n">streaming</span><span class="o">=</span><span class="n">streaming</span><span class="p">,</span>
|
|
<span class="n">stopping_criteria</span><span class="o">=</span><span class="n">stopping_criteria</span><span class="p">,</span>
|
|
<span class="n">logits_processor</span><span class="o">=</span><span class="n">logits_processor</span><span class="p">,</span>
|
|
<span class="o">**</span><span class="n">ptuning_kwargs</span><span class="p">)</span>
|
|
<span class="k">if</span> <span class="n">sampling_config</span><span class="o">.</span><span class="n">return_dict</span><span class="p">:</span>
|
|
<span class="k">if</span> <span class="n">streaming</span><span class="p">:</span>
|
|
<span class="n">outputs</span> <span class="o">=</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_prepare_outputs</span><span class="p">(</span><span class="n">curr_outputs</span><span class="p">,</span> <span class="n">input_lengths</span><span class="p">)</span>
|
|
<span class="k">for</span> <span class="n">curr_outputs</span> <span class="ow">in</span> <span class="n">outputs</span><span class="p">)</span>
|
|
<span class="k">else</span><span class="p">:</span>
|
|
<span class="n">outputs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_prepare_outputs</span><span class="p">(</span><span class="n">outputs</span><span class="p">,</span> <span class="n">input_lengths</span><span class="p">)</span>
|
|
<span class="k">return</span> <span class="n">outputs</span></div>
|
|
|
|
|
|
<div class="viewcode-block" id="ModelRunner.serialize_engine">
|
|
<a class="viewcode-back" href="../../../python-api/tensorrt_llm.runtime.html#tensorrt_llm.runtime.ModelRunner.serialize_engine">[docs]</a>
|
|
<span class="k">def</span> <span class="nf">serialize_engine</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></span> <span class="n">trt</span><span class="o">.</span><span class="n">IHostMemory</span><span class="p">:</span>
|
|
<span class="w"> </span><span class="sd">"""</span>
|
|
<span class="sd"> Serialize the engine.</span>
|
|
|
|
<span class="sd"> Returns:</span>
|
|
<span class="sd"> bytes: The serialized engine.</span>
|
|
<span class="sd"> """</span>
|
|
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">session</span><span class="o">.</span><span class="n">runtime</span><span class="o">.</span><span class="n">_serialize_engine</span><span class="p">()</span></div>
|
|
</div>
|
|
|
|
</pre></div>
|
|
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