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TensorRT-LLMs/_modules/tensorrt_llm/models/medusa/model.html
Kaiyu Xie b151d03357 Update GitHub pages in root to v1.0.0rc5
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<div class="bd-toc-item navbar-nav"><p aria-level="2" class="caption" role="heading"><span class="caption-text">Getting Started</span></p>
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<li class="toctree-l1"><a class="reference internal" href="../../../../overview.html">Overview</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../../../../examples/llm_inference.html">Generate text</a></li>
<li class="toctree-l2"><a class="reference internal" href="../../../../examples/llm_inference_async.html">Generate text asynchronously</a></li>
<li class="toctree-l2"><a class="reference internal" href="../../../../examples/llm_inference_async_streaming.html">Generate text in streaming</a></li>
<li class="toctree-l2"><a class="reference internal" href="../../../../examples/llm_inference_distributed.html">Distributed LLM Generation</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../../../../examples/llm_multilora.html">Generate text with multiple LoRA adapters</a></li>
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<p aria-level="2" class="caption" role="heading"><span class="caption-text">Advanced</span></p>
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<li class="toctree-l1"><a class="reference internal" href="../../../../advanced/gpt-attention.html">Multi-Head, Multi-Query, and Group-Query Attention</a></li>
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<li class="toctree-l1"><a class="reference internal" href="../../../../advanced/lora.html">Run gpt-2b + LoRA using Executor / cpp runtime</a></li>
<li class="toctree-l1"><a class="reference internal" href="../../../../advanced/expert-parallelism.html">Expert Parallelism in TensorRT-LLM</a></li>
<li class="toctree-l1"><a class="reference internal" href="../../../../advanced/kv-cache-management.html">KV Cache Management: Pools, Blocks, and Events</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../../../../performance/performance-tuning-guide/fp8-quantization.html">FP8 Quantization</a></li>
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<li class="toctree-l1"><a class="reference internal" href="../../../../blogs/H100vsA100.html">H100 has 4.6x A100 Performance in TensorRT-LLM, achieving 10,000 tok/s at 100ms to first token</a></li>
<li class="toctree-l1"><a class="reference internal" href="../../../../blogs/H200launch.html">H200 achieves nearly 12,000 tokens/sec on Llama2-13B with TensorRT-LLM</a></li>
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<h1>Source code for tensorrt_llm.models.medusa.model</h1><div class="highlight"><pre>
<span></span><span class="c1"># SPDX-FileCopyrightText: Copyright (c) 2022-2023 NVIDIA CORPORATION &amp; AFFILIATES. All rights reserved.</span>
<span class="c1"># SPDX-License-Identifier: Apache-2.0</span>
<span class="c1">#</span>
<span class="c1"># Licensed under the Apache License, Version 2.0 (the &quot;License&quot;);</span>
<span class="c1"># you may not use this file except in compliance with the License.</span>
<span class="c1"># You may obtain a copy of the License at</span>
<span class="c1">#</span>
<span class="c1"># http://www.apache.org/licenses/LICENSE-2.0</span>
<span class="c1">#</span>
<span class="c1"># Unless required by applicable law or agreed to in writing, software</span>
<span class="c1"># distributed under the License is distributed on an &quot;AS IS&quot; BASIS,</span>
<span class="c1"># WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.</span>
<span class="c1"># See the License for the specific language governing permissions and</span>
<span class="c1"># limitations under the License.</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">json</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">typing</span><span class="w"> </span><span class="kn">import</span> <span class="n">Optional</span><span class="p">,</span> <span class="n">Union</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">transformers</span><span class="w"> </span><span class="kn">import</span> <span class="n">AutoModelForCausalLM</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">tensorrt_llm._utils</span><span class="w"> </span><span class="kn">import</span> <span class="n">numpy_to_torch</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">tensorrt_llm.models.llama.model</span><span class="w"> </span><span class="kn">import</span> <span class="n">LLaMAForCausalLM</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">tensorrt_llm.models.medusa.weight</span><span class="w"> </span><span class="kn">import</span> <span class="n">load_medusa_hf</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">tensorrt_llm.models.qwen.model</span><span class="w"> </span><span class="kn">import</span> <span class="n">QWenForCausalLM</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">..._common</span><span class="w"> </span><span class="kn">import</span> <span class="n">default_net</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">..._utils</span><span class="w"> </span><span class="kn">import</span> <span class="n">pad_vocab_size</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">...functional</span><span class="w"> </span><span class="kn">import</span> <span class="n">ACT2FN</span><span class="p">,</span> <span class="n">stack</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">...layers</span><span class="w"> </span><span class="kn">import</span> <span class="n">ColumnLinear</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">...mapping</span><span class="w"> </span><span class="kn">import</span> <span class="n">Mapping</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">...module</span><span class="w"> </span><span class="kn">import</span> <span class="n">Module</span><span class="p">,</span> <span class="n">ModuleList</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">..modeling_utils</span><span class="w"> </span><span class="kn">import</span> <span class="n">PretrainedModel</span><span class="p">,</span> <span class="n">QuantConfig</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">.config</span><span class="w"> </span><span class="kn">import</span> <span class="n">MedusaConfig</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">.weight</span><span class="w"> </span><span class="kn">import</span> <span class="n">convert_hf_llama</span>
<span class="k">class</span><span class="w"> </span><span class="nc">MedusaLayer</span><span class="p">(</span><span class="n">Module</span><span class="p">):</span>
<span class="k">def</span><span class="w"> </span><span class="fm">__init__</span><span class="p">(</span>
<span class="bp">self</span><span class="p">,</span>
<span class="n">hidden_size</span><span class="p">,</span>
<span class="n">hidden_act</span><span class="o">=</span><span class="s2">&quot;silu&quot;</span><span class="p">,</span>
<span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
<span class="n">mapping</span><span class="o">=</span><span class="n">Mapping</span><span class="p">(),</span>
<span class="p">):</span>
<span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>
<span class="bp">self</span><span class="o">.</span><span class="n">linear</span> <span class="o">=</span> <span class="n">ColumnLinear</span><span class="p">(</span><span class="n">hidden_size</span><span class="p">,</span>
<span class="n">hidden_size</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">tp_group</span><span class="o">=</span><span class="n">mapping</span><span class="o">.</span><span class="n">tp_group</span><span class="p">,</span>
<span class="n">tp_size</span><span class="o">=</span><span class="n">mapping</span><span class="o">.</span><span class="n">tp_size</span><span class="p">,</span>
<span class="n">gather_output</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">hidden_act</span> <span class="o">=</span> <span class="n">hidden_act</span>
<span class="k">def</span><span class="w"> </span><span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
<span class="k">return</span> <span class="n">x</span> <span class="o">+</span> <span class="n">ACT2FN</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">hidden_act</span><span class="p">](</span><span class="bp">self</span><span class="o">.</span><span class="n">linear</span><span class="p">(</span><span class="n">x</span><span class="p">))</span>
<span class="k">class</span><span class="w"> </span><span class="nc">MedusaHead</span><span class="p">(</span><span class="n">Module</span><span class="p">):</span>
<span class="k">def</span><span class="w"> </span><span class="fm">__init__</span><span class="p">(</span>
<span class="bp">self</span><span class="p">,</span>
<span class="n">num_layers</span><span class="p">,</span>
<span class="n">hidden_size</span><span class="p">,</span>
<span class="n">vocab_size</span><span class="p">,</span>
<span class="n">hidden_act</span><span class="o">=</span><span class="s2">&quot;silu&quot;</span><span class="p">,</span>
<span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
<span class="n">mapping</span><span class="o">=</span><span class="n">Mapping</span><span class="p">(),</span>
<span class="p">):</span>
<span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>
<span class="bp">self</span><span class="o">.</span><span class="n">medusa_layers</span> <span class="o">=</span> <span class="n">ModuleList</span><span class="p">([</span>
<span class="n">MedusaLayer</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">hidden_act</span><span class="o">=</span><span class="n">hidden_act</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">mapping</span><span class="o">=</span><span class="n">mapping</span><span class="p">)</span> <span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">num_layers</span><span class="p">)</span>
<span class="p">])</span>
<span class="bp">self</span><span class="o">.</span><span class="n">lm_head</span> <span class="o">=</span> <span class="n">ColumnLinear</span><span class="p">(</span><span class="n">hidden_size</span><span class="p">,</span>
<span class="n">vocab_size</span><span class="p">,</span>
<span class="n">bias</span><span class="o">=</span><span class="kc">False</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">tp_group</span><span class="o">=</span><span class="n">mapping</span><span class="o">.</span><span class="n">tp_group</span><span class="p">,</span>
<span class="n">tp_size</span><span class="o">=</span><span class="n">mapping</span><span class="o">.</span><span class="n">tp_size</span><span class="p">,</span>
<span class="n">gather_output</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="k">return</span>
<span class="k">def</span><span class="w"> </span><span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
<span class="n">hidden_states</span> <span class="o">=</span> <span class="n">x</span>
<span class="k">for</span> <span class="n">layer</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">medusa_layers</span><span class="p">:</span>
<span class="n">hidden_states</span> <span class="o">=</span> <span class="n">layer</span><span class="p">(</span><span class="n">hidden_states</span><span class="p">)</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">lm_head</span><span class="p">(</span><span class="n">hidden_states</span><span class="p">)</span>
<span class="c1"># MedusaForCausalLm is a thin wrapper that picks parent class for GenericMedusaForCausalLM.</span>
<span class="c1"># All medusa functionality is defined in GenericMedusaForCausalLM.</span>
<div class="viewcode-block" id="MedusaForCausalLm">
<a class="viewcode-back" href="../../../../python-api/tensorrt_llm.models.html#tensorrt_llm.models.MedusaForCausalLm">[docs]</a>
<span class="k">class</span><span class="w"> </span><span class="nc">MedusaForCausalLm</span><span class="p">(</span><span class="n">PretrainedModel</span><span class="p">):</span>
<span class="n">config_class</span> <span class="o">=</span> <span class="n">MedusaConfig</span>
<span class="k">def</span><span class="w"> </span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">config</span><span class="p">:</span> <span class="n">MedusaConfig</span><span class="p">):</span>
<span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">config</span><span class="p">)</span>
<span class="n">BaseLM</span> <span class="o">=</span> <span class="n">QWenForCausalLM</span> <span class="k">if</span> <span class="nb">hasattr</span><span class="p">(</span>
<span class="n">config</span><span class="p">,</span>
<span class="s2">&quot;model_type&quot;</span><span class="p">)</span> <span class="ow">and</span> <span class="s2">&quot;qwen&quot;</span> <span class="ow">in</span> <span class="n">config</span><span class="o">.</span><span class="n">model_type</span> <span class="k">else</span> <span class="n">LLaMAForCausalLM</span>
<span class="k">class</span><span class="w"> </span><span class="nc">GenericMedusaForCausalLM</span><span class="p">(</span><span class="n">BaseLM</span><span class="p">):</span>
<span class="k">def</span><span class="w"> </span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">config</span><span class="p">:</span> <span class="n">MedusaConfig</span><span class="p">):</span>
<span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">config</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">num_medusa_heads</span> <span class="o">=</span> <span class="n">config</span><span class="o">.</span><span class="n">num_medusa_heads</span>
<span class="bp">self</span><span class="o">.</span><span class="n">num_medusa_layers</span> <span class="o">=</span> <span class="n">config</span><span class="o">.</span><span class="n">num_medusa_layers</span>
<span class="bp">self</span><span class="o">.</span><span class="n">hidden_size</span> <span class="o">=</span> <span class="n">config</span><span class="o">.</span><span class="n">hidden_size</span>
<span class="bp">self</span><span class="o">.</span><span class="n">vocab_size</span> <span class="o">=</span> <span class="n">config</span><span class="o">.</span><span class="n">vocab_size</span>
<span class="n">vocab_size_padded</span> <span class="o">=</span> <span class="n">pad_vocab_size</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">vocab_size</span><span class="p">,</span>
<span class="n">config</span><span class="o">.</span><span class="n">mapping</span><span class="o">.</span><span class="n">tp_size</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">medusa_heads</span> <span class="o">=</span> <span class="n">ModuleList</span><span class="p">([</span>
<span class="n">MedusaHead</span><span class="p">(</span><span class="n">num_layers</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">num_medusa_layers</span><span class="p">,</span>
<span class="n">hidden_size</span><span class="o">=</span><span class="n">config</span><span class="o">.</span><span class="n">hidden_size</span><span class="p">,</span>
<span class="n">vocab_size</span><span class="o">=</span><span class="n">vocab_size_padded</span><span class="p">,</span>
<span class="n">hidden_act</span><span class="o">=</span><span class="n">config</span><span class="o">.</span><span class="n">hidden_act</span><span class="p">,</span>
<span class="n">dtype</span><span class="o">=</span><span class="n">config</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
<span class="n">mapping</span><span class="o">=</span><span class="n">config</span><span class="o">.</span><span class="n">mapping</span><span class="p">)</span>
<span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">num_medusa_heads</span><span class="p">)</span>
<span class="p">])</span>
<span class="bp">self</span><span class="o">.</span><span class="n">max_medusa_token_len</span> <span class="o">=</span> <span class="n">config</span><span class="o">.</span><span class="n">max_draft_len</span>
<span class="k">def</span><span class="w"> </span><span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="n">output_original</span> <span class="o">=</span> <span class="kc">True</span>
<span class="n">hidden_states</span> <span class="o">=</span> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">forward</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="k">if</span> <span class="n">kwargs</span><span class="p">[</span><span class="s1">&#39;use_cache&#39;</span><span class="p">]:</span>
<span class="k">if</span> <span class="n">default_net</span><span class="p">()</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">lm_logits</span><span class="p">,</span> <span class="n">hidden_states</span><span class="p">,</span> <span class="n">_</span> <span class="o">=</span> <span class="n">hidden_states</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">lm_logits</span><span class="p">,</span> <span class="n">presents</span><span class="p">,</span> <span class="n">hidden_states</span> <span class="o">=</span> <span class="n">hidden_states</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">mapping</span><span class="o">.</span><span class="n">is_last_pp_rank</span><span class="p">():</span>
<span class="n">medusa_logits</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">num_medusa_heads</span><span class="p">):</span>
<span class="n">medusa_logits</span><span class="o">.</span><span class="n">append</span><span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">medusa_heads</span><span class="p">[</span><span class="n">i</span><span class="p">](</span><span class="n">hidden_states</span><span class="p">))</span>
<span class="c1"># [num_medusa_heads, batch_size, num_medusa_tokens + 1, padded_vocab_size].</span>
<span class="c1"># Remove padding [num_medusa_heads, batch_size * num_medusa_tokens + 1, padded_vocab_size].</span>
<span class="n">medusa_logits</span> <span class="o">=</span> <span class="n">stack</span><span class="p">(</span><span class="n">medusa_logits</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="n">medusa_logits</span><span class="o">.</span><span class="n">mark_output</span><span class="p">(</span><span class="s1">&#39;medusa_logits&#39;</span><span class="p">,</span>
<span class="bp">self</span><span class="o">.</span><span class="n">config</span><span class="o">.</span><span class="n">logits_dtype</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">hidden_states</span><span class="o">.</span><span class="n">mark_output</span><span class="p">(</span><span class="s1">&#39;hidden_states_output&#39;</span><span class="p">,</span>
<span class="bp">self</span><span class="o">.</span><span class="n">config</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span>
<span class="k">if</span> <span class="n">kwargs</span><span class="p">[</span><span class="s1">&#39;use_cache&#39;</span><span class="p">]</span> <span class="ow">and</span> <span class="n">default_net</span><span class="p">(</span>
<span class="p">)</span><span class="o">.</span><span class="n">plugin_config</span><span class="o">.</span><span class="n">paged_kv_cache</span> <span class="o">==</span> <span class="kc">False</span><span class="p">:</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">mapping</span><span class="o">.</span><span class="n">is_last_pp_rank</span><span class="p">():</span>
<span class="k">if</span> <span class="n">output_original</span><span class="p">:</span>
<span class="k">return</span> <span class="p">(</span><span class="n">medusa_logits</span><span class="p">,</span> <span class="n">lm_logits</span><span class="p">,</span> <span class="n">presents</span><span class="p">)</span>
<span class="k">return</span> <span class="p">(</span><span class="n">medusa_logits</span><span class="p">,</span> <span class="n">presents</span><span class="p">)</span>
<span class="k">return</span> <span class="p">(</span><span class="n">hidden_states</span><span class="p">,</span> <span class="n">presents</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">mapping</span><span class="o">.</span><span class="n">is_last_pp_rank</span><span class="p">():</span>
<span class="k">if</span> <span class="n">output_original</span><span class="p">:</span>
<span class="k">return</span> <span class="n">medusa_logits</span><span class="p">,</span> <span class="n">lm_logits</span>
<span class="k">return</span> <span class="n">medusa_logits</span>
<span class="k">return</span> <span class="n">hidden_states</span>
<span class="k">def</span><span class="w"> </span><span class="nf">prepare_inputs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="n">kwargs</span><span class="p">[</span><span class="s1">&#39;speculative_decoding_draft_tokens_external&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="kc">False</span>
<span class="n">kwargs</span><span class="p">[</span><span class="s1">&#39;max_draft_len&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_medusa_token_len</span>
<span class="k">return</span> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">prepare_inputs</span><span class="p">(</span><span class="o">*</span><span class="n">args</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">model</span> <span class="o">=</span> <span class="n">GenericMedusaForCausalLM</span><span class="p">(</span><span class="n">config</span><span class="p">)</span>
<span class="c1"># Specialization to redirect accesses to self.model</span>
<span class="k">def</span><span class="w"> </span><span class="fm">__getattribute__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">):</span>
<span class="k">if</span> <span class="n">name</span> <span class="o">==</span> <span class="s1">&#39;model&#39;</span> <span class="ow">or</span> <span class="s1">&#39;__&#39;</span> <span class="ow">in</span> <span class="n">name</span><span class="p">:</span>
<span class="k">return</span> <span class="nb">object</span><span class="o">.</span><span class="fm">__getattribute__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">model</span> <span class="o">=</span> <span class="nb">object</span><span class="o">.</span><span class="fm">__getattribute__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;model&#39;</span><span class="p">)</span>
<span class="k">return</span> <span class="n">model</span><span class="o">.</span><span class="fm">__getattribute__</span><span class="p">(</span><span class="n">name</span><span class="p">)</span>
<span class="c1"># Override specialized __setattr__ defined in Module</span>
<span class="k">def</span><span class="w"> </span><span class="fm">__setattr__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">value</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
<span class="nb">object</span><span class="o">.</span><span class="fm">__setattr__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">value</span><span class="p">)</span>
<div class="viewcode-block" id="MedusaForCausalLm.from_hugging_face">
<a class="viewcode-back" href="../../../../python-api/tensorrt_llm.models.html#tensorrt_llm.models.MedusaForCausalLm.from_hugging_face">[docs]</a>
<span class="nd">@classmethod</span>
<span class="k">def</span><span class="w"> </span><span class="nf">from_hugging_face</span><span class="p">(</span>
<span class="bp">cls</span><span class="p">,</span>
<span class="n">hf_model_or_dir</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="s1">&#39;transformers.PreTrainedModel&#39;</span><span class="p">],</span>
<span class="n">dtype</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s1">&#39;auto&#39;</span><span class="p">,</span>
<span class="n">mapping</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Mapping</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
<span class="n">quant_config</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">QuantConfig</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
<span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">transformers</span>
<span class="k">assert</span> <span class="n">hf_model_or_dir</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span>
<span class="n">speculative_model_dir</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;speculative_model_dir&#39;</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
<span class="n">use_preloading</span> <span class="o">=</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">hf_model_or_dir</span><span class="p">,</span>
<span class="n">transformers</span><span class="o">.</span><span class="n">PreTrainedModel</span><span class="p">)</span>
<span class="k">if</span> <span class="n">use_preloading</span><span class="p">:</span>
<span class="n">hf_model</span> <span class="o">=</span> <span class="n">hf_model_or_dir</span>
<span class="n">hf_config_or_dir</span> <span class="o">=</span> <span class="n">hf_model</span><span class="o">.</span><span class="n">config</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">hf_model_dir</span> <span class="o">=</span> <span class="n">hf_model_or_dir</span>
<span class="n">hf_config_or_dir</span> <span class="o">=</span> <span class="n">hf_model_or_dir</span>
<span class="n">config</span> <span class="o">=</span> <span class="n">MedusaConfig</span><span class="o">.</span><span class="n">from_hugging_face</span><span class="p">(</span><span class="n">hf_config_or_dir</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">mapping</span><span class="o">=</span><span class="n">mapping</span><span class="p">,</span>
<span class="n">quant_config</span><span class="o">=</span><span class="n">quant_config</span><span class="p">,</span>
<span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="c1"># ModelOpt ckpt has combined base model and Medusa-head</span>
<span class="n">is_modelopt_ckpt</span> <span class="o">=</span> <span class="kc">True</span> <span class="k">if</span> <span class="ow">not</span> <span class="n">speculative_model_dir</span> <span class="k">else</span> <span class="kc">False</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">use_preloading</span><span class="p">:</span>
<span class="n">trust_remote_code</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">&#39;trust_remote_code&#39;</span><span class="p">,</span> <span class="kc">True</span><span class="p">)</span>
<span class="k">if</span> <span class="n">is_modelopt_ckpt</span><span class="p">:</span>
<span class="n">hf_model</span> <span class="o">=</span> <span class="n">LLaMAForCausalLM</span><span class="o">.</span><span class="n">from_hugging_face</span><span class="p">(</span>
<span class="n">hf_model_dir</span><span class="p">,</span>
<span class="n">dtype</span><span class="p">,</span>
<span class="n">mapping</span><span class="o">=</span><span class="n">mapping</span><span class="p">,</span>
<span class="n">quant_config</span><span class="o">=</span><span class="n">quant_config</span><span class="p">,</span>
<span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">hf_model</span> <span class="o">=</span> <span class="n">AutoModelForCausalLM</span><span class="o">.</span><span class="n">from_pretrained</span><span class="p">(</span>
<span class="n">hf_model_dir</span><span class="p">,</span>
<span class="n">torch_dtype</span><span class="o">=</span><span class="s2">&quot;auto&quot;</span><span class="p">,</span>
<span class="n">trust_remote_code</span><span class="o">=</span><span class="n">trust_remote_code</span><span class="p">)</span>
<span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">hf_model</span><span class="p">,</span> <span class="n">transformers</span><span class="o">.</span><span class="n">PreTrainedModel</span><span class="p">)</span>
<span class="k">if</span> <span class="n">is_modelopt_ckpt</span><span class="p">:</span>
<span class="n">weights</span> <span class="o">=</span> <span class="p">{</span>
<span class="n">name</span><span class="p">:</span> <span class="n">numpy_to_torch</span><span class="p">(</span><span class="n">param</span><span class="o">.</span><span class="n">raw_value</span><span class="p">)</span>
<span class="k">for</span> <span class="n">name</span><span class="p">,</span> <span class="n">param</span> <span class="ow">in</span> <span class="n">hf_model</span><span class="o">.</span><span class="n">named_parameters</span><span class="p">()</span>
<span class="p">}</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">weights</span> <span class="o">=</span> <span class="n">convert_hf_llama</span><span class="p">(</span>
<span class="n">hf_model</span><span class="p">,</span>
<span class="n">config</span><span class="o">.</span><span class="n">mapping</span><span class="p">,</span>
<span class="n">dtype</span><span class="o">=</span><span class="s1">&#39;float16&#39;</span><span class="p">,</span>
<span class="n">use_parallel_embedding</span><span class="o">=</span><span class="n">config</span><span class="o">.</span><span class="n">use_parallel_embedding</span><span class="p">)</span>
<span class="n">model</span> <span class="o">=</span> <span class="bp">cls</span><span class="p">(</span><span class="n">config</span><span class="p">)</span>
<span class="k">if</span> <span class="n">is_modelopt_ckpt</span><span class="p">:</span>
<span class="n">num_medusa_heads</span> <span class="o">=</span> <span class="n">config</span><span class="o">.</span><span class="n">config</span><span class="o">.</span><span class="n">num_medusa_heads</span>
<span class="n">num_medusa_layers</span> <span class="o">=</span> <span class="n">config</span><span class="o">.</span><span class="n">config</span><span class="o">.</span><span class="n">num_medusa_layers</span>
<span class="n">speculative_model_dir</span> <span class="o">=</span> <span class="n">hf_model_or_dir</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">config_file</span> <span class="o">=</span> <span class="n">speculative_model_dir</span> <span class="o">/</span> <span class="s2">&quot;config.json&quot;</span>
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">config_file</span><span class="p">)</span> <span class="k">as</span> <span class="n">fp</span><span class="p">:</span>
<span class="n">model_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">fp</span><span class="p">)</span>
<span class="n">num_medusa_heads</span> <span class="o">=</span> <span class="n">kwargs</span><span class="p">[</span>
<span class="s1">&#39;speculative_config&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">num_medusa_heads</span> <span class="k">if</span> <span class="s1">&#39;speculative_config&#39;</span> <span class="ow">in</span> <span class="n">kwargs</span> <span class="k">else</span> <span class="n">model_config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span>
<span class="s1">&#39;medusa_num_heads&#39;</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
<span class="n">num_medusa_layers</span> <span class="o">=</span> <span class="n">model_config</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;medusa_num_layers&#39;</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
<span class="n">medusa_weights</span> <span class="o">=</span> <span class="n">load_medusa_hf</span><span class="p">(</span><span class="n">medusa_path</span><span class="o">=</span><span class="n">speculative_model_dir</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">num_medusa_layers</span><span class="o">=</span><span class="n">num_medusa_layers</span><span class="p">,</span>
<span class="n">mapping</span><span class="o">=</span><span class="n">mapping</span><span class="p">,</span>
<span class="n">dtype</span><span class="o">=</span><span class="s2">&quot;float16&quot;</span><span class="p">,</span>
<span class="n">is_modelopt_ckpt</span><span class="o">=</span><span class="n">is_modelopt_ckpt</span><span class="p">)</span>
<span class="n">weights</span><span class="o">.</span><span class="n">update</span><span class="p">(</span><span class="n">medusa_weights</span><span class="p">)</span>
<span class="n">model</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">weights</span><span class="p">)</span>
<span class="k">return</span> <span class="n">model</span></div>
</div>
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