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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-l1"><a class="reference internal" href="../../../../quick-start-guide.html">Quick Start Guide</a></li>
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<li class="toctree-l1 has-children"><a class="reference internal" href="../../../../installation/index.html">Installation</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
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<li class="toctree-l2"><a class="reference internal" href="../../../../installation/containers.html">Pre-built release container images on NGC</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../../../../installation/build-from-source-linux.html">Building from Source Code on Linux</a></li>
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<p aria-level="2" class="caption" role="heading"><span class="caption-text">Deployment Guide</span></p>
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<li class="toctree-l1 has-children"><a class="reference internal" href="../../../../examples/llm_api_examples.html">LLM Examples</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
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<li class="toctree-l2"><a class="reference internal" href="../../../../examples/llm_inference.html">Generate text</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../../../../examples/llm_inference_async.html">Generate text asynchronously</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../../../../examples/llm_inference_async_streaming.html">Generate text in streaming</a></li>
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<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_guided_decoding.html">Generate text with guided decoding</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../../../../examples/llm_logits_processor.html">Control generated text using logits processor</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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<li class="toctree-l2"><a class="reference internal" href="../../../../examples/llm_speculative_decoding.html">Speculative Decoding</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../../../../examples/llm_kv_cache_connector.html">KV Cache Connector</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../../../../examples/llm_runtime.html">Runtime Configuration Examples</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../../../../examples/llm_sampling.html">Sampling Techniques Showcase</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../../../../examples/llm_mgmn_llm_distributed.html">Run LLM-API with pytorch backend on Slurm</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../../../../examples/llm_mgmn_trtllm_bench.html">Run trtllm-bench with pytorch backend on Slurm</a></li>
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<li class="toctree-l2"><a class="reference internal" href="../../../../examples/llm_mgmn_trtllm_serve.html">Run trtllm-serve with pytorch backend on Slurm</a></li>
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</ul>
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</details></li>
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<li class="toctree-l1 has-children"><a class="reference internal" href="../../../../examples/trtllm_serve_examples.html">Online Serving Examples</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
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<li class="toctree-l2"><a class="reference internal" href="../../../../examples/curl_chat_client.html">Curl Chat Client</a></li>
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||
<li class="toctree-l2"><a class="reference internal" href="../../../../examples/curl_chat_client_for_multimodal.html">Curl Chat Client For Multimodal</a></li>
|
||
<li class="toctree-l2"><a class="reference internal" href="../../../../examples/curl_completion_client.html">Curl Completion Client</a></li>
|
||
<li class="toctree-l2"><a class="reference internal" href="../../../../examples/deepseek_r1_reasoning_parser.html">Deepseek R1 Reasoning Parser</a></li>
|
||
<li class="toctree-l2"><a class="reference internal" href="../../../../examples/genai_perf_client.html">Genai Perf Client</a></li>
|
||
<li class="toctree-l2"><a class="reference internal" href="../../../../examples/genai_perf_client_for_multimodal.html">Genai Perf Client For Multimodal</a></li>
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||
<li class="toctree-l2"><a class="reference internal" href="../../../../examples/openai_chat_client.html">OpenAI Chat Client</a></li>
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||
<li class="toctree-l2"><a class="reference internal" href="../../../../examples/openai_chat_client_for_multimodal.html">OpenAI Chat Client for Multimodal</a></li>
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||
<li class="toctree-l2"><a class="reference internal" href="../../../../examples/openai_completion_client.html">OpenAI Completion Client</a></li>
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||
<li class="toctree-l2"><a class="reference internal" href="../../../../examples/openai_completion_client_for_lora.html">Openai Completion Client For Lora</a></li>
|
||
<li class="toctree-l2"><a class="reference internal" href="../../../../examples/openai_completion_client_json_schema.html">OpenAI Completion Client with JSON Schema</a></li>
|
||
</ul>
|
||
</details></li>
|
||
<li class="toctree-l1"><a class="reference internal" href="../../../../examples/dynamo_k8s_example.html">Dynamo K8s Example</a></li>
|
||
<li class="toctree-l1 has-children"><a class="reference internal" href="../../../../deployment-guide/index.html">Model Recipes</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
|
||
<li class="toctree-l2"><a class="reference internal" href="../../../../deployment-guide/quick-start-recipe-for-deepseek-r1-on-trtllm.html">Quick Start Recipe for DeepSeek R1 on TensorRT LLM - Blackwell & Hopper Hardware</a></li>
|
||
<li class="toctree-l2"><a class="reference internal" href="../../../../deployment-guide/quick-start-recipe-for-llama3.3-70b-on-trtllm.html">Quick Start Recipe for Llama3.3 70B on TensorRT LLM - Blackwell & Hopper Hardware</a></li>
|
||
<li class="toctree-l2"><a class="reference internal" href="../../../../deployment-guide/quick-start-recipe-for-llama4-scout-on-trtllm.html">Quick Start Recipe for Llama4 Scout 17B on TensorRT LLM - Blackwell & Hopper Hardware</a></li>
|
||
<li class="toctree-l2"><a class="reference internal" href="../../../../deployment-guide/quick-start-recipe-for-gpt-oss-on-trtllm.html">Quick Start Recipe for GPT-OSS on TensorRT-LLM - Blackwell Hardware</a></li>
|
||
</ul>
|
||
</details></li>
|
||
</ul>
|
||
<p aria-level="2" class="caption" role="heading"><span class="caption-text">Models</span></p>
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<ul class="nav bd-sidenav">
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<li class="toctree-l1"><a class="reference internal" href="../../../../models/supported-models.html">Supported Models</a></li>
|
||
|
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<li class="toctree-l1"><a class="reference internal" href="../../../../models/adding-new-model.html">Adding a New Model</a></li>
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</ul>
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<ul class="nav bd-sidenav">
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<li class="breadcrumb-item active" aria-current="page"><span class="ellipsis">tensorrt_llm.models.redrafter.model</span></li>
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<article class="bd-article">
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<h1>Source code for tensorrt_llm.models.redrafter.model</h1><div class="highlight"><pre>
|
||
<span></span><span class="c1"># SPDX-FileCopyrightText: Copyright (c) 2022-2024 NVIDIA CORPORATION & 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 "License");</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 "AS IS" 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">from</span><span class="w"> </span><span class="nn">collections</span><span class="w"> </span><span class="kn">import</span> <span class="n">OrderedDict</span>
|
||
|
||
<span class="kn">import</span><span class="w"> </span><span class="nn">tensorrt</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">trt</span>
|
||
|
||
<span class="kn">from</span><span class="w"> </span><span class="nn">tensorrt_llm._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">tensorrt_llm.bindings</span><span class="w"> </span><span class="kn">import</span> <span class="n">KVCacheType</span>
|
||
<span class="kn">from</span><span class="w"> </span><span class="nn">tensorrt_llm.functional</span><span class="w"> </span><span class="kn">import</span> <span class="n">Tensor</span><span class="p">,</span> <span class="n">cast</span><span class="p">,</span> <span class="n">categorical_sample</span>
|
||
<span class="kn">from</span><span class="w"> </span><span class="nn">tensorrt_llm.models</span><span class="w"> </span><span class="kn">import</span> <span class="n">LLaMAForCausalLM</span><span class="p">,</span> <span class="n">QWenForCausalLM</span>
|
||
<span class="kn">from</span><span class="w"> </span><span class="nn">tensorrt_llm.models.generation_mixin</span><span class="w"> </span><span class="kn">import</span> <span class="n">GenerationMixin</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="p">,</span> <span class="n">str_dtype_to_trt</span>
|
||
<span class="kn">from</span><span class="w"> </span><span class="nn">.drafter</span><span class="w"> </span><span class="kn">import</span> <span class="n">Drafter</span>
|
||
<span class="kn">from</span><span class="w"> </span><span class="nn">.redrafter_helper</span><span class="w"> </span><span class="kn">import</span> <span class="p">(</span><span class="n">_beam_search_candidates</span><span class="p">,</span> <span class="n">_beams2tree</span><span class="p">,</span>
|
||
<span class="n">_process_logits_and_hidden_states</span><span class="p">)</span>
|
||
|
||
|
||
<span class="k">class</span><span class="w"> </span><span class="nc">ReDrafterMixin</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="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">dtype</span> <span class="o">=</span> <span class="n">str_dtype_to_trt</span><span class="p">(</span><span class="n">config</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</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">drafter</span> <span class="o">=</span> <span class="n">Drafter</span><span class="o">.</span><span class="n">from_config</span><span class="p">(</span><span class="n">config</span><span class="p">,</span> <span class="n">vocab_size_padded</span><span class="p">)</span>
|
||
<span class="bp">self</span><span class="o">.</span><span class="n">num_beams</span> <span class="o">=</span> <span class="n">config</span><span class="o">.</span><span class="n">redrafter_num_beams</span>
|
||
<span class="bp">self</span><span class="o">.</span><span class="n">beam_candidate_length</span> <span class="o">=</span> <span class="n">config</span><span class="o">.</span><span class="n">redrafter_draft_len_per_beam</span>
|
||
<span class="bp">self</span><span class="o">.</span><span class="n">beam_length</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">beam_candidate_length</span> <span class="o">+</span> <span class="mi">1</span> <span class="c1"># including true token</span>
|
||
<span class="bp">self</span><span class="o">.</span><span class="n">greedy_search</span> <span class="o">=</span> <span class="n">config</span><span class="o">.</span><span class="n">redrafter_greedy_search</span>
|
||
<span class="bp">self</span><span class="o">.</span><span class="n">is_rnn</span> <span class="o">=</span> <span class="n">config</span><span class="o">.</span><span class="n">redrafter_is_rnn</span>
|
||
<span class="k">assert</span> <span class="bp">self</span><span class="o">.</span><span class="n">dtype</span> <span class="o">==</span> <span class="bp">self</span><span class="o">.</span><span class="n">drafter</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span> <span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">dtype</span><span class="si">}</span><span class="s2"> != </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">drafter</span><span class="o">.</span><span class="n">dtype</span><span class="si">}</span><span class="s2">"</span>
|
||
|
||
<span class="k">def</span><span class="w"> </span><span class="nf">_fwd_helper</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">hidden_states</span><span class="p">,</span> <span class="n">lm_logits</span><span class="p">,</span> <span class="n">embedding</span><span class="p">,</span> <span class="n">drafter</span><span class="p">,</span>
|
||
<span class="n">kwargs</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"> Must enable remove_input_padding:</span>
|
||
<span class="sd"> hidden_states [total_tokens, H]</span>
|
||
<span class="sd"> lm_logits [total_tokens, V]</span>
|
||
<span class="sd"> 1. process_logits: context vs gen</span>
|
||
<span class="sd"> a. Context: just return the last hidden states, and logits/probs</span>
|
||
<span class="sd"> b. Gen:</span>
|
||
<span class="sd"> i. verify: use lm_logits, draft_probs, draft_indices, draft_tokens</span>
|
||
<span class="sd"> ii. select hidden state and update probs</span>
|
||
<span class="sd"> 3. Sample token based on probs</span>
|
||
<span class="sd"> 4. Generate candidates using hidden_states, sampled token</span>
|
||
<span class="sd"> 5. Using beams, generate validation buffers, mark them as output</span>
|
||
<span class="sd"> 6. Mark all the outputs</span>
|
||
<span class="sd"> '''</span>
|
||
|
||
<span class="n">num_beams</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">num_beams</span>
|
||
<span class="n">beam_length</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">beam_length</span>
|
||
|
||
<span class="c1"># Get the inputs needed</span>
|
||
<span class="n">rand_data_sample</span> <span class="o">=</span> <span class="n">kwargs</span><span class="p">[</span><span class="s1">'rand_data_sample'</span><span class="p">]</span>
|
||
<span class="n">position_ids_base</span> <span class="o">=</span> <span class="n">kwargs</span><span class="p">[</span><span class="s1">'position_ids_base'</span><span class="p">]</span>
|
||
|
||
<span class="c1"># Step 1: Process logits and hidden states</span>
|
||
<span class="c1"># process the base model output (verify for gen-phase)</span>
|
||
<span class="n">probs</span><span class="p">,</span> <span class="n">draft_input</span><span class="p">,</span> <span class="n">num_accepted_tokens</span><span class="p">,</span> \
|
||
<span class="n">accepted_beam_index</span> <span class="o">=</span> <span class="n">_process_logits_and_hidden_states</span><span class="p">(</span>
|
||
<span class="bp">self</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">kwargs</span><span class="p">)</span>
|
||
<span class="c1"># NOTE: num_accepted_tokens doesn't include true token so add 1 here</span>
|
||
<span class="n">num_accepted_tokens</span> <span class="o">=</span> <span class="n">num_accepted_tokens</span> <span class="o">+</span> <span class="mi">1</span>
|
||
|
||
<span class="c1"># At this point:</span>
|
||
<span class="c1"># probs : [bs, V]</span>
|
||
<span class="c1"># hidden_states : [bs, H]</span>
|
||
|
||
<span class="c1"># Step 2: Sample token</span>
|
||
<span class="n">next_token</span> <span class="o">=</span> <span class="n">categorical_sample</span><span class="p">(</span><span class="n">probs</span><span class="p">,</span> <span class="n">rand_data_sample</span><span class="p">)</span>
|
||
|
||
<span class="c1"># Step 3: beam search</span>
|
||
<span class="n">new_draft_tokens</span><span class="p">,</span> <span class="n">new_draft_logits</span> <span class="o">=</span> <span class="n">_beam_search_candidates</span><span class="p">(</span>
|
||
<span class="n">draft_input</span><span class="p">,</span> <span class="n">next_token</span><span class="p">,</span> <span class="n">embedding</span><span class="p">,</span> <span class="n">drafter</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">num_beams</span><span class="p">,</span>
|
||
<span class="bp">self</span><span class="o">.</span><span class="n">beam_length</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">is_rnn</span><span class="p">)</span>
|
||
|
||
<span class="c1"># Step 4: tree processing</span>
|
||
<span class="n">active_tokens_flattened</span><span class="p">,</span> <span class="n">new_draft_token_indices</span><span class="p">,</span> <span class="n">new_mask</span><span class="p">,</span> \
|
||
<span class="n">new_position_offsets</span><span class="p">,</span> <span class="n">packed_position_ids</span><span class="p">,</span> <span class="n">next_num_gen_tokens</span><span class="p">,</span> <span class="n">max_gen_token</span><span class="p">,</span> \
|
||
<span class="n">total_gen_token</span> <span class="o">=</span> <span class="n">_beams2tree</span><span class="p">(</span><span class="n">new_draft_tokens</span><span class="p">,</span> <span class="n">num_beams</span><span class="p">,</span> <span class="n">beam_length</span><span class="p">,</span>
|
||
<span class="n">position_ids_base</span> <span class="o">+</span> <span class="n">num_accepted_tokens</span><span class="p">)</span>
|
||
|
||
<span class="c1"># Step 5: mark all the tensors we need</span>
|
||
<span class="n">num_accepted_tokens</span><span class="o">.</span><span class="n">mark_output</span><span class="p">(</span><span class="s1">'num_accepted_tokens'</span><span class="p">)</span>
|
||
<span class="n">accepted_beam_index</span><span class="o">.</span><span class="n">mark_output</span><span class="p">(</span><span class="s1">'accepted_beam_index'</span><span class="p">)</span>
|
||
<span class="n">max_gen_token</span><span class="o">.</span><span class="n">mark_output</span><span class="p">(</span><span class="s1">'max_gen_token'</span><span class="p">)</span>
|
||
<span class="n">total_gen_token</span><span class="o">.</span><span class="n">mark_output</span><span class="p">(</span><span class="s1">'total_gen_token'</span><span class="p">)</span>
|
||
<span class="n">next_num_gen_tokens</span><span class="o">.</span><span class="n">mark_output</span><span class="p">(</span><span class="s1">'next_spec_decoding_generation_lengths'</span><span class="p">)</span>
|
||
<span class="n">active_tokens_flattened</span><span class="o">.</span><span class="n">mark_output</span><span class="p">(</span><span class="s1">'next_flat_tokens'</span><span class="p">)</span>
|
||
<span class="n">new_draft_tokens</span><span class="o">.</span><span class="n">mark_output</span><span class="p">(</span><span class="s1">'next_draft_tokens'</span><span class="p">)</span>
|
||
<span class="n">new_draft_logits</span><span class="o">.</span><span class="n">mark_output</span><span class="p">(</span><span class="s1">'next_draft_probs'</span><span class="p">)</span>
|
||
<span class="n">new_draft_token_indices</span><span class="o">.</span><span class="n">mark_output</span><span class="p">(</span><span class="s1">'next_draft_indices'</span><span class="p">)</span>
|
||
<span class="n">new_mask</span><span class="o">.</span><span class="n">mark_output</span><span class="p">(</span><span class="s1">'spec_decoding_mask'</span><span class="p">)</span>
|
||
<span class="n">new_position_offsets</span><span class="o">.</span><span class="n">mark_output</span><span class="p">(</span><span class="s1">'next_spec_decoding_position_offsets'</span><span class="p">)</span>
|
||
<span class="n">packed_position_ids</span><span class="o">.</span><span class="n">mark_output</span><span class="p">(</span><span class="s1">'packed_position_ids'</span><span class="p">)</span>
|
||
|
||
<span class="k">return</span> <span class="n">next_token</span><span class="p">,</span> <span class="n">probs</span><span class="p">,</span> <span class="n">draft_input</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="w"> </span><span class="sd">"""</span>
|
||
<span class="sd"> 0. run base model, get logits, hidden_states</span>
|
||
<span class="sd"> """</span>
|
||
|
||
<span class="n">extra_args</span> <span class="o">=</span> <span class="p">[</span>
|
||
<span class="s1">'draft_tokens'</span><span class="p">,</span>
|
||
<span class="s1">'draft_indices'</span><span class="p">,</span>
|
||
<span class="s1">'draft_probs'</span><span class="p">,</span>
|
||
<span class="s1">'device_request_types'</span><span class="p">,</span>
|
||
<span class="s1">'redrafter_inverted_temperature'</span><span class="p">,</span>
|
||
<span class="s1">'rand_data_validation'</span><span class="p">,</span>
|
||
<span class="s1">'rand_data_sample'</span><span class="p">,</span>
|
||
<span class="s1">'position_ids_base'</span><span class="p">,</span>
|
||
<span class="p">]</span>
|
||
<span class="n">use_cache</span> <span class="o">=</span> <span class="kc">True</span>
|
||
<span class="n">base_kwargs</span> <span class="o">=</span> <span class="p">{</span><span class="n">k</span><span class="p">:</span> <span class="n">v</span> <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">items</span><span class="p">()</span> <span class="k">if</span> <span class="n">k</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">extra_args</span><span class="p">}</span>
|
||
<span class="k">if</span> <span class="n">use_cache</span> <span class="ow">and</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="ow">is</span> <span class="kc">False</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="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">base_kwargs</span><span class="p">)</span>
|
||
<span class="k">else</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="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">base_kwargs</span><span class="p">)</span>
|
||
|
||
<span class="c1"># lm_logits could be in fp32</span>
|
||
<span class="n">lm_logits_cast</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="n">lm_logits</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span> <span class="c1"># no-op if same type</span>
|
||
<span class="bp">self</span><span class="o">.</span><span class="n">register_network_output</span><span class="p">(</span><span class="s2">"hidden_states"</span><span class="p">,</span>
|
||
<span class="n">hidden_states</span><span class="p">)</span> <span class="c1"># debugging</span>
|
||
|
||
<span class="n">new_draft_tokens</span><span class="p">,</span> <span class="n">new_draft_logits</span><span class="p">,</span> <span class="n">probs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_fwd_helper</span><span class="p">(</span>
|
||
<span class="n">hidden_states</span><span class="p">,</span>
|
||
<span class="n">lm_logits_cast</span><span class="p">,</span>
|
||
<span class="bp">self</span><span class="o">.</span><span class="n">transformer</span><span class="o">.</span><span class="n">vocab_embedding</span><span class="p">,</span>
|
||
<span class="bp">self</span><span class="o">.</span><span class="n">drafter</span><span class="p">,</span>
|
||
<span class="n">kwargs</span><span class="o">=</span><span class="n">kwargs</span><span class="p">)</span>
|
||
|
||
<span class="k">return</span> <span class="n">new_draft_tokens</span><span class="p">,</span> <span class="n">new_draft_logits</span><span class="p">,</span> <span class="n">probs</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="w"> </span><span class="sd">"""</span>
|
||
<span class="sd"> Inputs needed:</span>
|
||
<span class="sd"> Assuming, max_gen_tokens = 1 + nb*(bl - 1), counting true token</span>
|
||
<span class="sd"> device_request_types: [bs]</span>
|
||
<span class="sd"> draft_tokens: [bs, nb, bl]</span>
|
||
<span class="sd"> draft_indices: [bs, nb, bl]</span>
|
||
<span class="sd"> draft_probs: [bs, nb, bl-1, V]</span>
|
||
<span class="sd"> spec_decoding_generation_lengths: [bs]</span>
|
||
<span class="sd"> spec_decoding_position_offsets: [bs, max_gen_tokens]</span>
|
||
<span class="sd"> spec_decoding_packed_mask: [bs, max_gen_tokens, packed_length] **</span>
|
||
<span class="sd"> redrafter_inverted_temperature: [bs]</span>
|
||
<span class="sd"> rand_data_sample: [bs]</span>
|
||
<span class="sd"> rand_data_validation: [bs, nb, bl-1]</span>
|
||
|
||
<span class="sd"> ** The mask is tricky since the boolean mask will need to be</span>
|
||
<span class="sd"> packed in runtime. So, the last dim will be:</span>
|
||
<span class="sd"> packed_length = ceil(max_gen_tokens/32)</span>
|
||
<span class="sd"> """</span>
|
||
<span class="n">default_range</span> <span class="o">=</span> <span class="n">GenerationMixin</span><span class="o">.</span><span class="n">default_range</span>
|
||
<span class="n">remove_input_padding</span> <span class="o">=</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">remove_input_padding</span>
|
||
<span class="n">use_gpt_attention_plugin</span> <span class="o">=</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">gpt_attention_plugin</span>
|
||
<span class="n">use_gemm_plugin</span> <span class="o">=</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">gemm_plugin</span>
|
||
<span class="n">paged_kv_cache</span> <span class="o">=</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="n">max_batch_size</span> <span class="o">=</span> <span class="n">kwargs</span><span class="p">[</span><span class="s1">'max_batch_size'</span><span class="p">]</span>
|
||
<span class="k">assert</span> <span class="n">max_batch_size</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span>
|
||
<span class="n">bb_range</span> <span class="o">=</span> <span class="n">default_range</span><span class="p">(</span><span class="n">max_batch_size</span><span class="p">)</span>
|
||
<span class="n">bb0_range</span> <span class="o">=</span> <span class="n">default_range</span><span class="p">(</span><span class="n">max_batch_size</span><span class="p">,</span> <span class="n">min_range</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">opt_offset</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
|
||
<span class="n">num_beam_tokens</span> <span class="o">=</span> <span class="bp">self</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">beam_length</span>
|
||
<span class="n">max_draft_len</span> <span class="o">=</span> <span class="n">num_beam_tokens</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">num_beams</span> <span class="c1"># ignore the true token</span>
|
||
<span class="n">max_gen_token_len</span> <span class="o">=</span> <span class="mi">1</span> <span class="o">+</span> <span class="n">max_draft_len</span> <span class="c1"># for the true token</span>
|
||
<span class="n">max_gen_token_len_range</span> <span class="o">=</span> <span class="n">default_range</span><span class="p">(</span><span class="n">max_gen_token_len</span><span class="p">)</span>
|
||
<span class="n">bb_max_gen_token_len_range</span> <span class="o">=</span> <span class="n">default_range</span><span class="p">(</span><span class="n">max_gen_token_len</span> <span class="o">*</span>
|
||
<span class="n">max_batch_size</span><span class="p">,</span>
|
||
<span class="n">min_range</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
|
||
|
||
<span class="n">kwargs</span><span class="p">[</span><span class="s1">'speculative_decoding_draft_tokens_external'</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">'max_draft_len'</span><span class="p">]</span> <span class="o">=</span> <span class="n">max_draft_len</span>
|
||
<span class="n">kwargs</span><span class="p">[</span><span class="s1">'spec_decoding_is_generation_length_variable'</span><span class="p">]</span> <span class="o">=</span> <span class="kc">True</span>
|
||
<span class="n">inputs</span> <span class="o">=</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="k">assert</span> <span class="n">inputs</span><span class="p">[</span><span class="s1">'spec_decoding_params'</span><span class="p">]</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span>
|
||
|
||
<span class="n">enable_two_optimization_profiles</span> <span class="o">=</span> <span class="n">GenerationMixin</span><span class="o">.</span><span class="n">has_ctx_gen_opt_profiles</span><span class="p">(</span>
|
||
<span class="n">use_gpt_attention_plugin</span><span class="o">=</span><span class="n">use_gpt_attention_plugin</span><span class="p">,</span>
|
||
<span class="n">use_gemm_plugin</span><span class="o">=</span><span class="n">use_gemm_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">kv_cache_type</span><span class="o">=</span><span class="n">KVCacheType</span><span class="o">.</span><span class="n">PAGED</span>
|
||
<span class="k">if</span> <span class="n">paged_kv_cache</span> <span class="k">else</span> <span class="n">KVCacheType</span><span class="o">.</span><span class="n">CONTINUOUS</span><span class="p">)</span>
|
||
<span class="k">if</span> <span class="n">enable_two_optimization_profiles</span><span class="p">:</span>
|
||
<span class="n">bb_range</span> <span class="o">=</span> <span class="p">[</span><span class="n">bb_range</span><span class="p">,</span> <span class="n">bb_range</span><span class="p">]</span>
|
||
<span class="n">bb0_range</span> <span class="o">=</span> <span class="p">[</span><span class="n">bb0_range</span><span class="p">,</span> <span class="n">bb0_range</span><span class="p">]</span>
|
||
<span class="n">max_gen_token_len_range</span> <span class="o">=</span> <span class="p">[</span>
|
||
<span class="n">max_gen_token_len_range</span><span class="p">,</span> <span class="n">max_gen_token_len_range</span>
|
||
<span class="p">]</span>
|
||
<span class="n">bb_max_gen_token_len_range</span> <span class="o">=</span> <span class="p">[</span>
|
||
<span class="n">bb_max_gen_token_len_range</span><span class="p">,</span> <span class="n">bb_max_gen_token_len_range</span>
|
||
<span class="p">]</span>
|
||
<span class="n">num_beams_range</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">num_beams</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">num_beams</span><span class="p">]</span>
|
||
<span class="n">beam_length_range</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">beam_length</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">beam_length</span><span class="p">]</span>
|
||
<span class="n">candidate_length_range</span> <span class="o">=</span> <span class="p">[</span>
|
||
<span class="bp">self</span><span class="o">.</span><span class="n">beam_candidate_length</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">beam_candidate_length</span>
|
||
<span class="p">]</span>
|
||
<span class="n">vocab_size_range</span> <span class="o">=</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="bp">self</span><span class="o">.</span><span class="n">vocab_size</span><span class="p">]</span>
|
||
<span class="k">else</span><span class="p">:</span>
|
||
<span class="n">bb_range</span> <span class="o">=</span> <span class="p">[</span><span class="n">bb_range</span><span class="p">]</span>
|
||
<span class="n">bb0_range</span> <span class="o">=</span> <span class="p">[</span><span class="n">bb0_range</span><span class="p">]</span>
|
||
<span class="n">max_gen_token_len_range</span> <span class="o">=</span> <span class="p">[</span><span class="n">max_gen_token_len_range</span><span class="p">]</span>
|
||
<span class="n">bb_max_gen_token_len_range</span> <span class="o">=</span> <span class="p">[</span><span class="n">bb_max_gen_token_len_range</span><span class="p">]</span>
|
||
<span class="n">num_beams_range</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">num_beams</span><span class="p">]</span>
|
||
<span class="n">beam_length_range</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">beam_length</span><span class="p">]</span>
|
||
<span class="n">candidate_length_range</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">beam_candidate_length</span><span class="p">]</span>
|
||
<span class="n">vocab_size_range</span> <span class="o">=</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">device_request_types</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s1">'device_request_types'</span><span class="p">,</span>
|
||
<span class="n">dtype</span><span class="o">=</span><span class="n">trt</span><span class="o">.</span><span class="n">int32</span><span class="p">,</span>
|
||
<span class="n">shape</span><span class="o">=</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">],</span>
|
||
<span class="n">dim_range</span><span class="o">=</span><span class="n">OrderedDict</span><span class="p">([</span>
|
||
<span class="p">(</span><span class="s1">'batch_size'</span><span class="p">,</span> <span class="n">bb_range</span><span class="p">),</span>
|
||
<span class="p">]))</span>
|
||
<span class="n">draft_tokens</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s1">'draft_tokens'</span><span class="p">,</span>
|
||
<span class="n">dtype</span><span class="o">=</span><span class="n">trt</span><span class="o">.</span><span class="n">int32</span><span class="p">,</span>
|
||
<span class="n">shape</span><span class="o">=</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">num_beams</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">beam_length</span><span class="p">],</span>
|
||
<span class="n">dim_range</span><span class="o">=</span><span class="n">OrderedDict</span><span class="p">([</span>
|
||
<span class="p">(</span><span class="s1">'batch_size_wt0'</span><span class="p">,</span> <span class="n">bb0_range</span><span class="p">),</span>
|
||
<span class="p">(</span><span class="s1">'num_beams'</span><span class="p">,</span> <span class="n">num_beams_range</span><span class="p">),</span>
|
||
<span class="p">(</span><span class="s1">'beam_length'</span><span class="p">,</span> <span class="n">beam_length_range</span><span class="p">),</span>
|
||
<span class="p">]))</span>
|
||
<span class="n">draft_indices</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s1">'draft_indices'</span><span class="p">,</span>
|
||
<span class="n">dtype</span><span class="o">=</span><span class="n">trt</span><span class="o">.</span><span class="n">int32</span><span class="p">,</span>
|
||
<span class="n">shape</span><span class="o">=</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">num_beams</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">beam_length</span><span class="p">],</span>
|
||
<span class="n">dim_range</span><span class="o">=</span><span class="n">OrderedDict</span><span class="p">([</span>
|
||
<span class="p">(</span><span class="s1">'batch_size_wt0'</span><span class="p">,</span> <span class="n">bb0_range</span><span class="p">),</span>
|
||
<span class="p">(</span><span class="s1">'num_beams'</span><span class="p">,</span> <span class="n">num_beams_range</span><span class="p">),</span>
|
||
<span class="p">(</span><span class="s1">'beam_length'</span><span class="p">,</span> <span class="n">beam_length_range</span><span class="p">),</span>
|
||
<span class="p">]))</span>
|
||
<span class="n">draft_probs</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">(</span>
|
||
<span class="n">name</span><span class="o">=</span><span class="s1">'draft_probs'</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">shape</span><span class="o">=</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">num_beams</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">beam_length</span> <span class="o">-</span> <span class="mi">1</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">vocab_size</span><span class="p">],</span>
|
||
<span class="n">dim_range</span><span class="o">=</span><span class="n">OrderedDict</span><span class="p">([</span>
|
||
<span class="p">(</span><span class="s1">'batch_size_wt0'</span><span class="p">,</span> <span class="n">bb0_range</span><span class="p">),</span>
|
||
<span class="p">(</span><span class="s1">'num_beams'</span><span class="p">,</span> <span class="n">num_beams_range</span><span class="p">),</span>
|
||
<span class="p">(</span><span class="s1">'candidate_length'</span><span class="p">,</span> <span class="n">candidate_length_range</span><span class="p">),</span>
|
||
<span class="p">(</span><span class="s1">'vocab_size'</span><span class="p">,</span> <span class="n">vocab_size_range</span><span class="p">),</span>
|
||
<span class="p">]))</span>
|
||
<span class="n">redrafter_inverted_temperature</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">(</span>
|
||
<span class="n">name</span><span class="o">=</span><span class="s1">'redrafter_inverted_temperature'</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">shape</span><span class="o">=</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">],</span>
|
||
<span class="n">dim_range</span><span class="o">=</span><span class="n">OrderedDict</span><span class="p">([</span>
|
||
<span class="p">(</span><span class="s2">"batch_size"</span><span class="p">,</span> <span class="n">bb_range</span><span class="p">),</span>
|
||
<span class="p">]))</span>
|
||
<span class="n">rand_data_validation</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">(</span>
|
||
<span class="n">name</span><span class="o">=</span><span class="s1">'rand_data_validation'</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">shape</span><span class="o">=</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">num_beams</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">beam_length</span> <span class="o">-</span> <span class="mi">1</span><span class="p">],</span>
|
||
<span class="n">dim_range</span><span class="o">=</span><span class="n">OrderedDict</span><span class="p">([</span>
|
||
<span class="p">(</span><span class="s1">'batch_size_wt0'</span><span class="p">,</span> <span class="n">bb0_range</span><span class="p">),</span>
|
||
<span class="p">(</span><span class="s1">'num_beams'</span><span class="p">,</span> <span class="n">num_beams_range</span><span class="p">),</span>
|
||
<span class="p">(</span><span class="s1">'candidate_length'</span><span class="p">,</span> <span class="n">candidate_length_range</span><span class="p">),</span>
|
||
<span class="p">]))</span>
|
||
<span class="n">rand_data_sample</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s1">'rand_data_sample'</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">shape</span><span class="o">=</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">],</span>
|
||
<span class="n">dim_range</span><span class="o">=</span><span class="n">OrderedDict</span><span class="p">([</span>
|
||
<span class="p">(</span><span class="s1">'batch_size'</span><span class="p">,</span> <span class="n">bb_range</span><span class="p">),</span>
|
||
<span class="p">]))</span>
|
||
<span class="n">position_ids_base</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">(</span>
|
||
<span class="n">name</span><span class="o">=</span><span class="s2">"position_ids_base"</span><span class="p">,</span>
|
||
<span class="n">dtype</span><span class="o">=</span><span class="n">trt</span><span class="o">.</span><span class="n">int32</span><span class="p">,</span>
|
||
<span class="n">shape</span><span class="o">=</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">],</span>
|
||
<span class="n">dim_range</span><span class="o">=</span><span class="n">OrderedDict</span><span class="p">([</span>
|
||
<span class="p">(</span><span class="s2">"batch_size"</span><span class="p">,</span> <span class="n">bb_range</span><span class="p">),</span>
|
||
<span class="p">]),</span>
|
||
<span class="p">)</span>
|
||
|
||
<span class="n">inputs</span><span class="p">[</span>
|
||
<span class="s1">'device_request_types'</span><span class="p">]</span> <span class="o">=</span> <span class="n">device_request_types</span> <span class="c1"># needed by process_logits</span>
|
||
<span class="n">inputs</span><span class="p">[</span><span class="s1">'draft_tokens'</span><span class="p">]</span> <span class="o">=</span> <span class="n">draft_tokens</span>
|
||
<span class="n">inputs</span><span class="p">[</span><span class="s1">'draft_indices'</span><span class="p">]</span> <span class="o">=</span> <span class="n">draft_indices</span>
|
||
<span class="n">inputs</span><span class="p">[</span><span class="s1">'draft_probs'</span><span class="p">]</span> <span class="o">=</span> <span class="n">draft_probs</span>
|
||
<span class="n">inputs</span><span class="p">[</span>
|
||
<span class="s1">'redrafter_inverted_temperature'</span><span class="p">]</span> <span class="o">=</span> <span class="n">redrafter_inverted_temperature</span>
|
||
<span class="n">inputs</span><span class="p">[</span><span class="s1">'rand_data_validation'</span><span class="p">]</span> <span class="o">=</span> <span class="n">rand_data_validation</span>
|
||
<span class="n">inputs</span><span class="p">[</span><span class="s1">'rand_data_sample'</span><span class="p">]</span> <span class="o">=</span> <span class="n">rand_data_sample</span>
|
||
<span class="n">inputs</span><span class="p">[</span><span class="s1">'position_ids_base'</span><span class="p">]</span> <span class="o">=</span> <span class="n">position_ids_base</span>
|
||
<span class="k">return</span> <span class="n">inputs</span>
|
||
|
||
|
||
<div class="viewcode-block" id="ReDrafterForQWenLM">
|
||
<a class="viewcode-back" href="../../../../python-api/tensorrt_llm.models.html#tensorrt_llm.models.ReDrafterForQWenLM">[docs]</a>
|
||
<span class="k">class</span><span class="w"> </span><span class="nc">ReDrafterForQWenLM</span><span class="p">(</span><span class="n">ReDrafterMixin</span><span class="p">,</span> <span class="n">QWenForCausalLM</span><span class="p">):</span>
|
||
<span class="w"> </span><span class="sd">"""ReDrafter implementation for QWen models.</span>
|
||
|
||
<span class="sd"> Combines:</span>
|
||
<span class="sd"> - Base QWen model functionality from QWenForCausalLM</span>
|
||
<span class="sd"> - Drafting/speculative decoding logic from ReDrafterMixin</span>
|
||
<span class="sd"> """</span></div>
|
||
|
||
|
||
|
||
<div class="viewcode-block" id="ReDrafterForLLaMALM">
|
||
<a class="viewcode-back" href="../../../../python-api/tensorrt_llm.models.html#tensorrt_llm.models.ReDrafterForLLaMALM">[docs]</a>
|
||
<span class="k">class</span><span class="w"> </span><span class="nc">ReDrafterForLLaMALM</span><span class="p">(</span><span class="n">ReDrafterMixin</span><span class="p">,</span> <span class="n">LLaMAForCausalLM</span><span class="p">):</span>
|
||
<span class="w"> </span><span class="sd">"""ReDrafter implementation for LLaMA models.</span>
|
||
|
||
<span class="sd"> Combines:</span>
|
||
<span class="sd"> - Base LLaMA model functionality from LLaMAForCausalLM</span>
|
||
<span class="sd"> - Drafting/speculative decoding logic from ReDrafterMixin</span>
|
||
<span class="sd"> """</span></div>
|
||
|
||
</pre></div>
|
||
|
||
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<p>Last updated on September 15, 2025.</p>
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<p>This page is generated by TensorRT-LLM commit <a href="https://github.com/NVIDIA/TensorRT-LLM/tree/0c9430e">0c9430e</a>.</p>
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