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<h1>Source code for tensorrt_llm.layers.linear</h1><div class="highlight"><pre>
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<span></span><span class="c1"># SPDX-FileCopyrightText: Copyright (c) 2022-2023 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">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">from</span> <span class="nn">.._common</span> <span class="kn">import</span> <span class="n">default_net</span><span class="p">,</span> <span class="n">default_trtnet</span>
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<span class="kn">from</span> <span class="nn">.._utils</span> <span class="kn">import</span> <span class="n">int32_array</span><span class="p">,</span> <span class="n">str_dtype_to_trt</span>
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<span class="kn">from</span> <span class="nn">..functional</span> <span class="kn">import</span> <span class="p">(</span><span class="n">Tensor</span><span class="p">,</span> <span class="n">_create_tensor</span><span class="p">,</span> <span class="n">allgather</span><span class="p">,</span> <span class="n">allreduce</span><span class="p">,</span> <span class="n">cast</span><span class="p">,</span>
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<span class="n">concat</span><span class="p">,</span> <span class="n">constant</span><span class="p">,</span> <span class="n">matmul</span><span class="p">,</span> <span class="n">shape</span><span class="p">,</span> <span class="nb">slice</span><span class="p">)</span>
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<span class="kn">from</span> <span class="nn">..module</span> <span class="kn">import</span> <span class="n">Module</span>
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<span class="kn">from</span> <span class="nn">..parameter</span> <span class="kn">import</span> <span class="n">Parameter</span>
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<span class="kn">from</span> <span class="nn">..plugin</span> <span class="kn">import</span> <span class="n">TRT_LLM_PLUGIN_NAMESPACE</span>
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<span class="k">def</span> <span class="nf">_gemm_plugin</span><span class="p">(</span><span class="nb">input</span><span class="p">:</span> <span class="n">Tensor</span><span class="p">,</span>
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<span class="n">mat2</span><span class="p">:</span> <span class="n">Tensor</span><span class="p">,</span>
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<span class="n">transa</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
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<span class="n">transb</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
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<span class="n">use_fp8</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="o">-></span> <span class="n">Tensor</span><span class="p">:</span>
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<span class="n">plg_creator</span> <span class="o">=</span> <span class="n">trt</span><span class="o">.</span><span class="n">get_plugin_registry</span><span class="p">()</span><span class="o">.</span><span class="n">get_plugin_creator</span><span class="p">(</span>
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<span class="s1">'Gemm'</span><span class="p">,</span> <span class="s1">'1'</span><span class="p">,</span> <span class="n">TRT_LLM_PLUGIN_NAMESPACE</span><span class="p">)</span>
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<span class="k">assert</span> <span class="n">plg_creator</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span>
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<span class="n">transa</span> <span class="o">=</span> <span class="mi">1</span> <span class="k">if</span> <span class="n">transa</span> <span class="k">else</span> <span class="mi">0</span>
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<span class="n">transa</span> <span class="o">=</span> <span class="n">trt</span><span class="o">.</span><span class="n">PluginField</span><span class="p">(</span><span class="s2">"transa"</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">transa</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">int32</span><span class="p">),</span>
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<span class="n">trt</span><span class="o">.</span><span class="n">PluginFieldType</span><span class="o">.</span><span class="n">INT32</span><span class="p">)</span>
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<span class="n">transb</span> <span class="o">=</span> <span class="mi">1</span> <span class="k">if</span> <span class="n">transb</span> <span class="k">else</span> <span class="mi">0</span>
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<span class="n">transb</span> <span class="o">=</span> <span class="n">trt</span><span class="o">.</span><span class="n">PluginField</span><span class="p">(</span><span class="s2">"transb"</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">transb</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">int32</span><span class="p">),</span>
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<span class="n">trt</span><span class="o">.</span><span class="n">PluginFieldType</span><span class="o">.</span><span class="n">INT32</span><span class="p">)</span>
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<span class="n">use_fp8</span> <span class="o">=</span> <span class="mi">1</span> <span class="k">if</span> <span class="n">use_fp8</span> <span class="k">else</span> <span class="mi">0</span>
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<span class="n">use_fp8</span> <span class="o">=</span> <span class="n">trt</span><span class="o">.</span><span class="n">PluginField</span><span class="p">(</span><span class="s2">"use_fp8"</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">use_fp8</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">int32</span><span class="p">),</span>
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<span class="n">trt</span><span class="o">.</span><span class="n">PluginFieldType</span><span class="o">.</span><span class="n">INT32</span><span class="p">)</span>
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<span class="n">p_dtype</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>
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<span class="n">pf_type</span> <span class="o">=</span> <span class="n">trt</span><span class="o">.</span><span class="n">PluginField</span><span class="p">(</span>
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<span class="s2">"type_id"</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="nb">int</span><span class="p">(</span><span class="n">str_dtype_to_trt</span><span class="p">(</span><span class="n">p_dtype</span><span class="p">))],</span> <span class="n">np</span><span class="o">.</span><span class="n">int32</span><span class="p">),</span>
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<span class="n">trt</span><span class="o">.</span><span class="n">PluginFieldType</span><span class="o">.</span><span class="n">INT32</span><span class="p">)</span>
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<span class="n">pfc</span> <span class="o">=</span> <span class="n">trt</span><span class="o">.</span><span class="n">PluginFieldCollection</span><span class="p">([</span><span class="n">transa</span><span class="p">,</span> <span class="n">transb</span><span class="p">,</span> <span class="n">pf_type</span><span class="p">,</span> <span class="n">use_fp8</span><span class="p">])</span>
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<span class="n">gemm_plug</span> <span class="o">=</span> <span class="n">plg_creator</span><span class="o">.</span><span class="n">create_plugin</span><span class="p">(</span><span class="s2">"gemm"</span><span class="p">,</span> <span class="n">pfc</span><span class="p">)</span>
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<span class="n">plug_inputs</span> <span class="o">=</span> <span class="p">[</span><span class="nb">input</span><span class="o">.</span><span class="n">trt_tensor</span><span class="p">,</span> <span class="n">mat2</span><span class="o">.</span><span class="n">trt_tensor</span><span class="p">]</span>
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<span class="n">layer</span> <span class="o">=</span> <span class="n">default_trtnet</span><span class="p">()</span><span class="o">.</span><span class="n">add_plugin_v2</span><span class="p">(</span><span class="n">plug_inputs</span><span class="p">,</span> <span class="n">gemm_plug</span><span class="p">)</span>
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<span class="k">return</span> <span class="n">_create_tensor</span><span class="p">(</span><span class="n">layer</span><span class="o">.</span><span class="n">get_output</span><span class="p">(</span><span class="mi">0</span><span class="p">),</span> <span class="n">layer</span><span class="p">)</span>
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<div class="viewcode-block" id="Linear">
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<a class="viewcode-back" href="../../../python-api/tensorrt_llm.layers.html#tensorrt_llm.layers.linear.Linear">[docs]</a>
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<span class="k">class</span> <span class="nc">Linear</span><span class="p">(</span><span class="n">Module</span><span class="p">):</span>
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<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span>
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<span class="n">in_features</span><span class="p">,</span>
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<span class="n">out_features</span><span class="p">,</span>
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<span class="n">bias</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
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<span class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
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<span class="n">tp_group</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
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<span class="n">tp_size</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span>
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<span class="n">gather_output</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
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<span class="n">share_weight</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
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<span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>
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<span class="bp">self</span><span class="o">.</span><span class="n">in_features</span> <span class="o">=</span> <span class="n">in_features</span>
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<span class="bp">self</span><span class="o">.</span><span class="n">out_features</span> <span class="o">=</span> <span class="n">out_features</span> <span class="o">//</span> <span class="n">tp_size</span>
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<span class="bp">self</span><span class="o">.</span><span class="n">dtype</span> <span class="o">=</span> <span class="n">dtype</span>
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<span class="k">if</span> <span class="ow">not</span> <span class="n">share_weight</span><span class="p">:</span>
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<span class="bp">self</span><span class="o">.</span><span class="n">weight</span> <span class="o">=</span> <span class="n">Parameter</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">out_features</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">in_features</span><span class="p">),</span>
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<span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">)</span>
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<span class="k">else</span><span class="p">:</span>
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<span class="bp">self</span><span class="o">.</span><span class="n">weight</span> <span class="o">=</span> <span class="n">share_weight</span>
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<span class="bp">self</span><span class="o">.</span><span class="n">tp_size</span> <span class="o">=</span> <span class="n">tp_size</span>
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<span class="bp">self</span><span class="o">.</span><span class="n">tp_group</span> <span class="o">=</span> <span class="n">tp_group</span>
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<span class="bp">self</span><span class="o">.</span><span class="n">gather_output</span> <span class="o">=</span> <span class="n">gather_output</span>
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<span class="k">if</span> <span class="n">bias</span><span class="p">:</span>
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<span class="bp">self</span><span class="o">.</span><span class="n">bias</span> <span class="o">=</span> <span class="n">Parameter</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">out_features</span><span class="p">,</span> <span class="p">),</span> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">)</span>
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<span class="k">else</span><span class="p">:</span>
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<span class="bp">self</span><span class="o">.</span><span class="n">register_parameter</span><span class="p">(</span><span class="s1">'bias'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
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<div class="viewcode-block" id="Linear.multiply_gather">
|
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<a class="viewcode-back" href="../../../python-api/tensorrt_llm.layers.html#tensorrt_llm.layers.linear.Linear.multiply_gather">[docs]</a>
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<span class="k">def</span> <span class="nf">multiply_gather</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">weight</span><span class="p">,</span> <span class="n">gemm_plugin</span><span class="p">,</span> <span class="n">use_fp8</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
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<span class="k">if</span> <span class="n">gemm_plugin</span><span class="p">:</span>
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|
<span class="n">x</span> <span class="o">=</span> <span class="n">_gemm_plugin</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">transb</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">use_fp8</span><span class="o">=</span><span class="n">use_fp8</span><span class="p">)</span>
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<span class="k">else</span><span class="p">:</span>
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|
<span class="n">x</span> <span class="o">=</span> <span class="n">matmul</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">transb</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
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<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">bias</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
|
<span class="k">if</span> <span class="n">x</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">bias</span><span class="o">.</span><span class="n">value</span><span class="o">.</span><span class="n">dtype</span><span class="p">:</span>
|
|
<span class="n">x</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">bias</span><span class="o">.</span><span class="n">value</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span>
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<span class="n">x</span> <span class="o">=</span> <span class="n">x</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">bias</span><span class="o">.</span><span class="n">value</span>
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<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">gather_output</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">tp_size</span> <span class="o">></span> <span class="mi">1</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">tp_group</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
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<span class="c1"># 1. [dim0, local_dim] -> [dim0 * tp_size, local_dim]</span>
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|
<span class="n">x</span> <span class="o">=</span> <span class="n">allgather</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tp_group</span><span class="p">)</span>
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<span class="c1"># 2. [dim0 * tp_size, local_dim] -> [dim0, local_dim * tp_size]</span>
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<span class="c1"># 2.1 split</span>
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<span class="n">split_size</span> <span class="o">=</span> <span class="n">shape</span><span class="p">(</span><span class="n">x</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="bp">self</span><span class="o">.</span><span class="n">tp_size</span>
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<span class="n">ndim</span> <span class="o">=</span> <span class="n">x</span><span class="o">.</span><span class="n">ndim</span><span class="p">()</span>
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|
<span class="n">starts</span> <span class="o">=</span> <span class="p">[</span><span class="n">constant</span><span class="p">(</span><span class="n">int32_array</span><span class="p">([</span><span class="mi">0</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">ndim</span><span class="p">)]</span>
|
|
<span class="n">sizes</span> <span class="o">=</span> <span class="p">[</span><span class="n">shape</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="n">d</span><span class="p">)</span> <span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">ndim</span><span class="p">)]</span>
|
|
<span class="n">sizes</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="n">split_size</span>
|
|
<span class="n">sections</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">tp_size</span><span class="p">):</span>
|
|
<span class="n">starts</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="n">split_size</span> <span class="o">*</span> <span class="n">i</span>
|
|
<span class="n">sections</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">slice</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">concat</span><span class="p">(</span><span class="n">starts</span><span class="p">),</span> <span class="n">concat</span><span class="p">(</span><span class="n">sizes</span><span class="p">)))</span>
|
|
<span class="c1"># 2.2 concat</span>
|
|
<span class="n">x</span> <span class="o">=</span> <span class="n">concat</span><span class="p">(</span><span class="n">sections</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="k">return</span> <span class="n">x</span></div>
|
|
|
|
|
|
<div class="viewcode-block" id="Linear.forward">
|
|
<a class="viewcode-back" href="../../../python-api/tensorrt_llm.layers.html#tensorrt_llm.layers.linear.Linear.forward">[docs]</a>
|
|
<span class="k">def</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="bp">self</span><span class="o">.</span><span class="n">multiply_gather</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">weight</span><span class="o">.</span><span class="n">value</span><span class="p">,</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="p">)</span></div>
|
|
</div>
|
|
|
|
|
|
|
|
<span class="n">ColumnLinear</span> <span class="o">=</span> <span class="n">Linear</span>
|
|
|
|
|
|
<div class="viewcode-block" id="RowLinear">
|
|
<a class="viewcode-back" href="../../../python-api/tensorrt_llm.layers.html#tensorrt_llm.layers.linear.RowLinear">[docs]</a>
|
|
<span class="k">class</span> <span class="nc">RowLinear</span><span class="p">(</span><span class="n">Module</span><span class="p">):</span>
|
|
|
|
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span>
|
|
<span class="n">in_features</span><span class="p">,</span>
|
|
<span class="n">out_features</span><span class="p">,</span>
|
|
<span class="n">bias</span><span class="o">=</span><span class="kc">True</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">tp_group</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
|
|
<span class="n">tp_size</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span>
|
|
<span class="n">instance_id</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="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">in_features</span> <span class="o">=</span> <span class="n">in_features</span> <span class="o">//</span> <span class="n">tp_size</span>
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">out_features</span> <span class="o">=</span> <span class="n">out_features</span>
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">dtype</span> <span class="o">=</span> <span class="n">dtype</span>
|
|
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">weight</span> <span class="o">=</span> <span class="n">Parameter</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">out_features</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">in_features</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="k">if</span> <span class="n">bias</span><span class="p">:</span>
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">bias</span> <span class="o">=</span> <span class="n">Parameter</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">out_features</span><span class="p">,</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="k">else</span><span class="p">:</span>
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">register_parameter</span><span class="p">(</span><span class="s1">'bias'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
|
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">tp_group</span> <span class="o">=</span> <span class="n">tp_group</span>
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">tp_size</span> <span class="o">=</span> <span class="n">tp_size</span>
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">instance_id</span> <span class="o">=</span> <span class="n">instance_id</span>
|
|
|
|
<div class="viewcode-block" id="RowLinear.multiply_reduce">
|
|
<a class="viewcode-back" href="../../../python-api/tensorrt_llm.layers.html#tensorrt_llm.layers.linear.RowLinear.multiply_reduce">[docs]</a>
|
|
<span class="k">def</span> <span class="nf">multiply_reduce</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">weight</span><span class="p">,</span>
|
|
<span class="n">gemm_plugin</span><span class="p">,</span>
|
|
<span class="n">use_fp8</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
|
|
<span class="n">workspace</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
|
<span class="k">if</span> <span class="n">gemm_plugin</span><span class="p">:</span>
|
|
<span class="n">x</span> <span class="o">=</span> <span class="n">_gemm_plugin</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">transb</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">use_fp8</span><span class="o">=</span><span class="n">use_fp8</span><span class="p">)</span>
|
|
<span class="k">else</span><span class="p">:</span>
|
|
<span class="n">x</span> <span class="o">=</span> <span class="n">matmul</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">weight</span><span class="p">,</span> <span class="n">transb</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
|
|
|
|
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">tp_size</span> <span class="o">></span> <span class="mi">1</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">tp_group</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
|
<span class="n">x</span> <span class="o">=</span> <span class="n">allreduce</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">tp_group</span><span class="p">,</span> <span class="n">workspace</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">instance_id</span><span class="p">)</span>
|
|
|
|
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">bias</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
|
<span class="k">if</span> <span class="n">x</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">bias</span><span class="o">.</span><span class="n">value</span><span class="o">.</span><span class="n">dtype</span><span class="p">:</span>
|
|
<span class="n">x</span> <span class="o">=</span> <span class="n">cast</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">bias</span><span class="o">.</span><span class="n">value</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span>
|
|
|
|
<span class="n">x</span> <span class="o">=</span> <span class="n">x</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">bias</span><span class="o">.</span><span class="n">value</span>
|
|
|
|
<span class="k">return</span> <span class="n">x</span></div>
|
|
|
|
|
|
<div class="viewcode-block" id="RowLinear.forward">
|
|
<a class="viewcode-back" href="../../../python-api/tensorrt_llm.layers.html#tensorrt_llm.layers.linear.RowLinear.forward">[docs]</a>
|
|
<span class="k">def</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">workspace</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
|
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">multiply_reduce</span><span class="p">(</span><span class="n">x</span><span class="p">,</span>
|
|
<span class="bp">self</span><span class="o">.</span><span class="n">weight</span><span class="o">.</span><span class="n">value</span><span class="p">,</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="p">,</span>
|
|
<span class="n">workspace</span><span class="o">=</span><span class="n">workspace</span><span class="p">)</span></div>
|
|
</div>
|
|
|
|
</pre></div>
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