mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
synced 2026-01-14 06:27:45 +08:00
720 lines
108 KiB
HTML
720 lines
108 KiB
HTML
<!DOCTYPE html>
|
|
<html class="writer-html5" lang="en" data-content_root="../../../../">
|
|
<head>
|
|
<meta charset="utf-8" />
|
|
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
|
<title>tensorrt_llm.models.quantized.quant — tensorrt_llm documentation</title>
|
|
<link rel="stylesheet" type="text/css" href="../../../../_static/pygments.css?v=80d5e7a1" />
|
|
<link rel="stylesheet" type="text/css" href="../../../../_static/css/theme.css?v=19f00094" />
|
|
|
|
|
|
<!--[if lt IE 9]>
|
|
<script src="../../../../_static/js/html5shiv.min.js"></script>
|
|
<![endif]-->
|
|
|
|
<script src="../../../../_static/jquery.js?v=5d32c60e"></script>
|
|
<script src="../../../../_static/_sphinx_javascript_frameworks_compat.js?v=2cd50e6c"></script>
|
|
<script src="../../../../_static/documentation_options.js?v=5929fcd5"></script>
|
|
<script src="../../../../_static/doctools.js?v=888ff710"></script>
|
|
<script src="../../../../_static/sphinx_highlight.js?v=dc90522c"></script>
|
|
<script src="../../../../_static/js/theme.js"></script>
|
|
<link rel="index" title="Index" href="../../../../genindex.html" />
|
|
<link rel="search" title="Search" href="../../../../search.html" />
|
|
</head>
|
|
|
|
<body class="wy-body-for-nav">
|
|
<div class="wy-grid-for-nav">
|
|
<nav data-toggle="wy-nav-shift" class="wy-nav-side">
|
|
<div class="wy-side-scroll">
|
|
<div class="wy-side-nav-search" >
|
|
|
|
|
|
|
|
<a href="../../../../index.html" class="icon icon-home">
|
|
tensorrt_llm
|
|
</a>
|
|
<div role="search">
|
|
<form id="rtd-search-form" class="wy-form" action="../../../../search.html" method="get">
|
|
<input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
|
|
<input type="hidden" name="check_keywords" value="yes" />
|
|
<input type="hidden" name="area" value="default" />
|
|
</form>
|
|
</div>
|
|
</div><div class="wy-menu wy-menu-vertical" data-spy="affix" role="navigation" aria-label="Navigation menu">
|
|
<p class="caption" role="heading"><span class="caption-text">Getting Started</span></p>
|
|
<ul>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../overview.html">Overview</a></li>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../quick-start-guide.html">Quick Start Guide</a></li>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../release-notes.html">Release Notes</a></li>
|
|
</ul>
|
|
<p class="caption" role="heading"><span class="caption-text">Installation</span></p>
|
|
<ul>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../installation/linux.html">Installing on Linux</a></li>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../installation/build-from-source-linux.html">Building from Source Code on Linux</a></li>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../installation/windows.html">Installing on Windows</a></li>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../installation/build-from-source-windows.html">Building from Source Code on Windows</a></li>
|
|
</ul>
|
|
<p class="caption" role="heading"><span class="caption-text">Architecture</span></p>
|
|
<ul>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../architecture/overview.html">TensorRT-LLM Architecture</a></li>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../architecture/core-concepts.html">Model Definition</a></li>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../architecture/core-concepts.html#compilation">Compilation</a></li>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../architecture/core-concepts.html#runtime">Runtime</a></li>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../architecture/core-concepts.html#multi-gpu-and-multi-node-support">Multi-GPU and Multi-Node Support</a></li>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../architecture/checkpoint.html">TensorRT-LLM Checkpoint</a></li>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../architecture/workflow.html">TensorRT-LLM Build Workflow</a></li>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../architecture/add-model.html">Adding a Model</a></li>
|
|
</ul>
|
|
<p class="caption" role="heading"><span class="caption-text">Advanced</span></p>
|
|
<ul>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../advanced/gpt-attention.html">Multi-Head, Multi-Query, and Group-Query Attention</a></li>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../advanced/gpt-runtime.html">C++ GPT Runtime</a></li>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../advanced/graph-rewriting.html">Graph Rewriting Module</a></li>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../advanced/batch-manager.html">The Batch Manager in TensorRT-LLM</a></li>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../advanced/inference-request.html">Inference Request</a></li>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../advanced/lora.html">Run gpt-2b + LoRA using GptManager / cpp runtime</a></li>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../advanced/expert-parallelism.html">Expert Parallelism in TensorRT-LLM</a></li>
|
|
</ul>
|
|
<p class="caption" role="heading"><span class="caption-text">Performance</span></p>
|
|
<ul>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../performance/perf-overview.html">Overview</a></li>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../performance/perf-best-practices.html">Best Practices for Tuning the Performance of TensorRT-LLM</a></li>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../performance/perf-analysis.html">Performance Analysis</a></li>
|
|
</ul>
|
|
<p class="caption" role="heading"><span class="caption-text">Reference</span></p>
|
|
<ul>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../reference/troubleshooting.html">Troubleshooting</a></li>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../reference/support-matrix.html">Support Matrix</a></li>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../reference/precision.html">Numerical Precision</a></li>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../reference/memory.html">Memory Usage of TensorRT-LLM</a></li>
|
|
</ul>
|
|
<p class="caption" role="heading"><span class="caption-text">C++ API</span></p>
|
|
<ul>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../_cpp_gen/runtime.html">Runtime</a></li>
|
|
</ul>
|
|
<p class="caption" role="heading"><span class="caption-text">Python API</span></p>
|
|
<ul>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../python-api/tensorrt_llm.layers.html">Layers</a></li>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../python-api/tensorrt_llm.functional.html">Functionals</a></li>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../python-api/tensorrt_llm.models.html">Models</a></li>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../python-api/tensorrt_llm.plugin.html">Plugin</a></li>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../python-api/tensorrt_llm.quantization.html">Quantization</a></li>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../python-api/tensorrt_llm.runtime.html">Runtime</a></li>
|
|
</ul>
|
|
<p class="caption" role="heading"><span class="caption-text">Blogs</span></p>
|
|
<ul>
|
|
<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>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../blogs/Falcon180B-H200.html">Falcon-180B on a single H200 GPU with INT4 AWQ, and 6.7x faster Llama-70B over A100</a></li>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../blogs/quantization-in-TRT-LLM.html">Speed up inference with SOTA quantization techniques in TRT-LLM</a></li>
|
|
<li class="toctree-l1"><a class="reference internal" href="../../../../blogs/XQA-kernel.html">New XQA-kernel provides 2.4x more Llama-70B throughput within the same latency budget</a></li>
|
|
</ul>
|
|
|
|
</div>
|
|
</div>
|
|
</nav>
|
|
|
|
<section data-toggle="wy-nav-shift" class="wy-nav-content-wrap"><nav class="wy-nav-top" aria-label="Mobile navigation menu" >
|
|
<i data-toggle="wy-nav-top" class="fa fa-bars"></i>
|
|
<a href="../../../../index.html">tensorrt_llm</a>
|
|
</nav>
|
|
|
|
<div class="wy-nav-content">
|
|
<div class="rst-content">
|
|
<div role="navigation" aria-label="Page navigation">
|
|
<ul class="wy-breadcrumbs">
|
|
<li><a href="../../../../index.html" class="icon icon-home" aria-label="Home"></a></li>
|
|
<li class="breadcrumb-item"><a href="../../../index.html">Module code</a></li>
|
|
<li class="breadcrumb-item active">tensorrt_llm.models.quantized.quant</li>
|
|
<li class="wy-breadcrumbs-aside">
|
|
</li>
|
|
</ul>
|
|
<hr/>
|
|
</div>
|
|
<div role="main" class="document" itemscope="itemscope" itemtype="http://schema.org/Article">
|
|
<div itemprop="articleBody">
|
|
|
|
<h1>Source code for tensorrt_llm.models.quantized.quant</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">import</span> <span class="nn">dataclasses</span>
|
|
<span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Any</span>
|
|
|
|
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
|
|
|
<span class="kn">from</span> <span class="nn">...layers</span> <span class="kn">import</span> <span class="n">ColumnLinear</span><span class="p">,</span> <span class="n">RowLinear</span>
|
|
<span class="kn">from</span> <span class="nn">...module</span> <span class="kn">import</span> <span class="n">Module</span>
|
|
<span class="kn">from</span> <span class="nn">...quantization</span> <span class="kn">import</span> <span class="n">QuantMode</span>
|
|
<span class="kn">from</span> <span class="nn">...quantization.layers</span> <span class="kn">import</span> <span class="n">FP8Linear</span><span class="p">,</span> <span class="n">FP8RowLinear</span>
|
|
<span class="kn">from</span> <span class="nn">...quantization.mode</span> <span class="kn">import</span> <span class="n">QuantAlgo</span>
|
|
<span class="kn">from</span> <span class="nn">...quantization.quantize</span> <span class="kn">import</span> <span class="n">weight_only_quantize</span>
|
|
<span class="kn">from</span> <span class="nn">..modeling_utils</span> <span class="kn">import</span> <span class="n">QuantConfig</span>
|
|
|
|
<span class="c1"># isort: off</span>
|
|
<span class="kn">from</span> <span class="nn">...quantization.layers</span> <span class="kn">import</span> <span class="p">(</span><span class="n">SmoothQuantAttention</span><span class="p">,</span> <span class="n">SmoothQuantGatedMLP</span><span class="p">,</span>
|
|
<span class="n">SmoothQuantLayerNorm</span><span class="p">,</span> <span class="n">SmoothQuantMLP</span><span class="p">,</span>
|
|
<span class="n">SmoothQuantRmsNorm</span><span class="p">,</span>
|
|
<span class="n">WeightOnlyGroupwiseQuantColumnLinear</span><span class="p">,</span>
|
|
<span class="n">WeightOnlyGroupwiseQuantRowLinear</span><span class="p">)</span>
|
|
<span class="c1"># isort: on</span>
|
|
|
|
|
|
<span class="k">def</span> <span class="nf">_smooth_quantize_gpt</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">quant_mode</span><span class="p">):</span>
|
|
<span class="k">assert</span> <span class="n">quant_mode</span><span class="o">.</span><span class="n">has_act_and_weight_quant</span><span class="p">()</span>
|
|
<span class="k">for</span> <span class="n">layer_idx</span><span class="p">,</span> <span class="n">layer</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">layers</span><span class="p">):</span>
|
|
<span class="k">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span>
|
|
<span class="s2">"input_layernorm"</span><span class="p">),</span> <span class="s2">"The layer has no input_layernorm"</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">input_layernorm</span> <span class="o">=</span> <span class="n">SmoothQuantLayerNorm</span><span class="p">(</span>
|
|
<span class="n">normalized_shape</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">hidden_size</span><span class="p">,</span>
|
|
<span class="n">dtype</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="o">=</span><span class="n">quant_mode</span><span class="p">)</span>
|
|
<span class="k">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span> <span class="s2">"attention"</span><span class="p">),</span> <span class="s2">"The layer has no attention"</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">attention</span> <span class="o">=</span> <span class="n">SmoothQuantAttention</span><span class="p">(</span>
|
|
<span class="n">layer_idx</span><span class="o">=</span><span class="n">layer_idx</span><span class="p">,</span>
|
|
<span class="n">hidden_size</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">hidden_size</span><span class="p">,</span>
|
|
<span class="n">num_attention_heads</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">num_attention_heads</span><span class="p">,</span>
|
|
<span class="n">num_kv_heads</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">attention</span><span class="o">.</span><span class="n">num_attention_kv_heads</span> <span class="o">*</span> <span class="n">layer</span><span class="o">.</span><span class="n">tp_size</span><span class="p">,</span>
|
|
<span class="n">max_position_embeddings</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">max_position_embeddings</span><span class="p">,</span>
|
|
<span class="n">num_layers</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">num_layers</span><span class="p">,</span>
|
|
<span class="n">apply_query_key_layer_scaling</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">apply_query_key_layer_scaling</span><span class="p">,</span>
|
|
<span class="n">dtype</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
|
|
<span class="n">attention_mask_type</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">attention_mask_type</span><span class="p">,</span>
|
|
<span class="n">bias</span><span class="o">=</span><span class="p">(</span><span class="n">layer</span><span class="o">.</span><span class="n">attention</span><span class="o">.</span><span class="n">dense</span><span class="o">.</span><span class="n">bias</span> <span class="o">!=</span> <span class="kc">None</span><span class="p">),</span>
|
|
<span class="n">qkv_bias_only</span><span class="o">=</span><span class="p">(</span><span class="n">layer</span><span class="o">.</span><span class="n">attention</span><span class="o">.</span><span class="n">qkv</span><span class="o">.</span><span class="n">bias</span> <span class="o">!=</span> <span class="kc">None</span>
|
|
<span class="ow">and</span> <span class="n">layer</span><span class="o">.</span><span class="n">attention</span><span class="o">.</span><span class="n">dense</span><span class="o">.</span><span class="n">bias</span> <span class="o">==</span> <span class="kc">None</span><span class="p">),</span>
|
|
<span class="n">position_embedding_type</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">position_embedding_type</span><span class="p">,</span>
|
|
<span class="n">tp_group</span><span class="o">=</span><span class="n">layer</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">layer</span><span class="o">.</span><span class="n">tp_size</span><span class="p">,</span>
|
|
<span class="n">tp_rank</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">attention</span><span class="o">.</span><span class="n">tp_rank</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="o">=</span><span class="n">quant_mode</span><span class="p">)</span>
|
|
<span class="k">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span> <span class="s2">"mlp"</span><span class="p">),</span> <span class="s2">"The layer has no mlp"</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">mlp</span> <span class="o">=</span> <span class="n">SmoothQuantMLP</span><span class="p">(</span><span class="n">hidden_size</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">hidden_size</span><span class="p">,</span>
|
|
<span class="n">ffn_hidden_size</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">hidden_size</span> <span class="o">*</span> <span class="mi">4</span><span class="p">,</span>
|
|
<span class="n">hidden_act</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">hidden_act</span><span class="p">,</span>
|
|
<span class="n">bias</span><span class="o">=</span><span class="p">(</span><span class="n">layer</span><span class="o">.</span><span class="n">mlp</span><span class="o">.</span><span class="n">fc</span><span class="o">.</span><span class="n">bias</span> <span class="o">!=</span> <span class="kc">None</span><span class="p">),</span>
|
|
<span class="n">dtype</span><span class="o">=</span><span class="n">layer</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">layer</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">layer</span><span class="o">.</span><span class="n">tp_size</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="o">=</span><span class="n">quant_mode</span><span class="p">)</span>
|
|
<span class="k">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span>
|
|
<span class="s2">"post_layernorm"</span><span class="p">),</span> <span class="s2">"The layer has no post_layernorm"</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">post_layernorm</span> <span class="o">=</span> <span class="n">SmoothQuantLayerNorm</span><span class="p">(</span>
|
|
<span class="n">normalized_shape</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">hidden_size</span><span class="p">,</span>
|
|
<span class="n">dtype</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="o">=</span><span class="n">quant_mode</span><span class="p">)</span>
|
|
|
|
<span class="k">return</span> <span class="n">model</span>
|
|
|
|
|
|
<span class="k">def</span> <span class="nf">_smooth_quantize_llama</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">quant_mode</span><span class="p">):</span>
|
|
<span class="k">assert</span> <span class="n">quant_mode</span><span class="o">.</span><span class="n">has_act_and_weight_quant</span><span class="p">()</span>
|
|
<span class="k">for</span> <span class="n">layer_idx</span><span class="p">,</span> <span class="n">layer</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">layers</span><span class="p">):</span>
|
|
<span class="k">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span>
|
|
<span class="s2">"input_layernorm"</span><span class="p">),</span> <span class="s2">"The layer has no input_layernorm"</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">input_layernorm</span> <span class="o">=</span> <span class="n">SmoothQuantRmsNorm</span><span class="p">(</span>
|
|
<span class="n">normalized_shape</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">hidden_size</span><span class="p">,</span>
|
|
<span class="n">dtype</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="o">=</span><span class="n">quant_mode</span><span class="p">)</span>
|
|
<span class="k">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span> <span class="s2">"attention"</span><span class="p">),</span> <span class="s2">"The layer has no attention"</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">attention</span> <span class="o">=</span> <span class="n">SmoothQuantAttention</span><span class="p">(</span>
|
|
<span class="n">layer_idx</span><span class="o">=</span><span class="n">layer_idx</span><span class="p">,</span>
|
|
<span class="n">hidden_size</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">hidden_size</span><span class="p">,</span>
|
|
<span class="n">num_attention_heads</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">num_attention_heads</span><span class="p">,</span>
|
|
<span class="n">num_kv_heads</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">num_kv_heads</span><span class="p">,</span>
|
|
<span class="n">max_position_embeddings</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">max_position_embeddings</span><span class="p">,</span>
|
|
<span class="n">num_layers</span><span class="o">=</span><span class="n">model</span><span class="o">.</span><span class="n">num_layers</span><span class="p">,</span>
|
|
<span class="n">dtype</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
|
|
<span class="n">attention_mask_type</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">attention_mask_type</span><span class="p">,</span>
|
|
<span class="n">position_embedding_type</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">position_embedding_type</span><span class="p">,</span>
|
|
<span class="n">rotary_embedding_base</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">attention</span><span class="o">.</span><span class="n">rotary_embedding_base</span><span class="p">,</span>
|
|
<span class="n">tp_group</span><span class="o">=</span><span class="n">layer</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">layer</span><span class="o">.</span><span class="n">tp_size</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="o">=</span><span class="n">quant_mode</span><span class="p">,</span>
|
|
<span class="n">bias</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">attention</span><span class="o">.</span><span class="n">qkv</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">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span> <span class="s2">"mlp"</span><span class="p">),</span> <span class="s2">"The layer has no mlp"</span>
|
|
<span class="k">if</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="s2">"moe_config"</span><span class="p">):</span>
|
|
<span class="k">assert</span> <span class="ow">not</span> <span class="n">model</span><span class="o">.</span><span class="n">moe_config</span><span class="o">.</span><span class="n">has_moe</span><span class="p">(</span>
|
|
<span class="p">),</span> <span class="s2">"MOE does not support smooth quant"</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">mlp</span> <span class="o">=</span> <span class="n">SmoothQuantGatedMLP</span><span class="p">(</span><span class="n">hidden_size</span><span class="o">=</span><span class="n">model</span><span class="o">.</span><span class="n">hidden_size</span><span class="p">,</span>
|
|
<span class="n">ffn_hidden_size</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">mlp_hidden_size</span><span class="p">,</span>
|
|
<span class="n">hidden_act</span><span class="o">=</span><span class="n">layer</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">layer</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">layer</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">layer</span><span class="o">.</span><span class="n">tp_size</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="o">=</span><span class="n">quant_mode</span><span class="p">,</span>
|
|
<span class="n">bias</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">mlp</span><span class="o">.</span><span class="n">fc</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">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span>
|
|
<span class="s2">"post_layernorm"</span><span class="p">),</span> <span class="s2">"The layer has no post_layernorm"</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">post_layernorm</span> <span class="o">=</span> <span class="n">SmoothQuantRmsNorm</span><span class="p">(</span>
|
|
<span class="n">normalized_shape</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">hidden_size</span><span class="p">,</span>
|
|
<span class="n">dtype</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="o">=</span><span class="n">quant_mode</span><span class="p">)</span>
|
|
|
|
<span class="k">return</span> <span class="n">model</span>
|
|
|
|
|
|
<span class="k">def</span> <span class="nf">_smooth_quantize_bloom</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">quant_mode</span><span class="p">):</span>
|
|
<span class="k">assert</span> <span class="n">quant_mode</span><span class="o">.</span><span class="n">has_act_and_weight_quant</span><span class="p">()</span>
|
|
<span class="k">for</span> <span class="n">layer_idx</span><span class="p">,</span> <span class="n">layer</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">layers</span><span class="p">):</span>
|
|
<span class="k">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span>
|
|
<span class="s2">"input_layernorm"</span><span class="p">),</span> <span class="s2">"The layer has no input_layernorm"</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">input_layernorm</span> <span class="o">=</span> <span class="n">SmoothQuantLayerNorm</span><span class="p">(</span>
|
|
<span class="n">normalized_shape</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">hidden_size</span><span class="p">,</span>
|
|
<span class="n">dtype</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="o">=</span><span class="n">quant_mode</span><span class="p">)</span>
|
|
<span class="k">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span> <span class="s2">"attention"</span><span class="p">),</span> <span class="s2">"The layer has no attention"</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">attention</span> <span class="o">=</span> <span class="n">SmoothQuantAttention</span><span class="p">(</span>
|
|
<span class="n">layer_idx</span><span class="o">=</span><span class="n">layer_idx</span><span class="p">,</span>
|
|
<span class="n">hidden_size</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">hidden_size</span><span class="p">,</span>
|
|
<span class="n">num_attention_heads</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">num_attention_heads</span><span class="p">,</span>
|
|
<span class="n">max_position_embeddings</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">max_position_embeddings</span><span class="p">,</span>
|
|
<span class="n">num_layers</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">num_layers</span><span class="p">,</span>
|
|
<span class="n">dtype</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
|
|
<span class="n">attention_mask_type</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">attention_mask_type</span><span class="p">,</span>
|
|
<span class="n">position_embedding_type</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">position_embedding_type</span><span class="p">,</span>
|
|
<span class="n">tp_group</span><span class="o">=</span><span class="n">layer</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">layer</span><span class="o">.</span><span class="n">tp_size</span><span class="p">,</span>
|
|
<span class="n">tp_rank</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">tp_rank</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="o">=</span><span class="n">quant_mode</span><span class="p">)</span>
|
|
|
|
<span class="k">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span> <span class="s2">"mlp"</span><span class="p">),</span> <span class="s2">"The layer has no mlp"</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">mlp</span> <span class="o">=</span> <span class="n">SmoothQuantMLP</span><span class="p">(</span><span class="n">hidden_size</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">hidden_size</span><span class="p">,</span>
|
|
<span class="n">ffn_hidden_size</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">hidden_size</span> <span class="o">*</span> <span class="mi">4</span><span class="p">,</span>
|
|
<span class="n">hidden_act</span><span class="o">=</span><span class="n">layer</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">layer</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">layer</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">layer</span><span class="o">.</span><span class="n">tp_size</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="o">=</span><span class="n">quant_mode</span><span class="p">)</span>
|
|
<span class="k">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span>
|
|
<span class="s2">"post_layernorm"</span><span class="p">),</span> <span class="s2">"The layer has no post_layernorm"</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">post_layernorm</span> <span class="o">=</span> <span class="n">SmoothQuantLayerNorm</span><span class="p">(</span>
|
|
<span class="n">normalized_shape</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">hidden_size</span><span class="p">,</span>
|
|
<span class="n">dtype</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="o">=</span><span class="n">quant_mode</span><span class="p">)</span>
|
|
|
|
<span class="nb">setattr</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="s1">'quant_mode'</span><span class="p">,</span> <span class="n">quant_mode</span><span class="p">)</span>
|
|
<span class="k">return</span> <span class="n">model</span>
|
|
|
|
|
|
<span class="k">def</span> <span class="nf">_smooth_quantize_baichuan</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">quant_mode</span><span class="p">):</span>
|
|
<span class="k">assert</span> <span class="n">quant_mode</span><span class="o">.</span><span class="n">has_act_and_weight_quant</span><span class="p">()</span>
|
|
<span class="k">for</span> <span class="n">layer_idx</span><span class="p">,</span> <span class="n">layer</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">layers</span><span class="p">):</span>
|
|
<span class="k">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span>
|
|
<span class="s2">"input_layernorm"</span><span class="p">),</span> <span class="s2">"The layer has no input_layernorm"</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">input_layernorm</span> <span class="o">=</span> <span class="n">SmoothQuantRmsNorm</span><span class="p">(</span>
|
|
<span class="n">normalized_shape</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">hidden_size</span><span class="p">,</span>
|
|
<span class="n">dtype</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="o">=</span><span class="n">quant_mode</span><span class="p">)</span>
|
|
<span class="k">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span> <span class="s2">"attention"</span><span class="p">),</span> <span class="s2">"The layer has no attention"</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">attention</span> <span class="o">=</span> <span class="n">SmoothQuantAttention</span><span class="p">(</span>
|
|
<span class="n">layer_idx</span><span class="o">=</span><span class="n">layer_idx</span><span class="p">,</span>
|
|
<span class="n">hidden_size</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">hidden_size</span><span class="p">,</span>
|
|
<span class="n">num_attention_heads</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">num_attention_heads</span><span class="p">,</span>
|
|
<span class="n">num_kv_heads</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">num_kv_heads</span><span class="p">,</span>
|
|
<span class="n">max_position_embeddings</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">max_position_embeddings</span><span class="p">,</span>
|
|
<span class="n">num_layers</span><span class="o">=</span><span class="n">model</span><span class="o">.</span><span class="n">num_layers</span><span class="p">,</span>
|
|
<span class="n">dtype</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
|
|
<span class="n">attention_mask_type</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">attention_mask_type</span><span class="p">,</span>
|
|
<span class="n">position_embedding_type</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">position_embedding_type</span><span class="p">,</span>
|
|
<span class="n">rotary_embedding_base</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">attention</span><span class="o">.</span><span class="n">rotary_embedding_base</span><span class="p">,</span>
|
|
<span class="n">tp_group</span><span class="o">=</span><span class="n">layer</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">layer</span><span class="o">.</span><span class="n">tp_size</span><span class="p">,</span>
|
|
<span class="n">tp_rank</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">tp_rank</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="o">=</span><span class="n">quant_mode</span><span class="p">,</span>
|
|
<span class="n">bias</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">attention</span><span class="o">.</span><span class="n">qkv</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">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span> <span class="s2">"mlp"</span><span class="p">),</span> <span class="s2">"The layer has no mlp"</span>
|
|
<span class="k">if</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="s2">"moe_config"</span><span class="p">):</span>
|
|
<span class="k">assert</span> <span class="ow">not</span> <span class="n">model</span><span class="o">.</span><span class="n">moe_config</span><span class="o">.</span><span class="n">has_moe</span><span class="p">(</span>
|
|
<span class="p">),</span> <span class="s2">"MOE does not support smooth quant"</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">mlp</span> <span class="o">=</span> <span class="n">SmoothQuantGatedMLP</span><span class="p">(</span><span class="n">hidden_size</span><span class="o">=</span><span class="n">model</span><span class="o">.</span><span class="n">hidden_size</span><span class="p">,</span>
|
|
<span class="n">ffn_hidden_size</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">mlp_hidden_size</span><span class="p">,</span>
|
|
<span class="n">hidden_act</span><span class="o">=</span><span class="n">layer</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">layer</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">layer</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">layer</span><span class="o">.</span><span class="n">tp_size</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="o">=</span><span class="n">quant_mode</span><span class="p">,</span>
|
|
<span class="n">bias</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">mlp</span><span class="o">.</span><span class="n">fc</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">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span>
|
|
<span class="s2">"post_layernorm"</span><span class="p">),</span> <span class="s2">"The layer has no post_layernorm"</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">post_layernorm</span> <span class="o">=</span> <span class="n">SmoothQuantRmsNorm</span><span class="p">(</span>
|
|
<span class="n">normalized_shape</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">hidden_size</span><span class="p">,</span>
|
|
<span class="n">dtype</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="o">=</span><span class="n">quant_mode</span><span class="p">)</span>
|
|
|
|
<span class="k">return</span> <span class="n">model</span>
|
|
|
|
|
|
<span class="k">def</span> <span class="nf">_smooth_quantize_internlm</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">quant_mode</span><span class="p">):</span>
|
|
<span class="k">assert</span> <span class="n">quant_mode</span><span class="o">.</span><span class="n">has_act_and_weight_quant</span><span class="p">()</span>
|
|
<span class="k">for</span> <span class="n">layer_idx</span><span class="p">,</span> <span class="n">layer</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">layers</span><span class="p">):</span>
|
|
<span class="k">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span>
|
|
<span class="s2">"input_layernorm"</span><span class="p">),</span> <span class="s2">"The layer has no input_layernorm"</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">input_layernorm</span> <span class="o">=</span> <span class="n">SmoothQuantRmsNorm</span><span class="p">(</span>
|
|
<span class="n">normalized_shape</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">hidden_size</span><span class="p">,</span>
|
|
<span class="n">dtype</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="o">=</span><span class="n">quant_mode</span><span class="p">)</span>
|
|
<span class="k">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span> <span class="s2">"attention"</span><span class="p">),</span> <span class="s2">"The layer has no attention"</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">attention</span> <span class="o">=</span> <span class="n">SmoothQuantAttention</span><span class="p">(</span>
|
|
<span class="n">layer_idx</span><span class="o">=</span><span class="n">layer_idx</span><span class="p">,</span>
|
|
<span class="n">hidden_size</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">hidden_size</span><span class="p">,</span>
|
|
<span class="n">num_attention_heads</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">num_attention_heads</span><span class="p">,</span>
|
|
<span class="n">num_kv_heads</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">num_kv_heads</span><span class="p">,</span>
|
|
<span class="n">max_position_embeddings</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">max_position_embeddings</span><span class="p">,</span>
|
|
<span class="n">num_layers</span><span class="o">=</span><span class="n">model</span><span class="o">.</span><span class="n">num_layers</span><span class="p">,</span>
|
|
<span class="n">dtype</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
|
|
<span class="n">attention_mask_type</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">attention_mask_type</span><span class="p">,</span>
|
|
<span class="n">position_embedding_type</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">position_embedding_type</span><span class="p">,</span>
|
|
<span class="n">tp_group</span><span class="o">=</span><span class="n">layer</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">layer</span><span class="o">.</span><span class="n">tp_size</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="o">=</span><span class="n">quant_mode</span><span class="p">,</span>
|
|
<span class="n">bias</span><span class="o">=</span><span class="n">model</span><span class="o">.</span><span class="n">attn_bias</span><span class="p">)</span>
|
|
|
|
<span class="k">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span> <span class="s2">"mlp"</span><span class="p">),</span> <span class="s2">"The layer has no mlp"</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">mlp</span> <span class="o">=</span> <span class="n">SmoothQuantGatedMLP</span><span class="p">(</span><span class="n">hidden_size</span><span class="o">=</span><span class="n">model</span><span class="o">.</span><span class="n">hidden_size</span><span class="p">,</span>
|
|
<span class="n">ffn_hidden_size</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">mlp_hidden_size</span><span class="p">,</span>
|
|
<span class="n">hidden_act</span><span class="o">=</span><span class="n">layer</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">layer</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">layer</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">layer</span><span class="o">.</span><span class="n">tp_size</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="o">=</span><span class="n">quant_mode</span><span class="p">,</span>
|
|
<span class="n">bias</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
|
|
<span class="k">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span>
|
|
<span class="s2">"post_layernorm"</span><span class="p">),</span> <span class="s2">"The layer has no post_layernorm"</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">post_layernorm</span> <span class="o">=</span> <span class="n">SmoothQuantRmsNorm</span><span class="p">(</span>
|
|
<span class="n">normalized_shape</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">hidden_size</span><span class="p">,</span>
|
|
<span class="n">dtype</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="o">=</span><span class="n">quant_mode</span><span class="p">)</span>
|
|
|
|
<span class="nb">setattr</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="s1">'quant_mode'</span><span class="p">,</span> <span class="n">quant_mode</span><span class="p">)</span>
|
|
<span class="k">return</span> <span class="n">model</span>
|
|
|
|
|
|
<span class="k">def</span> <span class="nf">_smooth_quantize_qwen</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">quant_mode</span><span class="p">):</span>
|
|
<span class="k">assert</span> <span class="n">quant_mode</span><span class="o">.</span><span class="n">has_act_and_weight_quant</span><span class="p">()</span>
|
|
<span class="k">for</span> <span class="n">layer_idx</span><span class="p">,</span> <span class="n">layer</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">layers</span><span class="p">):</span>
|
|
<span class="k">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span> <span class="s2">"ln_1"</span><span class="p">),</span> <span class="s2">"The layer has no ln_1"</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">ln_1</span> <span class="o">=</span> <span class="n">SmoothQuantRmsNorm</span><span class="p">(</span><span class="n">normalized_shape</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">hidden_size</span><span class="p">,</span>
|
|
<span class="n">dtype</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="o">=</span><span class="n">quant_mode</span><span class="p">)</span>
|
|
<span class="k">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span> <span class="s2">"attention"</span><span class="p">),</span> <span class="s2">"The layer has no attention"</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">attention</span> <span class="o">=</span> <span class="n">SmoothQuantAttention</span><span class="p">(</span>
|
|
<span class="n">layer_idx</span><span class="o">=</span><span class="n">layer_idx</span><span class="p">,</span>
|
|
<span class="n">hidden_size</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">hidden_size</span><span class="p">,</span>
|
|
<span class="n">num_attention_heads</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">num_attention_heads</span><span class="p">,</span>
|
|
<span class="n">max_position_embeddings</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">max_position_embeddings</span><span class="p">,</span>
|
|
<span class="n">num_layers</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">num_layers</span><span class="p">,</span>
|
|
<span class="n">apply_query_key_layer_scaling</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">apply_query_key_layer_scaling</span><span class="p">,</span>
|
|
<span class="n">attention_mask_type</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">attention_mask_type</span><span class="p">,</span>
|
|
<span class="n">bias</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">bias</span><span class="p">,</span>
|
|
<span class="n">qkv_bias_only</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="n">layer</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
|
|
<span class="n">position_embedding_type</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">position_embedding_type</span><span class="p">,</span>
|
|
<span class="n">tp_group</span><span class="o">=</span><span class="n">layer</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">layer</span><span class="o">.</span><span class="n">tp_size</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="o">=</span><span class="n">quant_mode</span><span class="p">)</span>
|
|
<span class="k">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span> <span class="s2">"mlp"</span><span class="p">),</span> <span class="s2">"The layer has no mlp"</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">mlp</span> <span class="o">=</span> <span class="n">SmoothQuantGatedMLP</span><span class="p">(</span><span class="n">hidden_size</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">hidden_size</span><span class="p">,</span>
|
|
<span class="n">ffn_hidden_size</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">mlp_hidden_size</span> <span class="o">//</span>
|
|
<span class="mi">2</span><span class="p">,</span>
|
|
<span class="n">hidden_act</span><span class="o">=</span><span class="n">layer</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">layer</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
|
|
<span class="n">bias</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">bias</span><span class="p">,</span>
|
|
<span class="n">tp_group</span><span class="o">=</span><span class="n">layer</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">layer</span><span class="o">.</span><span class="n">tp_size</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="o">=</span><span class="n">quant_mode</span><span class="p">)</span>
|
|
<span class="k">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span> <span class="s2">"ln_2"</span><span class="p">),</span> <span class="s2">"The layer has no ln_2"</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">ln_2</span> <span class="o">=</span> <span class="n">SmoothQuantRmsNorm</span><span class="p">(</span><span class="n">normalized_shape</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">hidden_size</span><span class="p">,</span>
|
|
<span class="n">dtype</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="o">=</span><span class="n">quant_mode</span><span class="p">)</span>
|
|
|
|
<span class="nb">setattr</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="s1">'quant_mode'</span><span class="p">,</span> <span class="n">quant_mode</span><span class="p">)</span>
|
|
<span class="k">return</span> <span class="n">model</span>
|
|
|
|
|
|
<span class="k">def</span> <span class="nf">_smooth_quantize_chatglm</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">quant_mode</span><span class="p">):</span>
|
|
<span class="k">assert</span> <span class="n">quant_mode</span><span class="o">.</span><span class="n">has_act_and_weight_quant</span><span class="p">()</span>
|
|
<span class="k">for</span> <span class="n">layer_idx</span><span class="p">,</span> <span class="n">layer</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">layers</span><span class="p">):</span>
|
|
<span class="k">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span>
|
|
<span class="s2">"input_layernorm"</span><span class="p">),</span> <span class="s2">"The layer has no input_layernorm"</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">input_layernorm</span> <span class="o">=</span> <span class="n">SmoothQuantRmsNorm</span><span class="p">(</span>
|
|
<span class="n">normalized_shape</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">hidden_size</span><span class="p">,</span>
|
|
<span class="n">dtype</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="o">=</span><span class="n">quant_mode</span><span class="p">,</span>
|
|
<span class="p">)</span>
|
|
<span class="k">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span> <span class="s2">"attention"</span><span class="p">),</span> <span class="s2">"The layer has no attention"</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">attention</span> <span class="o">=</span> <span class="n">SmoothQuantAttention</span><span class="p">(</span>
|
|
<span class="n">layer_idx</span><span class="o">=</span><span class="n">layer_idx</span><span class="p">,</span>
|
|
<span class="n">hidden_size</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">hidden_size</span><span class="p">,</span>
|
|
<span class="n">num_attention_heads</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">num_heads</span><span class="p">,</span>
|
|
<span class="n">num_kv_heads</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">num_kv_heads</span><span class="p">,</span>
|
|
<span class="n">max_position_embeddings</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">max_seq_length</span><span class="p">,</span>
|
|
<span class="n">num_layers</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">num_layers</span><span class="p">,</span>
|
|
<span class="n">apply_query_key_layer_scaling</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">apply_query_key_layer_scaling</span><span class="p">,</span>
|
|
<span class="n">dtype</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
|
|
<span class="n">attention_mask_type</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">attention_mask_type</span><span class="p">,</span>
|
|
<span class="n">position_embedding_type</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">position_embedding_type</span><span class="p">,</span>
|
|
<span class="n">rotary_embedding_base</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">rotary_embedding_base</span><span class="p">,</span>
|
|
<span class="n">tp_group</span><span class="o">=</span><span class="n">layer</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">layer</span><span class="o">.</span><span class="n">tp_size</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="o">=</span><span class="n">quant_mode</span><span class="p">,</span>
|
|
<span class="n">bias</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">dense_bias</span><span class="p">,</span>
|
|
<span class="n">qkv_bias_only</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">bias</span> <span class="ow">and</span> <span class="ow">not</span> <span class="n">layer</span><span class="o">.</span><span class="n">dense_bias</span><span class="p">,</span>
|
|
<span class="p">)</span>
|
|
<span class="k">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span> <span class="s2">"mlp"</span><span class="p">),</span> <span class="s2">"The layer has no mlp"</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">mlp</span> <span class="o">=</span> <span class="n">SmoothQuantMLP</span><span class="p">(</span>
|
|
<span class="n">hidden_size</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">hidden_size</span><span class="p">,</span>
|
|
<span class="n">ffn_hidden_size</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">ffn_hidden_size</span><span class="p">,</span>
|
|
<span class="n">hidden_act</span><span class="o">=</span><span class="n">layer</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">layer</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">layer</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">layer</span><span class="o">.</span><span class="n">tp_size</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="o">=</span><span class="n">quant_mode</span><span class="p">,</span>
|
|
<span class="n">bias</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">dense_bias</span><span class="p">,</span>
|
|
<span class="p">)</span>
|
|
<span class="k">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span>
|
|
<span class="s2">"post_layernorm"</span><span class="p">),</span> <span class="s2">"The layer has no post_layernorm"</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">post_layernorm</span> <span class="o">=</span> <span class="n">SmoothQuantRmsNorm</span><span class="p">(</span>
|
|
<span class="n">normalized_shape</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">hidden_size</span><span class="p">,</span>
|
|
<span class="n">dtype</span><span class="o">=</span><span class="n">layer</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="o">=</span><span class="n">quant_mode</span><span class="p">,</span>
|
|
<span class="p">)</span>
|
|
<span class="k">return</span> <span class="n">model</span>
|
|
|
|
|
|
<span class="k">def</span> <span class="nf">_smooth_quantize</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">quant_mode</span><span class="p">):</span>
|
|
<span class="kn">from</span> <span class="nn">...models</span> <span class="kn">import</span> <span class="p">(</span><span class="n">BaichuanForCausalLM</span><span class="p">,</span> <span class="n">BloomForCausalLM</span><span class="p">,</span>
|
|
<span class="n">ChatGLMForCausalLM</span><span class="p">,</span> <span class="n">GPTForCausalLM</span><span class="p">,</span> <span class="n">LLaMAForCausalLM</span><span class="p">,</span>
|
|
<span class="n">QWenForCausalLM</span><span class="p">)</span>
|
|
<span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">GPTForCausalLM</span><span class="p">)</span> <span class="ow">or</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">LLaMAForCausalLM</span><span class="p">)</span> \
|
|
<span class="ow">or</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">BloomForCausalLM</span><span class="p">)</span> <span class="ow">or</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">BaichuanForCausalLM</span><span class="p">)</span> \
|
|
<span class="ow">or</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">QWenForCausalLM</span><span class="p">)</span> <span class="ow">or</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">ChatGLMForCausalLM</span><span class="p">),</span> \
|
|
<span class="s2">"Only GPTForCausalLM, LLaMAForCausalLM BloomForCausalLM and BaichuanForCausalLM are well tested now"</span>
|
|
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">GPTForCausalLM</span><span class="p">):</span>
|
|
<span class="k">return</span> <span class="n">_smooth_quantize_gpt</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">quant_mode</span><span class="p">)</span>
|
|
<span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">LLaMAForCausalLM</span><span class="p">):</span>
|
|
<span class="k">return</span> <span class="n">_smooth_quantize_llama</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">quant_mode</span><span class="p">)</span>
|
|
<span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">BloomForCausalLM</span><span class="p">):</span>
|
|
<span class="k">return</span> <span class="n">_smooth_quantize_bloom</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">quant_mode</span><span class="p">)</span>
|
|
<span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">BaichuanForCausalLM</span><span class="p">):</span>
|
|
<span class="k">return</span> <span class="n">_smooth_quantize_baichuan</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">quant_mode</span><span class="p">)</span>
|
|
<span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">QWenForCausalLM</span><span class="p">):</span>
|
|
<span class="k">return</span> <span class="n">_smooth_quantize_qwen</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">quant_mode</span><span class="p">)</span>
|
|
<span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">ChatGLMForCausalLM</span><span class="p">):</span>
|
|
<span class="k">return</span> <span class="n">_smooth_quantize_chatglm</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">quant_mode</span><span class="p">)</span>
|
|
<span class="k">else</span><span class="p">:</span>
|
|
<span class="k">assert</span> <span class="kc">False</span><span class="p">,</span> <span class="sa">f</span><span class="s2">"Model </span><span class="si">{</span><span class="nb">type</span><span class="p">(</span><span class="n">model</span><span class="p">)</span><span class="o">.</span><span class="vm">__name__</span><span class="si">}</span><span class="s2"> is not supported by SmoothQuant yet"</span>
|
|
|
|
|
|
<span class="k">def</span> <span class="nf">_weight_only_groupwise_quantize</span><span class="p">(</span><span class="n">model</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="p">,</span>
|
|
<span class="n">group_size</span><span class="o">=</span><span class="mi">128</span><span class="p">,</span>
|
|
<span class="n">pre_quant_scale</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
|
|
<span class="n">zero</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
|
|
<span class="n">weight_only_precision</span><span class="o">=</span><span class="s2">"int4_awq"</span><span class="p">,</span>
|
|
<span class="n">exclude_modules</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
|
|
<span class="n">current_key_name</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
|
<span class="n">exclude_modules</span> <span class="o">=</span> <span class="p">[</span><span class="s1">'lm_head'</span>
|
|
<span class="p">]</span> <span class="k">if</span> <span class="n">exclude_modules</span> <span class="ow">is</span> <span class="kc">None</span> <span class="k">else</span> <span class="n">exclude_modules</span>
|
|
|
|
<span class="k">for</span> <span class="n">name</span><span class="p">,</span> <span class="n">module</span> <span class="ow">in</span> <span class="n">model</span><span class="o">.</span><span class="n">named_children</span><span class="p">():</span>
|
|
<span class="k">if</span> <span class="n">current_key_name</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
|
<span class="n">current_key_name</span> <span class="o">=</span> <span class="p">[]</span>
|
|
<span class="n">current_key_name</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">name</span><span class="p">)</span>
|
|
|
|
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="n">module</span><span class="o">.</span><span class="n">children</span><span class="p">()))</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
|
<span class="n">_weight_only_groupwise_quantize</span><span class="p">(</span><span class="n">module</span><span class="p">,</span> <span class="n">quant_mode</span><span class="p">,</span> <span class="n">group_size</span><span class="p">,</span>
|
|
<span class="n">pre_quant_scale</span><span class="p">,</span> <span class="n">zero</span><span class="p">,</span>
|
|
<span class="n">weight_only_precision</span><span class="p">,</span>
|
|
<span class="n">exclude_modules</span><span class="p">,</span> <span class="n">current_key_name</span><span class="p">)</span>
|
|
|
|
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">module</span><span class="p">,</span> <span class="n">ColumnLinear</span><span class="p">)</span> <span class="ow">and</span> <span class="n">name</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">exclude_modules</span><span class="p">:</span>
|
|
<span class="k">if</span> <span class="ow">not</span> <span class="nb">any</span><span class="p">(</span><span class="n">key</span> <span class="ow">in</span> <span class="s1">'.'</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">current_key_name</span><span class="p">)</span>
|
|
<span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="n">exclude_modules</span><span class="p">):</span>
|
|
<span class="n">model</span><span class="o">.</span><span class="n">_modules</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">WeightOnlyGroupwiseQuantColumnLinear</span><span class="p">(</span>
|
|
<span class="n">in_features</span><span class="o">=</span><span class="n">module</span><span class="o">.</span><span class="n">in_features</span><span class="p">,</span>
|
|
<span class="n">out_features</span><span class="o">=</span><span class="n">module</span><span class="o">.</span><span class="n">out_features</span> <span class="o">*</span> <span class="n">module</span><span class="o">.</span><span class="n">tp_size</span><span class="p">,</span>
|
|
<span class="n">group_size</span><span class="o">=</span><span class="n">group_size</span><span class="p">,</span>
|
|
<span class="n">pre_quant_scale</span><span class="o">=</span><span class="n">pre_quant_scale</span><span class="p">,</span>
|
|
<span class="n">zero</span><span class="o">=</span><span class="n">zero</span><span class="p">,</span>
|
|
<span class="n">bias</span><span class="o">=</span><span class="n">module</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="n">use_w4a8_awq</span><span class="o">=</span><span class="n">weight_only_precision</span> <span class="o">==</span> <span class="s1">'w4a8_awq'</span><span class="p">,</span>
|
|
<span class="n">dtype</span><span class="o">=</span><span class="n">module</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">module</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">module</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="n">module</span><span class="o">.</span><span class="n">gather_output</span><span class="p">)</span>
|
|
<span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">module</span><span class="p">,</span> <span class="n">RowLinear</span><span class="p">)</span> <span class="ow">and</span> <span class="n">name</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">exclude_modules</span><span class="p">:</span>
|
|
<span class="k">if</span> <span class="ow">not</span> <span class="nb">any</span><span class="p">(</span><span class="n">key</span> <span class="ow">in</span> <span class="s1">'.'</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">current_key_name</span><span class="p">)</span>
|
|
<span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="n">exclude_modules</span><span class="p">):</span>
|
|
<span class="n">model</span><span class="o">.</span><span class="n">_modules</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">WeightOnlyGroupwiseQuantRowLinear</span><span class="p">(</span>
|
|
<span class="n">in_features</span><span class="o">=</span><span class="n">module</span><span class="o">.</span><span class="n">in_features</span> <span class="o">*</span> <span class="n">module</span><span class="o">.</span><span class="n">tp_size</span><span class="p">,</span>
|
|
<span class="n">out_features</span><span class="o">=</span><span class="n">module</span><span class="o">.</span><span class="n">out_features</span><span class="p">,</span>
|
|
<span class="n">group_size</span><span class="o">=</span><span class="n">group_size</span><span class="p">,</span>
|
|
<span class="n">pre_quant_scale</span><span class="o">=</span><span class="n">pre_quant_scale</span><span class="p">,</span>
|
|
<span class="n">zero</span><span class="o">=</span><span class="n">zero</span><span class="p">,</span>
|
|
<span class="n">bias</span><span class="o">=</span><span class="n">module</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="n">use_w4a8_awq</span><span class="o">=</span><span class="n">weight_only_precision</span> <span class="o">==</span> <span class="s1">'w4a8_awq'</span><span class="p">,</span>
|
|
<span class="n">dtype</span><span class="o">=</span><span class="n">module</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">module</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">module</span><span class="o">.</span><span class="n">tp_size</span><span class="p">)</span>
|
|
|
|
<span class="n">current_key_name</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span>
|
|
|
|
<span class="k">return</span> <span class="n">model</span>
|
|
|
|
|
|
<div class="viewcode-block" id="quantize_model">
|
|
<a class="viewcode-back" href="../../../../python-api/tensorrt_llm.models.html#tensorrt_llm.models.quantize_model">[docs]</a>
|
|
<span class="k">def</span> <span class="nf">quantize_model</span><span class="p">(</span><span class="n">model</span><span class="p">:</span> <span class="n">Module</span><span class="p">,</span> <span class="n">quant_mode</span><span class="p">:</span> <span class="n">QuantMode</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">Any</span><span class="p">):</span>
|
|
<span class="k">if</span> <span class="n">quant_mode</span><span class="o">.</span><span class="n">is_weight_only</span><span class="p">():</span>
|
|
<span class="k">if</span> <span class="n">quant_mode</span><span class="o">.</span><span class="n">has_per_group_scaling</span><span class="p">():</span>
|
|
<span class="n">model</span> <span class="o">=</span> <span class="n">_weight_only_groupwise_quantize</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">quant_mode</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">quant_algo</span> <span class="o">=</span> <span class="n">QuantAlgo</span><span class="o">.</span><span class="n">W4A16</span> <span class="k">if</span> <span class="n">quant_mode</span><span class="o">.</span><span class="n">is_int4_weight_only</span><span class="p">(</span>
|
|
<span class="p">)</span> <span class="k">else</span> <span class="n">QuantAlgo</span><span class="o">.</span><span class="n">W8A16</span>
|
|
<span class="n">model</span> <span class="o">=</span> <span class="n">weight_only_quantize</span><span class="p">(</span>
|
|
<span class="n">model</span><span class="p">,</span> <span class="n">dataclasses</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="n">QuantConfig</span><span class="p">(</span><span class="n">quant_algo</span><span class="p">),</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">))</span>
|
|
<span class="k">elif</span> <span class="n">quant_mode</span><span class="o">.</span><span class="n">has_fp8_qdq</span><span class="p">()</span> <span class="ow">or</span> <span class="n">quant_mode</span><span class="o">.</span><span class="n">has_fp8_kv_cache</span><span class="p">():</span>
|
|
<span class="n">model</span> <span class="o">=</span> <span class="n">_fp8_quantize</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">quant_mode</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
|
<span class="k">elif</span> <span class="n">quant_mode</span><span class="o">.</span><span class="n">has_act_and_weight_quant</span><span class="p">():</span>
|
|
<span class="n">model</span> <span class="o">=</span> <span class="n">_smooth_quantize</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">quant_mode</span><span class="p">)</span>
|
|
|
|
<span class="nb">setattr</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="s2">"quant_mode"</span><span class="p">,</span> <span class="n">quant_mode</span><span class="p">)</span>
|
|
<span class="k">return</span> <span class="n">model</span></div>
|
|
|
|
|
|
|
|
<span class="k">def</span> <span class="nf">get_dummy_quant_scales</span><span class="p">(</span><span class="n">num_layers</span><span class="p">):</span>
|
|
<span class="k">return</span> <span class="p">{</span>
|
|
<span class="s1">'lm_head_act'</span><span class="p">:</span> <span class="mf">0.99</span><span class="p">,</span>
|
|
<span class="s1">'lm_head_weights'</span><span class="p">:</span> <span class="mf">0.99</span><span class="p">,</span>
|
|
<span class="s1">'fc_act'</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.99</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="s1">'fc_weights'</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.99</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="s1">'gate_act'</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.99</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="s1">'gate_weights'</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.99</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="s1">'proj_act'</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.99</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="s1">'proj_weights'</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.99</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="s1">'qkv_act'</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.99</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="s1">'qkv_weights'</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.99</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="s1">'qkv_output'</span><span class="p">:</span> <span class="p">[</span><span class="mf">1.0</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="s1">'dense_act'</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.99</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="s1">'dense_weights'</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.99</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="k">def</span> <span class="nf">_quantize_layer</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span> <span class="n">layer_idx</span><span class="p">,</span> <span class="n">quant_mode</span><span class="p">,</span> <span class="n">quant_scales</span><span class="p">):</span>
|
|
<span class="k">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span> <span class="s2">"mlp"</span><span class="p">),</span> <span class="s2">"The layer has no mlp"</span>
|
|
<span class="n">fake_fp8_sf_dt</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">float32</span>
|
|
|
|
<span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">layer</span><span class="o">.</span><span class="n">mlp</span><span class="o">.</span><span class="n">fc</span><span class="p">,</span> <span class="p">(</span><span class="n">FP8Linear</span><span class="p">,</span> <span class="n">FP8RowLinear</span><span class="p">))</span>
|
|
<span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">layer</span><span class="o">.</span><span class="n">mlp</span><span class="o">.</span><span class="n">proj</span><span class="p">,</span> <span class="p">(</span><span class="n">FP8Linear</span><span class="p">,</span> <span class="n">FP8RowLinear</span><span class="p">))</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">mlp</span><span class="o">.</span><span class="n">fc</span><span class="o">.</span><span class="n">activation_scaling_factor</span><span class="o">.</span><span class="n">value</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span>
|
|
<span class="p">[</span><span class="n">quant_scales</span><span class="p">[</span><span class="s1">'fc_act'</span><span class="p">][</span><span class="n">layer_idx</span><span class="p">]],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">fake_fp8_sf_dt</span><span class="p">)</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">mlp</span><span class="o">.</span><span class="n">fc</span><span class="o">.</span><span class="n">weights_scaling_factor</span><span class="o">.</span><span class="n">value</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span>
|
|
<span class="p">[</span><span class="n">quant_scales</span><span class="p">[</span><span class="s1">'fc_weights'</span><span class="p">][</span><span class="n">layer_idx</span><span class="p">]],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">fake_fp8_sf_dt</span><span class="p">)</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">mlp</span><span class="o">.</span><span class="n">proj</span><span class="o">.</span><span class="n">activation_scaling_factor</span><span class="o">.</span><span class="n">value</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span>
|
|
<span class="p">[</span><span class="n">quant_scales</span><span class="p">[</span><span class="s1">'proj_act'</span><span class="p">][</span><span class="n">layer_idx</span><span class="p">]],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">fake_fp8_sf_dt</span><span class="p">)</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">mlp</span><span class="o">.</span><span class="n">proj</span><span class="o">.</span><span class="n">weights_scaling_factor</span><span class="o">.</span><span class="n">value</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span>
|
|
<span class="p">[</span><span class="n">quant_scales</span><span class="p">[</span><span class="s1">'proj_weights'</span><span class="p">][</span><span class="n">layer_idx</span><span class="p">]],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">fake_fp8_sf_dt</span><span class="p">)</span>
|
|
<span class="k">if</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="o">.</span><span class="n">mlp</span><span class="p">,</span> <span class="s1">'gate'</span><span class="p">):</span>
|
|
<span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">layer</span><span class="o">.</span><span class="n">mlp</span><span class="o">.</span><span class="n">gate</span><span class="p">,</span> <span class="p">(</span><span class="n">FP8Linear</span><span class="p">,</span> <span class="n">FP8RowLinear</span><span class="p">))</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">mlp</span><span class="o">.</span><span class="n">gate</span><span class="o">.</span><span class="n">activation_scaling_factor</span><span class="o">.</span><span class="n">value</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span>
|
|
<span class="p">[</span><span class="n">quant_scales</span><span class="p">[</span><span class="s1">'gate_act'</span><span class="p">][</span><span class="n">layer_idx</span><span class="p">]],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">fake_fp8_sf_dt</span><span class="p">)</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">mlp</span><span class="o">.</span><span class="n">gate</span><span class="o">.</span><span class="n">weights_scaling_factor</span><span class="o">.</span><span class="n">value</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span>
|
|
<span class="p">[</span><span class="n">quant_scales</span><span class="p">[</span><span class="s1">'gate_weights'</span><span class="p">][</span><span class="n">layer_idx</span><span class="p">]],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">fake_fp8_sf_dt</span><span class="p">)</span>
|
|
|
|
<span class="k">assert</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span> <span class="s2">"attention"</span><span class="p">),</span> <span class="s2">"The layer has no attention"</span>
|
|
<span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">layer</span><span class="o">.</span><span class="n">attention</span><span class="o">.</span><span class="n">qkv</span><span class="p">,</span> <span class="p">(</span><span class="n">FP8Linear</span><span class="p">,</span> <span class="n">FP8RowLinear</span><span class="p">))</span>
|
|
<span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">layer</span><span class="o">.</span><span class="n">attention</span><span class="o">.</span><span class="n">dense</span><span class="p">,</span> <span class="p">(</span><span class="n">FP8Linear</span><span class="p">,</span> <span class="n">FP8RowLinear</span><span class="p">))</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">attention</span><span class="o">.</span><span class="n">qkv</span><span class="o">.</span><span class="n">activation_scaling_factor</span><span class="o">.</span><span class="n">value</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span>
|
|
<span class="p">[</span><span class="n">quant_scales</span><span class="p">[</span><span class="s1">'qkv_act'</span><span class="p">][</span><span class="n">layer_idx</span><span class="p">]],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">fake_fp8_sf_dt</span><span class="p">)</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">attention</span><span class="o">.</span><span class="n">qkv</span><span class="o">.</span><span class="n">weights_scaling_factor</span><span class="o">.</span><span class="n">value</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span>
|
|
<span class="p">[</span><span class="n">quant_scales</span><span class="p">[</span><span class="s1">'qkv_weights'</span><span class="p">][</span><span class="n">layer_idx</span><span class="p">]],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">fake_fp8_sf_dt</span><span class="p">)</span>
|
|
<span class="k">if</span> <span class="n">quant_mode</span><span class="o">.</span><span class="n">has_fp8_kv_cache</span><span class="p">():</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">attention</span><span class="o">.</span><span class="n">kv_cache_scaling_factor</span><span class="o">.</span><span class="n">value</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span>
|
|
<span class="p">[</span><span class="n">quant_scales</span><span class="p">[</span><span class="s1">'qkv_output'</span><span class="p">][</span><span class="n">layer_idx</span><span class="p">]],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">fake_fp8_sf_dt</span><span class="p">)</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">attention</span><span class="o">.</span><span class="n">dense</span><span class="o">.</span><span class="n">activation_scaling_factor</span><span class="o">.</span><span class="n">value</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span>
|
|
<span class="p">[</span><span class="n">quant_scales</span><span class="p">[</span><span class="s1">'dense_act'</span><span class="p">][</span><span class="n">layer_idx</span><span class="p">]],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">fake_fp8_sf_dt</span><span class="p">)</span>
|
|
<span class="n">layer</span><span class="o">.</span><span class="n">attention</span><span class="o">.</span><span class="n">dense</span><span class="o">.</span><span class="n">weights_scaling_factor</span><span class="o">.</span><span class="n">value</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span>
|
|
<span class="p">[</span><span class="n">quant_scales</span><span class="p">[</span><span class="s1">'dense_weights'</span><span class="p">][</span><span class="n">layer_idx</span><span class="p">]],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">fake_fp8_sf_dt</span><span class="p">)</span>
|
|
|
|
<span class="k">return</span> <span class="n">layer</span>
|
|
|
|
|
|
<span class="k">def</span> <span class="nf">_default_fp8_quantize</span><span class="p">(</span><span class="n">model</span><span class="p">,</span>
|
|
<span class="n">quant_mode</span><span class="p">:</span> <span class="n">QuantMode</span><span class="p">,</span>
|
|
<span class="n">quant_scales</span><span class="p">:</span> <span class="nb">dict</span> <span class="o">=</span> <span class="kc">None</span><span class="p">):</span>
|
|
<span class="w"> </span><span class="sd">"""</span>
|
|
<span class="sd"> Quantize all linear layers (i.e., MLP, Attention QKV/Dense) and KV cache IO with dummy scales</span>
|
|
<span class="sd"> This is used by benchmark script and therefore is intentionally decoupled from AMMO toolkit</span>
|
|
<span class="sd"> """</span>
|
|
<span class="k">if</span> <span class="n">quant_scales</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
|
<span class="n">num_layers</span> <span class="o">=</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="s1">'_num_layers'</span><span class="p">,</span>
|
|
<span class="nb">getattr</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="s1">'num_layers'</span><span class="p">,</span> <span class="kc">None</span><span class="p">))</span>
|
|
<span class="k">assert</span> <span class="n">num_layers</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span>
|
|
<span class="n">quant_scales</span> <span class="o">=</span> <span class="n">get_dummy_quant_scales</span><span class="p">(</span><span class="n">num_layers</span><span class="p">)</span>
|
|
|
|
<span class="k">assert</span> <span class="n">model</span><span class="o">.</span><span class="n">quant_mode</span> <span class="o">==</span> <span class="n">quant_mode</span><span class="p">,</span> <span class="s2">"Quant setting not consistent with model init setting"</span>
|
|
|
|
<span class="n">use_fp8_qdq</span> <span class="o">=</span> <span class="n">quant_mode</span><span class="o">.</span><span class="n">has_fp8_qdq</span><span class="p">()</span>
|
|
<span class="k">assert</span> <span class="n">use_fp8_qdq</span>
|
|
|
|
<span class="k">for</span> <span class="n">layer_idx</span><span class="p">,</span> <span class="n">layer</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">layers</span><span class="p">):</span>
|
|
<span class="n">layer</span> <span class="o">=</span> <span class="n">_quantize_layer</span><span class="p">(</span><span class="n">layer</span><span class="p">,</span> <span class="n">layer_idx</span><span class="p">,</span> <span class="n">quant_mode</span><span class="p">,</span> <span class="n">quant_scales</span><span class="p">)</span>
|
|
|
|
<span class="c1"># TODO: add lm_head</span>
|
|
|
|
<span class="k">return</span> <span class="n">model</span>
|
|
|
|
|
|
<span class="k">def</span> <span class="nf">_fp8_quantize</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">quant_mode</span><span class="p">:</span> <span class="n">QuantMode</span><span class="p">,</span> <span class="n">quant_scales</span><span class="p">:</span> <span class="nb">dict</span> <span class="o">=</span> <span class="kc">None</span><span class="p">):</span>
|
|
<span class="kn">from</span> <span class="nn">...models</span> <span class="kn">import</span> <span class="p">(</span><span class="n">BaichuanForCausalLM</span><span class="p">,</span> <span class="n">FalconForCausalLM</span><span class="p">,</span>
|
|
<span class="n">GPTForCausalLM</span><span class="p">,</span> <span class="n">GPTJForCausalLM</span><span class="p">,</span> <span class="n">LLaMAForCausalLM</span><span class="p">)</span>
|
|
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="p">(</span><span class="n">FalconForCausalLM</span><span class="p">,</span> <span class="n">GPTJForCausalLM</span><span class="p">,</span> <span class="n">GPTForCausalLM</span><span class="p">,</span>
|
|
<span class="n">LLaMAForCausalLM</span><span class="p">,</span> <span class="n">BaichuanForCausalLM</span><span class="p">)):</span>
|
|
<span class="k">return</span> <span class="n">_default_fp8_quantize</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">quant_mode</span><span class="p">,</span> <span class="n">quant_scales</span><span class="p">)</span>
|
|
<span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">(</span>
|
|
<span class="sa">f</span><span class="s2">"Model </span><span class="si">{</span><span class="n">model</span><span class="si">}</span><span class="s2"> is not implemented by fp8_quantize yet"</span><span class="p">)</span>
|
|
</pre></div>
|
|
|
|
</div>
|
|
</div>
|
|
<footer>
|
|
|
|
<hr/>
|
|
|
|
<div role="contentinfo">
|
|
<p>© Copyright 2023, NVidia.</p>
|
|
</div>
|
|
|
|
Built with <a href="https://www.sphinx-doc.org/">Sphinx</a> using a
|
|
<a href="https://github.com/readthedocs/sphinx_rtd_theme">theme</a>
|
|
provided by <a href="https://readthedocs.org">Read the Docs</a>.
|
|
|
|
|
|
</footer>
|
|
</div>
|
|
</div>
|
|
</section>
|
|
</div>
|
|
<script>
|
|
jQuery(function () {
|
|
SphinxRtdTheme.Navigation.enable(true);
|
|
});
|
|
</script>
|
|
|
|
</body>
|
|
</html> |