labmlai--annotated_deep_learning_paper_implementations
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<h1>Zero-DP Memory Optimization</h1>
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<p>This is an implementation of Zero-DP introduced in the paper <a href="https://arxiv.org/abs/1910.02054">ZeRO: Memory Optimization Towards Training A Trillion Parameter Models</a>,</p>
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<p>It keeps shards of the optimizer state, gradients and parameters into multiple devices/nodes. It reduces the memory consumption to <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:1.4608599999999998em;vertical-align:-0.4508599999999999em;"></span><span class="mord"><span class="mopen nulldelimiter"></span><span class="mfrac"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:1.01em;"><span style="top:-2.655em;"><span class="pstrut" style="height:3em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mord mtight coloredeq eqg" style=""><span class="mord mtight" style=""><span class="mord mathnormal mtight" style="margin-right:0.10903em">N</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.3448em;"><span style="top:-2.3487714285714287em;margin-left:-0.10903em;margin-right:0.07142857142857144em;"><span class="pstrut" style="height:2.5em;"></span><span class="sizing reset-size3 size1 mtight" style=""><span class="mord mathnormal mtight" style="">d</span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.15122857142857138em;"><span></span></span></span></span></span></span></span></span></span></span><span style="top:-3.23em;"><span class="pstrut" style="height:3em;"></span><span class="frac-line" style="border-bottom-width:0.04em;"></span></span><span style="top:-3.485em;"><span class="pstrut" style="height:3em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mtight"><span class="mopen mtight">(</span><span class="mord mtight coloredeq eqe" style=""><span class="mord mtight" style="">2</span><span class="mbin mtight" style="">+</span><span class="mord mtight" style="">2</span></span><span class="mbin mtight">+</span><span class="mord mtight coloredeq eqi" style=""><span class="mord mathnormal mtight" style="margin-right:0.07153em">K</span></span><span class="mclose mtight">)</span><span class="mord mtight coloredeq eqf" style=""><span class="mord mtight" style="">Ψ</span></span></span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.4508599999999999em;"><span></span></span></span></span></span><span class="mclose nulldelimiter"></span></span></span></span></span></span> of the original model, where <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.68333em;vertical-align:0em;"></span><span class="mord coloredeq eqf" style=""><span class="mord" style="">Ψ</span></span></span></span></span></span> is the number of parameters, <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.83333em;vertical-align:-0.15em;"></span><span class="mord coloredeq eqg" style=""><span class="mord" style=""><span class="mord mathnormal" style="margin-right:0.10903em">N</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.33610799999999996em;"><span style="top:-2.5500000000000003em;margin-left:-0.10903em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight" style=""><span class="mord mathnormal mtight" style="">d</span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span></span></span></span></span></span> is the number of shards, and <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.68333em;vertical-align:0em;"></span><span class="mord coloredeq eqi" style=""><span class="mord mathnormal" style="margin-right:0.07153em">K</span></span></span></span></span></span> is number of optimizer bytes per parameter. <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.72777em;vertical-align:-0.08333em;"></span><span class="mord coloredeq eqe" style=""><span class="mord" style="">2</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mbin" style="">+</span><span class="mspace" style="margin-right:0.2222222222222222em;"></span><span class="mord" style="">2</span></span></span></span></span></span> are the parameter and gradient memory assuming 16-bit precision; i.e. 2 bytes per parameter and gradient. <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.68333em;vertical-align:0em;"></span><span class="mord coloredeq eqi" style=""><span class="mord mathnormal" style="margin-right:0.07153em">K</span></span><span class="mspace" style="margin-right:0.2777777777777778em;"></span><span class="mrel">=</span><span class="mspace" style="margin-right:0.2777777777777778em;"></span></span><span class="base"><span class="strut" style="height:0.64444em;vertical-align:0em;"></span><span class="mord">12</span></span></span></span></span> for Adam optimizer because it maintains a copy of parameters, and two moments per parameter in fp32.</p>
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<p>The communication volume of Zero-DP is <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathcal" style="margin-right:0.02778em;">O</span><span class="mopen">(</span><span class="mord">3</span><span class="mord coloredeq eqf" style=""><span class="mord" style="">Ψ</span></span><span class="mclose">)</span></span></span></span></span>. For comparison data-parallel training has a communication volume of <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord mathcal" style="margin-right:0.02778em;">O</span><span class="mopen">(</span><span class="mord">2</span><span class="mord coloredeq eqf" style=""><span class="mord" style="">Ψ</span></span><span class="mclose">)</span></span></span></span></span>.</p>
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<p>Although this is named <code class="highlight"><span></span><span class="n">Zero3</span></code>
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, we have only implemented the Zero-DP part of it and not the Zero-R memory optimizations which target residual memory consumption. Out implementation supports training only a subset of parameters.</p>
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<p>This implementation is inspired by <a href="https://fairscale.readthedocs.io/en/stable/api/nn/fsdp.html">Fairscale FSDP</a>.</p>
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<p><a href="finetune_neox.html">Here's a script to fine-tune</a> GPT NeoX using Zero-DP memory optimization.</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">32</span><span></span><span class="kn">import</span> <span class="nn">functools</span>
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<span class="lineno">33</span><span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">List</span><span class="p">,</span> <span class="n">Optional</span><span class="p">,</span> <span class="n">Tuple</span>
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<span class="lineno">34</span>
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<span class="lineno">35</span><span class="kn">import</span> <span class="nn">torch</span>
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<span class="lineno">36</span><span class="kn">import</span> <span class="nn">torch.distributed</span> <span class="k">as</span> <span class="nn">dist</span>
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<span class="lineno">37</span><span class="kn">from</span> <span class="nn">torch</span> <span class="kn">import</span> <span class="n">nn</span></pre></div>
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<div class='section' id='section-1'>
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<div class='docs doc-strings'>
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<div class='section-link'>
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<a href='#section-1'>#</a>
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</div>
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<h2>Zero3 Layer</h2>
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<p>Each layer of the model (or a combination of a few consecutive layers) should be wrapped in this module.</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">40</span><span class="k">class</span> <span class="nc">Zero3Layer</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span></pre></div>
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<div class='section' id='section-2'>
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<a href='#section-2'>#</a>
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<p>Each shard keeps parameters in <code class="highlight"><span></span><span class="n">chunk</span></code>
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list. The <code class="highlight"><span></span><span class="n">chunk</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span></code>
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is for trainable parameters and <code class="highlight"><span></span><span class="n">chunk</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span></code>
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is for fixed parameters. </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">49</span> <span class="n">chunk</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="n">nn</span><span class="o">.</span><span class="n">Parameter</span><span class="p">]</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-3'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-3'>#</a>
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</div>
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<p>This is the sizes of the chunks in <code class="highlight"><span></span><span class="n">chunk</span></code>
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list. </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">51</span> <span class="n">chunk_size</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span></pre></div>
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<div class='section' id='section-4'>
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<div class='section-link'>
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<a href='#section-4'>#</a>
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<p>The first chunk is for trainable parameters. </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">53</span> <span class="n">TRAINING_PARAMS_IDX</span> <span class="o">=</span> <span class="mi">0</span></pre></div>
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<div class='section' id='section-5'>
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<div class='section-link'>
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<a href='#section-5'>#</a>
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<p>This is the list of parameters split into lists as trainable and fixed parameters. </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">56</span> <span class="n">param_refs</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="n">List</span><span class="p">[</span><span class="n">nn</span><span class="o">.</span><span class="n">Parameter</span><span class="p">]]</span></pre></div>
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<div class='section' id='section-6'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-6'>#</a>
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<p>CUDA stream to featch parameters </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">59</span> <span class="n">fetch_stream</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">Stream</span><span class="p">]</span></pre></div>
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<div class='section' id='section-7'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-7'>#</a>
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</div>
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<p>CUDA stream to backup/accumulate gradients </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">61</span> <span class="n">backup_stream</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">Stream</span><span class="p">]</span></pre></div>
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<div class='section' id='section-8'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-8'>#</a>
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</div>
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<p>List of layers right before this layer </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">63</span> <span class="n">prev_layer</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="s1">'Zero3Layer'</span><span class="p">]</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-9'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-9'>#</a>
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</div>
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<p>List of layers right after this layer </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">65</span> <span class="n">next_layer</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="s1">'Zero3Layer'</span><span class="p">]</span></pre></div>
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<div class='section' id='section-10'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-10'>#</a>
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<p>The position of the current layer; used this for debugging logs </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">67</span> <span class="n">layer_idx</span><span class="p">:</span> <span class="nb">int</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-11'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-11'>#</a>
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<p>Whether parameters have been fetched </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">70</span> <span class="n">is_fetched</span><span class="p">:</span> <span class="nb">bool</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-12'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-12'>#</a>
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<p>Device of the layer </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">73</span> <span class="n">device</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">device</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-13'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-13'>#</a>
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</div>
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<p>Data type of the layer </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">75</span> <span class="n">dtype</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">dtype</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-14'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-14'>#</a>
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</div>
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<p>The module to be wrapped </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">77</span> <span class="n">module</span><span class="p">:</span> <span class="n">nn</span><span class="o">.</span><span class="n">Module</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-15'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-15'>#</a>
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</div>
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<p>Number of nodes/devices the data is sharded across </p>
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</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">79</span> <span class="n">world_size</span><span class="p">:</span> <span class="nb">int</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-16'>
|
||
<div class='docs doc-strings'>
|
||
<div class='section-link'>
|
||
<a href='#section-16'>#</a>
|
||
</div>
|
||
<ul><li><code class="highlight"><span></span><span class="n">module</span></code>
|
||
The module to be wrapped. </li>
|
||
<li><code class="highlight"><span></span><span class="n">rank</span></code>
|
||
The rank of the current node. </li>
|
||
<li><code class="highlight"><span></span><span class="n">world_size</span></code>
|
||
The number of nodes/devices the data is sharded across. </li>
|
||
<li><code class="highlight"><span></span><span class="n">device</span></code>
|
||
The device of the layer. </li>
|
||
<li><code class="highlight"><span></span><span class="n">dtype</span></code>
|
||
The data type of the layer.</li></ul>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">81</span> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">module</span><span class="p">:</span> <span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">,</span> <span class="n">rank</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">world_size</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">device</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">device</span><span class="p">,</span> <span class="n">dtype</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">dtype</span><span class="p">):</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-17'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-17'>#</a>
|
||
</div>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">89</span> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-18'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-18'>#</a>
|
||
</div>
|
||
<p>Initialize the properties </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">92</span> <span class="bp">self</span><span class="o">.</span><span class="n">device</span> <span class="o">=</span> <span class="n">device</span>
|
||
<span class="lineno">93</span> <span class="bp">self</span><span class="o">.</span><span class="n">dtype</span> <span class="o">=</span> <span class="n">dtype</span>
|
||
<span class="lineno">94</span> <span class="bp">self</span><span class="o">.</span><span class="n">module</span> <span class="o">=</span> <span class="n">module</span>
|
||
<span class="lineno">95</span> <span class="bp">self</span><span class="o">.</span><span class="n">prev_layer</span> <span class="o">=</span> <span class="p">[]</span>
|
||
<span class="lineno">96</span> <span class="bp">self</span><span class="o">.</span><span class="n">next_layer</span> <span class="o">=</span> <span class="p">[]</span>
|
||
<span class="lineno">97</span> <span class="bp">self</span><span class="o">.</span><span class="n">is_fetched</span> <span class="o">=</span> <span class="kc">False</span>
|
||
<span class="lineno">98</span> <span class="bp">self</span><span class="o">.</span><span class="n">world_size</span> <span class="o">=</span> <span class="n">world_size</span>
|
||
<span class="lineno">99</span> <span class="bp">self</span><span class="o">.</span><span class="n">layer_idx</span> <span class="o">=</span> <span class="o">-</span><span class="mi">1</span>
|
||
<span class="lineno">100</span> <span class="bp">self</span><span class="o">.</span><span class="n">fetch_stream</span> <span class="o">=</span> <span class="kc">None</span>
|
||
<span class="lineno">101</span> <span class="bp">self</span><span class="o">.</span><span class="n">backup_stream</span> <span class="o">=</span> <span class="kc">None</span>
|
||
<span class="lineno">102</span>
|
||
<span class="lineno">103</span> <span class="k">with</span> <span class="n">torch</span><span class="o">.</span><span class="n">no_grad</span><span class="p">():</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-19'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-19'>#</a>
|
||
</div>
|
||
<p>Collect all the parameters of the layer </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">105</span> <span class="n">all_param_refs</span> <span class="o">=</span> <span class="p">[</span><span class="n">p</span> <span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">parameters</span><span class="p">()]</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-20'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-20'>#</a>
|
||
</div>
|
||
<p>Store the shape of the parameters because we need it later to reconstruct them </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">108</span> <span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">all_param_refs</span><span class="p">:</span>
|
||
<span class="lineno">109</span> <span class="n">p</span><span class="o">.</span><span class="n">_orig_shape</span> <span class="o">=</span> <span class="n">p</span><span class="o">.</span><span class="n">shape</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-21'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-21'>#</a>
|
||
</div>
|
||
<p>All parameters should have the same type </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">112</span> <span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">all_param_refs</span><span class="p">:</span>
|
||
<span class="lineno">113</span> <span class="k">assert</span> <span class="n">p</span><span class="o">.</span><span class="n">dtype</span> <span class="o">==</span> <span class="n">dtype</span><span class="p">,</span> <span class="s2">"All parameters should have same dtype"</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-22'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-22'>#</a>
|
||
</div>
|
||
<p>Separate parameters as trainable and fixed </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">116</span> <span class="bp">self</span><span class="o">.</span><span class="n">param_refs</span> <span class="o">=</span> <span class="p">[[</span><span class="n">p</span> <span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">all_param_refs</span> <span class="k">if</span> <span class="n">p</span><span class="o">.</span><span class="n">requires_grad</span><span class="p">],</span>
|
||
<span class="lineno">117</span> <span class="p">[</span><span class="n">p</span> <span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">all_param_refs</span> <span class="k">if</span> <span class="ow">not</span> <span class="n">p</span><span class="o">.</span><span class="n">requires_grad</span><span class="p">]]</span>
|
||
<span class="lineno">118</span> <span class="k">del</span> <span class="n">all_param_refs</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-23'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-23'>#</a>
|
||
</div>
|
||
<p>The <code class="highlight"><span></span><span class="n">rank</span> <span class="o">=</span> <span class="mi">0</span></code>
|
||
node will calculate the size each device/node should store, and distribute the parameters accordingly. </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">122</span> <span class="k">if</span> <span class="n">rank</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-24'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-24'>#</a>
|
||
</div>
|
||
<p>Merge and pad trainable (<code class="highlight"><span></span><span class="n">merged_params</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span></code>
|
||
) and fixed (<code class="highlight"><span></span><span class="n">merged_params</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span></code>
|
||
) parameters </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">124</span> <span class="n">merged_params</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">_merge_and_pad_params</span><span class="p">(</span><span class="n">ps</span><span class="p">)</span> <span class="k">for</span> <span class="n">ps</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">param_refs</span><span class="p">]</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-25'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-25'>#</a>
|
||
</div>
|
||
<p>Calculate the chunk sizes of trainable and fixed params </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">126</span> <span class="bp">self</span><span class="o">.</span><span class="n">chunk_size</span> <span class="o">=</span> <span class="p">[(</span><span class="nb">len</span><span class="p">(</span><span class="n">p</span><span class="p">)</span> <span class="o">//</span> <span class="n">world_size</span> <span class="k">if</span> <span class="n">p</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="k">else</span> <span class="mi">0</span><span class="p">)</span> <span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">merged_params</span><span class="p">]</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-26'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-26'>#</a>
|
||
</div>
|
||
<p>Broadcast the sizes </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">128</span> <span class="n">dist</span><span class="o">.</span><span class="n">broadcast</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">chunk_size</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="n">device</span><span class="p">),</span> <span class="n">src</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
|
||
<span class="lineno">129</span> <span class="k">else</span><span class="p">:</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-27'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-27'>#</a>
|
||
</div>
|
||
<p>Create an empty tensor to receive the sizes </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">131</span> <span class="n">chunk_size</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span> <span class="n">device</span><span class="o">=</span><span class="n">device</span><span class="p">)</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-28'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-28'>#</a>
|
||
</div>
|
||
<p>Receive the sizes </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">133</span> <span class="n">dist</span><span class="o">.</span><span class="n">broadcast</span><span class="p">(</span><span class="n">chunk_size</span><span class="p">,</span> <span class="n">src</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
|
||
<span class="lineno">134</span> <span class="bp">self</span><span class="o">.</span><span class="n">chunk_size</span> <span class="o">=</span> <span class="n">chunk_size</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-29'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-29'>#</a>
|
||
</div>
|
||
<p>Create parameters for trainable (<code class="highlight"><span></span><span class="bp">self</span><span class="o">.</span><span class="n">chunk</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span></code>
|
||
) and fixed (<code class="highlight"><span></span><span class="bp">self</span><span class="o">.</span><span class="n">chunk</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span></code>
|
||
) parameters to be stored in current device/node </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">138</span> <span class="bp">self</span><span class="o">.</span><span class="n">chunk</span> <span class="o">=</span> <span class="p">[</span><span class="n">nn</span><span class="o">.</span><span class="n">Parameter</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_empty</span><span class="p">((</span><span class="n">s</span><span class="p">,)),</span> <span class="n">requires_grad</span><span class="o">=</span><span class="n">i</span> <span class="o">==</span> <span class="bp">self</span><span class="o">.</span><span class="n">TRAINING_PARAMS_IDX</span><span class="p">)</span>
|
||
<span class="lineno">139</span> <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">s</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">chunk_size</span><span class="p">)]</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-30'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-30'>#</a>
|
||
</div>
|
||
<p>An empty tensor to receive the trainable and fixed parameters combined </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">142</span> <span class="n">chunk</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_empty</span><span class="p">((</span><span class="nb">sum</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">chunk_size</span><span class="p">),))</span>
|
||
<span class="lineno">143</span>
|
||
<span class="lineno">144</span> <span class="k">if</span> <span class="n">rank</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-31'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-31'>#</a>
|
||
</div>
|
||
<p>Concatenate both trainable and fixed params </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">146</span> <span class="n">all_params</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">cat</span><span class="p">([</span><span class="n">p</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="n">world_size</span><span class="p">,</span> <span class="o">-</span><span class="mi">1</span><span class="p">)</span> <span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">merged_params</span><span class="p">],</span> <span class="n">dim</span><span class="o">=-</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span>
|
||
<span class="lineno">147</span> <span class="k">del</span> <span class="n">merged_params</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-32'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-32'>#</a>
|
||
</div>
|
||
<p>Scatter them to all the nodes/devices </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">150</span> <span class="n">dist</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">chunk</span><span class="p">,</span> <span class="nb">list</span><span class="p">(</span><span class="n">all_params</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="nb">sum</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">chunk_size</span><span class="p">))))</span>
|
||
<span class="lineno">151</span> <span class="k">del</span> <span class="n">all_params</span>
|
||
<span class="lineno">152</span> <span class="k">else</span><span class="p">:</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-33'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-33'>#</a>
|
||
</div>
|
||
<p>Receive the parameters </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">154</span> <span class="n">dist</span><span class="o">.</span><span class="n">scatter</span><span class="p">(</span><span class="n">chunk</span><span class="p">)</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-34'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-34'>#</a>
|
||
</div>
|
||
<p>Collect the chunk data </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">157</span> <span class="n">chunk</span> <span class="o">=</span> <span class="n">chunk</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">chunk_size</span><span class="p">)</span>
|
||
<span class="lineno">158</span> <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">c</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">chunk</span><span class="p">):</span>
|
||
<span class="lineno">159</span> <span class="bp">self</span><span class="o">.</span><span class="n">chunk</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">data</span><span class="p">[:]</span> <span class="o">=</span> <span class="n">c</span>
|
||
<span class="lineno">160</span> <span class="k">del</span> <span class="n">chunk</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-35'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-35'>#</a>
|
||
</div>
|
||
<p>Cleanup the normal parameters </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">163</span> <span class="bp">self</span><span class="o">.</span><span class="n">_cleanup_params</span><span class="p">()</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-36'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-36'>#</a>
|
||
</div>
|
||
<p>Add a backward hook. This gets called when the gradients relative to the module are computed. </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">166</span> <span class="bp">self</span><span class="o">.</span><span class="n">_backward_hook_ref</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">register_full_backward_hook</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_backward_hook</span><span class="p">)</span> <span class="c1"># type: ignore</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-37'>
|
||
<div class='docs doc-strings'>
|
||
<div class='section-link'>
|
||
<a href='#section-37'>#</a>
|
||
</div>
|
||
<h4>Merge all the parameters and pad it so that it's divisible by <code class="highlight"><span></span><span class="n">world_size</span></code>
|
||
.</h4>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">168</span> <span class="k">def</span> <span class="nf">_merge_and_pad_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">params</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="n">nn</span><span class="o">.</span><span class="n">Parameter</span><span class="p">])</span> <span class="o">-></span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">:</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-38'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-38'>#</a>
|
||
</div>
|
||
<p>Total number of parameters </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">173</span> <span class="n">size</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">p</span><span class="o">.</span><span class="n">shape</span><span class="o">.</span><span class="n">numel</span><span class="p">()</span> <span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">params</span><span class="p">)</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-39'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-39'>#</a>
|
||
</div>
|
||
<p>If it is not divisible by <code class="highlight"><span></span><span class="n">world_size</span></code>
|
||
, pad it </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">176</span> <span class="k">if</span> <span class="n">size</span> <span class="o">%</span> <span class="bp">self</span><span class="o">.</span><span class="n">world_size</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span>
|
||
<span class="lineno">177</span> <span class="n">padding_fixed</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">world_size</span> <span class="o">-</span> <span class="p">(</span><span class="n">size</span> <span class="o">%</span> <span class="bp">self</span><span class="o">.</span><span class="n">world_size</span><span class="p">)</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-40'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-40'>#</a>
|
||
</div>
|
||
<p>Otherwise, no need to pad </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">179</span> <span class="k">else</span><span class="p">:</span>
|
||
<span class="lineno">180</span> <span class="n">padding_fixed</span> <span class="o">=</span> <span class="mi">0</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-41'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-41'>#</a>
|
||
</div>
|
||
<p>Create an empty padding tensor </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">182</span> <span class="n">padding</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_empty</span><span class="p">((</span><span class="n">padding_fixed</span><span class="p">,))</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-42'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-42'>#</a>
|
||
</div>
|
||
<p>Concatenate all the parameters and pad it </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">184</span> <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">cat</span><span class="p">([</span><span class="n">p</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span> <span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">params</span><span class="p">]</span> <span class="o">+</span> <span class="p">[</span><span class="n">padding</span><span class="p">],</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-43'>
|
||
<div class='docs doc-strings'>
|
||
<div class='section-link'>
|
||
<a href='#section-43'>#</a>
|
||
</div>
|
||
<h3>Get trainable chunk/shard of the parameters.</h3>
|
||
<p>This is what we pass on to the optimizer on the current node.</p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">186</span> <span class="k">def</span> <span class="nf">get_trainable_chunk</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-></span> <span class="n">List</span><span class="p">[</span><span class="n">nn</span><span class="o">.</span><span class="n">Parameter</span><span class="p">]:</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-44'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-44'>#</a>
|
||
</div>
|
||
<p>Return and empty list if there are no trainable parameters </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">193</span> <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">chunk</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">TRAINING_PARAMS_IDX</span><span class="p">])</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
|
||
<span class="lineno">194</span> <span class="k">return</span> <span class="p">[]</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-45'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-45'>#</a>
|
||
</div>
|
||
<p>Return the trainable chunk as a list </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">197</span> <span class="k">return</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">chunk</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">TRAINING_PARAMS_IDX</span><span class="p">]]</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-46'>
|
||
<div class='docs doc-strings'>
|
||
<div class='section-link'>
|
||
<a href='#section-46'>#</a>
|
||
</div>
|
||
<h4>Create an empty tensor of the given shape.</h4>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">199</span> <span class="k">def</span> <span class="nf">_empty</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">shape</span><span class="p">:</span> <span class="n">Tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">])</span> <span class="o">-></span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">:</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-47'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-47'>#</a>
|
||
</div>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">203</span> <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">empty</span><span class="p">(</span><span class="n">shape</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">device</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-48'>
|
||
<div class='docs doc-strings'>
|
||
<div class='section-link'>
|
||
<a href='#section-48'>#</a>
|
||
</div>
|
||
<h4>Cleanup the parameter data</h4>
|
||
<p>This will release all the memory used by the layer parameters.</p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">205</span> <span class="nd">@torch</span><span class="o">.</span><span class="n">no_grad</span><span class="p">()</span>
|
||
<span class="lineno">206</span> <span class="k">def</span> <span class="nf">_cleanup_params</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-49'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-49'>#</a>
|
||
</div>
|
||
<p>Set the flag to indicate that the parameters are not fetched </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">214</span> <span class="bp">self</span><span class="o">.</span><span class="n">is_fetched</span> <span class="o">=</span> <span class="kc">False</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-50'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-50'>#</a>
|
||
</div>
|
||
<p>Iterate through all parameters </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">217</span> <span class="k">for</span> <span class="n">ps</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">param_refs</span><span class="p">:</span>
|
||
<span class="lineno">218</span> <span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">ps</span><span class="p">:</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-51'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-51'>#</a>
|
||
</div>
|
||
<p>Wait for operations on the parameters to complete before any new operations </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">220</span> <span class="n">p</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">record_stream</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">current_stream</span><span class="p">())</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-52'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-52'>#</a>
|
||
</div>
|
||
<p>Check to make sure the parameter is not sharing storage with anything else </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">222</span> <span class="k">assert</span> <span class="n">p</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">storage_offset</span><span class="p">()</span> <span class="o">==</span> <span class="mi">0</span><span class="p">,</span> <span class="s2">"The tensor is not the sole occupant of the storage."</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-53'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-53'>#</a>
|
||
</div>
|
||
<p>Resize the storage to <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.64444em;vertical-align:0em;"></span><span class="mord coloredeq eqh" style=""><span class="mord" style="">0</span></span></span></span></span></span>. This will release the memory used by the parameter.</p>
|
||
<p><strong>Setting <code class="highlight"><span></span><span class="n">p</span><span class="o">.</span><span class="n">data</span></code>
|
||
will not release the memory, since the autograd graph keeps a reference to it.</strong> </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">226</span> <span class="n">p</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">storage</span><span class="p">()</span><span class="o">.</span><span class="n">resize_</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span> <span class="c1"># This is what actually clears the memory</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-54'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-54'>#</a>
|
||
</div>
|
||
<p>Make sure the parameter has no gradient data </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">228</span> <span class="k">assert</span> <span class="n">p</span><span class="o">.</span><span class="n">grad</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">,</span> <span class="s1">'Gradients should be None'</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-55'>
|
||
<div class='docs doc-strings'>
|
||
<div class='section-link'>
|
||
<a href='#section-55'>#</a>
|
||
</div>
|
||
<h3>Fetch the parameters from all shards</h3>
|
||
<p>This will fetch all the parameter data from all the nodes and rebuild the parameters on each node.</p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">230</span> <span class="nd">@torch</span><span class="o">.</span><span class="n">no_grad</span><span class="p">()</span>
|
||
<span class="lineno">231</span> <span class="k">def</span> <span class="nf">fetch_params</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-56'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-56'>#</a>
|
||
</div>
|
||
<p>Skip is already fetched </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">239</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">is_fetched</span><span class="p">:</span>
|
||
<span class="lineno">240</span> <span class="k">return</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-57'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-57'>#</a>
|
||
</div>
|
||
<p>Set the flag </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">243</span> <span class="bp">self</span><span class="o">.</span><span class="n">is_fetched</span> <span class="o">=</span> <span class="kc">True</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-58'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-58'>#</a>
|
||
</div>
|
||
<p>Skip if there's nothing to fetch or share. </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">246</span> <span class="k">if</span> <span class="nb">sum</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">chunk_size</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
|
||
<span class="lineno">247</span> <span class="k">return</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-59'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-59'>#</a>
|
||
</div>
|
||
<p>Use <code class="highlight"><span></span><span class="n">fetch_stream</span></code>
|
||
to fetch the parameters from all the shards </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">250</span> <span class="k">with</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">stream</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">fetch_stream</span><span class="p">):</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-60'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-60'>#</a>
|
||
</div>
|
||
<p>Create an empty tensor to receive the parameters </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">252</span> <span class="n">buffer</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_empty</span><span class="p">((</span><span class="bp">self</span><span class="o">.</span><span class="n">world_size</span> <span class="o">*</span> <span class="nb">sum</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">chunk_size</span><span class="p">),))</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-61'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-61'>#</a>
|
||
</div>
|
||
<p>Split the continuous buffer into the number of nodes. These splits are views of `buffer'. </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">254</span> <span class="n">buffers</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">buffer</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="nb">sum</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">chunk_size</span><span class="p">)))</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-62'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-62'>#</a>
|
||
</div>
|
||
<p>Concatenate both trainable and fixed chunks </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">257</span> <span class="n">chunk</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">cat</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">chunk</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-63'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-63'>#</a>
|
||
</div>
|
||
<p>Gather the parameters from all the nodes/devices </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">260</span> <span class="n">dist</span><span class="o">.</span><span class="n">all_gather</span><span class="p">(</span><span class="n">buffers</span><span class="p">,</span> <span class="n">chunk</span><span class="p">)</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-64'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-64'>#</a>
|
||
</div>
|
||
<p>Split the gathered parameters into the trainable and fixed chunks </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">263</span> <span class="n">params</span> <span class="o">=</span> <span class="n">buffer</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="nb">sum</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">chunk_size</span><span class="p">))</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">chunk_size</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-65'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-65'>#</a>
|
||
</div>
|
||
<p>Wait for the gather operation to complete and then clear the references to the buffers </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">265</span> <span class="n">buffer</span><span class="o">.</span><span class="n">record_stream</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">fetch_stream</span><span class="p">)</span>
|
||
<span class="lineno">266</span> <span class="k">for</span> <span class="n">b</span> <span class="ow">in</span> <span class="n">buffers</span><span class="p">:</span>
|
||
<span class="lineno">267</span> <span class="n">b</span><span class="o">.</span><span class="n">record_stream</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">fetch_stream</span><span class="p">)</span>
|
||
<span class="lineno">268</span> <span class="n">buffer</span><span class="o">.</span><span class="n">record_stream</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">fetch_stream</span><span class="p">)</span>
|
||
<span class="lineno">269</span> <span class="k">del</span> <span class="n">buffer</span>
|
||
<span class="lineno">270</span> <span class="k">del</span> <span class="n">buffers</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-66'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-66'>#</a>
|
||
</div>
|
||
<p>Reshape the trainable and fixed parameters to continuous tensors </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">273</span> <span class="n">params</span> <span class="o">=</span> <span class="p">[</span><span class="n">p</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span> <span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">params</span><span class="p">]</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-67'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-67'>#</a>
|
||
</div>
|
||
<p>Collect the individual parameter tensors </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">276</span> <span class="k">for</span> <span class="n">cont</span><span class="p">,</span> <span class="n">ps</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">params</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">param_refs</span><span class="p">):</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-68'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-68'>#</a>
|
||
</div>
|
||
<p>If there are no parameters, skip </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">278</span> <span class="k">if</span> <span class="ow">not</span> <span class="n">ps</span><span class="p">:</span>
|
||
<span class="lineno">279</span> <span class="k">continue</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-69'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-69'>#</a>
|
||
</div>
|
||
<p>Offset of the continuous tensor </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">282</span> <span class="n">offset</span> <span class="o">=</span> <span class="mi">0</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-70'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-70'>#</a>
|
||
</div>
|
||
<p>Iterate through model parameters and assign the values from the continuous tensor </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">284</span> <span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">ps</span><span class="p">:</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-71'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-71'>#</a>
|
||
</div>
|
||
<p>Original parameter shape </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">286</span> <span class="n">shape</span> <span class="o">=</span> <span class="n">p</span><span class="o">.</span><span class="n">_orig_shape</span> <span class="c1"># type: ignore[attr-defined]</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-72'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-72'>#</a>
|
||
</div>
|
||
<p>Change the storage size of the parameter. This was set to <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:0.64444em;vertical-align:0em;"></span><span class="mord coloredeq eqh" style=""><span class="mord" style="">0</span></span></span></span></span></span> when we cleaned up the parameters. </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">288</span> <span class="n">p</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">storage</span><span class="p">()</span><span class="o">.</span><span class="n">resize_</span><span class="p">(</span><span class="n">shape</span><span class="o">.</span><span class="n">numel</span><span class="p">())</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-73'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-73'>#</a>
|
||
</div>
|
||
<p>Assign the values from the continuous tensor </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">290</span> <span class="n">p</span><span class="o">.</span><span class="n">data</span><span class="p">[:]</span> <span class="o">=</span> <span class="n">cont</span><span class="p">[</span><span class="n">offset</span><span class="p">:</span> <span class="n">offset</span> <span class="o">+</span> <span class="n">shape</span><span class="o">.</span><span class="n">numel</span><span class="p">()]</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="n">shape</span><span class="p">)</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-74'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-74'>#</a>
|
||
</div>
|
||
<p>Wait for the operations to complete before other operations can be performed </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">292</span> <span class="n">p</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">record_stream</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">fetch_stream</span><span class="p">)</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-75'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-75'>#</a>
|
||
</div>
|
||
<p>Update the offset </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">294</span> <span class="n">offset</span> <span class="o">+=</span> <span class="n">shape</span><span class="o">.</span><span class="n">numel</span><span class="p">()</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-76'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-76'>#</a>
|
||
</div>
|
||
<p>Wait for the operation to complete before other operations can be performed </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">297</span> <span class="n">cont</span><span class="o">.</span><span class="n">record_stream</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">fetch_stream</span><span class="p">)</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-77'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-77'>#</a>
|
||
</div>
|
||
<p> </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">300</span> <span class="k">del</span> <span class="n">params</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-78'>
|
||
<div class='docs doc-strings'>
|
||
<div class='section-link'>
|
||
<a href='#section-78'>#</a>
|
||
</div>
|
||
<h3>Forward pass</h3>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">302</span> <span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-79'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-79'>#</a>
|
||
</div>
|
||
<p>Fetch all the parameters of the current node. This gets called by the previous layer so this call is just to make sure parameters are fetched. </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">309</span> <span class="bp">self</span><span class="o">.</span><span class="n">fetch_params</span><span class="p">()</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-80'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-80'>#</a>
|
||
</div>
|
||
<p>Wait for parameter fetching to complete. </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">312</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">current_stream</span><span class="p">()</span><span class="o">.</span><span class="n">wait_stream</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">fetch_stream</span><span class="p">)</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-81'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-81'>#</a>
|
||
</div>
|
||
<p>Start fetching parameters of the proceeding layers, so that they will fetch them which the current layer does its computations. </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">316</span> <span class="k">for</span> <span class="n">layer</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">next_layer</span><span class="p">:</span>
|
||
<span class="lineno">317</span> <span class="n">layer</span><span class="o">.</span><span class="n">fetch_params</span><span class="p">()</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-82'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-82'>#</a>
|
||
</div>
|
||
<p>Add backward hooks to the parameters of the current layer if autograd is enabled. </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">320</span> <span class="k">if</span> <span class="n">torch</span><span class="o">.</span><span class="n">is_grad_enabled</span><span class="p">():</span>
|
||
<span class="lineno">321</span> <span class="bp">self</span><span class="o">.</span><span class="n">_add_backward_hooks</span><span class="p">()</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-83'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-83'>#</a>
|
||
</div>
|
||
<p>Compute the outputs of the current layer </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">324</span> <span class="n">res</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">module</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-84'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-84'>#</a>
|
||
</div>
|
||
<p>Cleanup the parameters of the layer.</p>
|
||
<p><em>Skip cleaning up if autograd is enabled and this is the last layer in the network, because we will need to fetch the parameters again for the backward pass.</em> </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">330</span> <span class="k">if</span> <span class="ow">not</span> <span class="n">torch</span><span class="o">.</span><span class="n">is_grad_enabled</span><span class="p">()</span> <span class="ow">or</span> <span class="bp">self</span><span class="o">.</span><span class="n">next_layer</span><span class="p">:</span>
|
||
<span class="lineno">331</span> <span class="bp">self</span><span class="o">.</span><span class="n">_cleanup_params</span><span class="p">()</span>
|
||
<span class="lineno">332</span>
|
||
<span class="lineno">333</span> <span class="k">return</span> <span class="n">res</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-85'>
|
||
<div class='docs doc-strings'>
|
||
<div class='section-link'>
|
||
<a href='#section-85'>#</a>
|
||
</div>
|
||
<h4>Add backward hooks to the parameters of the current layer.</h4>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">335</span> <span class="k">def</span> <span class="nf">_add_backward_hooks</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-86'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-86'>#</a>
|
||
</div>
|
||
<p>Number of backward hooks added </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">341</span> <span class="bp">self</span><span class="o">.</span><span class="n">_backward_hook_handles</span> <span class="o">=</span> <span class="mi">0</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-87'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-87'>#</a>
|
||
</div>
|
||
<p>Loop through trainable parameters of the current layer </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">344</span> <span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">param_refs</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">TRAINING_PARAMS_IDX</span><span class="p">]:</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-88'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-88'>#</a>
|
||
</div>
|
||
<p>Make sure a hook hasn't already been added </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">346</span> <span class="k">assert</span> <span class="ow">not</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">p</span><span class="p">,</span> <span class="s2">"_hook_handle"</span><span class="p">),</span> <span class="s1">'Parameter has already been hooked'</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-89'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-89'>#</a>
|
||
</div>
|
||
<p>Use <code class="highlight"><span></span><span class="n">expand_as</span></code>
|
||
to create an autograd step which we can intercept </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">348</span> <span class="n">p_tmp</span> <span class="o">=</span> <span class="n">p</span><span class="o">.</span><span class="n">expand_as</span><span class="p">(</span><span class="n">p</span><span class="p">)</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-90'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-90'>#</a>
|
||
</div>
|
||
<p>Get a handle to add the backward hook. <a href="https://amsword.medium.com/understanding-pytorchs-autograd-with-grad-fn-and-next-functions-b2c4836daa00">This blog discusses about <code class="highlight"><span></span><span class="n">grad_acc</span></code>
|
||
</a>. </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">351</span> <span class="n">grad_acc</span> <span class="o">=</span> <span class="n">p_tmp</span><span class="o">.</span><span class="n">grad_fn</span><span class="o">.</span><span class="n">next_functions</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-91'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-91'>#</a>
|
||
</div>
|
||
<p>Add the backward hook </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">353</span> <span class="n">handle</span> <span class="o">=</span> <span class="n">grad_acc</span><span class="o">.</span><span class="n">register_hook</span><span class="p">(</span>
|
||
<span class="lineno">354</span> <span class="n">functools</span><span class="o">.</span><span class="n">partial</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_post_backward_hook</span><span class="p">,</span> <span class="n">p</span><span class="p">))</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-92'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-92'>#</a>
|
||
</div>
|
||
<p>Keep a reference to the handle </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">356</span> <span class="n">p</span><span class="o">.</span><span class="n">_hook_handle</span> <span class="o">=</span> <span class="n">handle</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-93'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-93'>#</a>
|
||
</div>
|
||
<p>Increment the number of hooks added </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">358</span> <span class="bp">self</span><span class="o">.</span><span class="n">_backward_hook_handles</span> <span class="o">+=</span> <span class="mi">1</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-94'>
|
||
<div class='docs doc-strings'>
|
||
<div class='section-link'>
|
||
<a href='#section-94'>#</a>
|
||
</div>
|
||
<h4>Handle a backward event</h4>
|
||
<p>This gets called by parameter backward hooks and the module backward hook.</p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">360</span> <span class="k">def</span> <span class="nf">_backward_event</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-95'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-95'>#</a>
|
||
</div>
|
||
<p>Decrement the hooks counter </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">368</span> <span class="bp">self</span><span class="o">.</span><span class="n">_backward_hook_handles</span> <span class="o">-=</span> <span class="mi">1</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-96'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-96'>#</a>
|
||
</div>
|
||
<p>If all the hooks (including the module hook) have been called, then we can back up gradients and clean up the parameters. </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">372</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_backward_hook_handles</span> <span class="o">==</span> <span class="o">-</span><span class="mi">1</span><span class="p">:</span>
|
||
<span class="lineno">373</span> <span class="bp">self</span><span class="o">.</span><span class="n">_backup_grads</span><span class="p">()</span>
|
||
<span class="lineno">374</span> <span class="bp">self</span><span class="o">.</span><span class="n">_cleanup_params</span><span class="p">()</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-97'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-97'>#</a>
|
||
</div>
|
||
<p>Start fetch parameters of the previous layer, because autograd will next process the gradients of it. </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">377</span> <span class="k">for</span> <span class="n">layer</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">prev_layer</span><span class="p">:</span>
|
||
<span class="lineno">378</span> <span class="n">layer</span><span class="o">.</span><span class="n">fetch_params</span><span class="p">()</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-98'>
|
||
<div class='docs doc-strings'>
|
||
<div class='section-link'>
|
||
<a href='#section-98'>#</a>
|
||
</div>
|
||
<h4>Parameter backward hook</h4>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">380</span> <span class="k">def</span> <span class="nf">_post_backward_hook</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">p</span><span class="p">:</span> <span class="n">nn</span><span class="o">.</span><span class="n">Parameter</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">):</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-99'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-99'>#</a>
|
||
</div>
|
||
<p>Remove the handle from the parameter </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">385</span> <span class="n">p</span><span class="o">.</span><span class="n">_hook_handle</span><span class="o">.</span><span class="n">remove</span><span class="p">()</span> <span class="c1"># type: ignore[attr-defined]</span>
|
||
<span class="lineno">386</span> <span class="nb">delattr</span><span class="p">(</span><span class="n">p</span><span class="p">,</span> <span class="s2">"_hook_handle"</span><span class="p">)</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-100'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-100'>#</a>
|
||
</div>
|
||
<p>Handle a backward event </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">389</span> <span class="bp">self</span><span class="o">.</span><span class="n">_backward_event</span><span class="p">()</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-101'>
|
||
<div class='docs doc-strings'>
|
||
<div class='section-link'>
|
||
<a href='#section-101'>#</a>
|
||
</div>
|
||
<h4>Module backward hook</h4>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">391</span> <span class="k">def</span> <span class="nf">_backward_hook</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-102'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-102'>#</a>
|
||
</div>
|
||
<p>Handle a backward event </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">396</span> <span class="bp">self</span><span class="o">.</span><span class="n">_backward_event</span><span class="p">()</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-103'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-103'>#</a>
|
||
</div>
|
||
<p>The previous layer will start computing gradients. We need to make sure it has finished fetching params. </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">399</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">current_stream</span><span class="p">()</span><span class="o">.</span><span class="n">wait_stream</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">fetch_stream</span><span class="p">)</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-104'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-104'>#</a>
|
||
</div>
|
||
<p> </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">402</span> <span class="k">return</span> <span class="kc">None</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-105'>
|
||
<div class='docs doc-strings'>
|
||
<div class='section-link'>
|
||
<a href='#section-105'>#</a>
|
||
</div>
|
||
<h3>Backup the gradients of the current layer</h3>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">404</span> <span class="nd">@torch</span><span class="o">.</span><span class="n">no_grad</span><span class="p">()</span>
|
||
<span class="lineno">405</span> <span class="k">def</span> <span class="nf">_backup_grads</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-106'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-106'>#</a>
|
||
</div>
|
||
<p>Skip if there are no trainable parameters </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">410</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">chunk_size</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">TRAINING_PARAMS_IDX</span><span class="p">]</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
|
||
<span class="lineno">411</span> <span class="k">return</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-107'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-107'>#</a>
|
||
</div>
|
||
<p>Use the backup stream to backup the gradients </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">414</span> <span class="k">with</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">stream</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">backup_stream</span><span class="p">):</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-108'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-108'>#</a>
|
||
</div>
|
||
<p>Buffer to store the gradients </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">416</span> <span class="n">buffer</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_empty</span><span class="p">((</span><span class="bp">self</span><span class="o">.</span><span class="n">world_size</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">chunk_size</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">TRAINING_PARAMS_IDX</span><span class="p">],))</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-109'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-109'>#</a>
|
||
</div>
|
||
<p>Split the continuous buffer into number of nodes. These splits are views of `buffer'. </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">418</span> <span class="n">buffers</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">buffer</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">chunk_size</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">TRAINING_PARAMS_IDX</span><span class="p">]))</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-110'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-110'>#</a>
|
||
</div>
|
||
<p>Offset of the continuous buffer </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">421</span> <span class="n">offset</span> <span class="o">=</span> <span class="mi">0</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-111'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-111'>#</a>
|
||
</div>
|
||
<p>Iterate through trainable parameters </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">423</span> <span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">param_refs</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">TRAINING_PARAMS_IDX</span><span class="p">]:</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-112'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-112'>#</a>
|
||
</div>
|
||
<p>Collect gradients </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">425</span> <span class="n">shape</span> <span class="o">=</span> <span class="n">p</span><span class="o">.</span><span class="n">_orig_shape</span> <span class="c1"># type: ignore[attr-defined]</span>
|
||
<span class="lineno">426</span> <span class="n">buffer</span><span class="p">[</span><span class="n">offset</span><span class="p">:</span> <span class="n">offset</span> <span class="o">+</span> <span class="n">shape</span><span class="o">.</span><span class="n">numel</span><span class="p">()]</span> <span class="o">=</span> <span class="n">p</span><span class="o">.</span><span class="n">grad</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-113'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-113'>#</a>
|
||
</div>
|
||
<p>Update the offset </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">428</span> <span class="n">offset</span> <span class="o">+=</span> <span class="n">shape</span><span class="o">.</span><span class="n">numel</span><span class="p">()</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-114'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-114'>#</a>
|
||
</div>
|
||
<p>Clean the gradients </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">430</span> <span class="n">p</span><span class="o">.</span><span class="n">grad</span> <span class="o">=</span> <span class="kc">None</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-115'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-115'>#</a>
|
||
</div>
|
||
<p>Empty tensor to accumulate the gradients of the current shard </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">433</span> <span class="n">grad</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_empty</span><span class="p">((</span><span class="bp">self</span><span class="o">.</span><span class="n">chunk_size</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">TRAINING_PARAMS_IDX</span><span class="p">],))</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-116'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-116'>#</a>
|
||
</div>
|
||
<p>Accumulate the gradients of each shard. It scatters the buffers across the nodes, and each node accumulates (reduces) the tensors it receives. </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">436</span> <span class="n">dist</span><span class="o">.</span><span class="n">reduce_scatter</span><span class="p">(</span><span class="n">grad</span><span class="p">,</span> <span class="n">buffers</span><span class="p">)</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-117'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-117'>#</a>
|
||
</div>
|
||
<p>Wait for the operation to complete and then clear the references to the buffers </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">439</span> <span class="k">for</span> <span class="n">b</span> <span class="ow">in</span> <span class="n">buffers</span><span class="p">:</span>
|
||
<span class="lineno">440</span> <span class="n">b</span><span class="o">.</span><span class="n">record_stream</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">fetch_stream</span><span class="p">)</span>
|
||
<span class="lineno">441</span> <span class="n">buffer</span><span class="o">.</span><span class="n">record_stream</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">fetch_stream</span><span class="p">)</span>
|
||
<span class="lineno">442</span> <span class="k">del</span> <span class="n">buffer</span>
|
||
<span class="lineno">443</span> <span class="k">del</span> <span class="n">buffers</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-118'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-118'>#</a>
|
||
</div>
|
||
<p>Set the chunk gradients. This is what the optimizer sees. </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">446</span> <span class="bp">self</span><span class="o">.</span><span class="n">chunk</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">TRAINING_PARAMS_IDX</span><span class="p">]</span><span class="o">.</span><span class="n">grad</span> <span class="o">=</span> <span class="n">grad</span>
|
||
<span class="lineno">447</span> <span class="k">del</span> <span class="n">grad</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-119'>
|
||
<div class='docs doc-strings'>
|
||
<div class='section-link'>
|
||
<a href='#section-119'>#</a>
|
||
</div>
|
||
<h2>Sequential module for <code class="highlight"><span></span><span class="n">Zero3Layer</span></code>
|
||
layers</h2>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">450</span><span class="k">class</span> <span class="nc">Zero3Sequential</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-120'>
|
||
<div class='docs doc-strings'>
|
||
<div class='section-link'>
|
||
<a href='#section-120'>#</a>
|
||
</div>
|
||
<ul><li><code class="highlight"><span></span><span class="n">modules</span></code>
|
||
List of <code class="highlight"><span></span><span class="n">Zero3Layer</span></code>
|
||
layers</li></ul>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">454</span> <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">modules</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="n">Zero3Layer</span><span class="p">]):</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-121'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-121'>#</a>
|
||
</div>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">458</span> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-122'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-122'>#</a>
|
||
</div>
|
||
<p>CUDA stream to fetch parameters </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">461</span> <span class="bp">self</span><span class="o">.</span><span class="n">fetch_stream</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">Stream</span><span class="p">()</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-123'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-123'>#</a>
|
||
</div>
|
||
<p>CUDA stream to back up (accumulate) gradients </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">463</span> <span class="bp">self</span><span class="o">.</span><span class="n">backup_stream</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">Stream</span><span class="p">()</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-124'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-124'>#</a>
|
||
</div>
|
||
<p>Set the streams and preceding and proceeding layers for each <code class="highlight"><span></span><span class="n">Zero3Layer</span></code>
|
||
layer </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">466</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">modules</span><span class="p">)):</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-125'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-125'>#</a>
|
||
</div>
|
||
<p>Set layer index </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">468</span> <span class="n">modules</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">layer_idx</span> <span class="o">=</span> <span class="n">i</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-126'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-126'>#</a>
|
||
</div>
|
||
<p>Set streams </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">470</span> <span class="n">modules</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">fetch_stream</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">fetch_stream</span>
|
||
<span class="lineno">471</span> <span class="n">modules</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">backup_stream</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">backup_stream</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-127'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-127'>#</a>
|
||
</div>
|
||
<p>Set proceeding layers </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">473</span> <span class="k">if</span> <span class="n">i</span> <span class="o">+</span> <span class="mi">1</span> <span class="o"><</span> <span class="nb">len</span><span class="p">(</span><span class="n">modules</span><span class="p">):</span>
|
||
<span class="lineno">474</span> <span class="n">modules</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">next_layer</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">modules</span><span class="p">[</span><span class="n">i</span> <span class="o">+</span> <span class="mi">1</span><span class="p">])</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-128'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-128'>#</a>
|
||
</div>
|
||
<p>Set preceding layers </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">476</span> <span class="k">if</span> <span class="n">i</span> <span class="o">-</span> <span class="mi">1</span> <span class="o">>=</span> <span class="mi">0</span><span class="p">:</span>
|
||
<span class="lineno">477</span> <span class="n">modules</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">prev_layer</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">modules</span><span class="p">[</span><span class="n">i</span> <span class="o">-</span> <span class="mi">1</span><span class="p">])</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-129'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-129'>#</a>
|
||
</div>
|
||
<p>Store list of modules </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">480</span> <span class="bp">self</span><span class="o">.</span><span class="n">module_list</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">ModuleList</span><span class="p">(</span><span class="n">modules</span><span class="p">)</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-130'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-130'>#</a>
|
||
</div>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">482</span> <span class="k">def</span> <span class="nf">get_trainable_chunk</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-131'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-131'>#</a>
|
||
</div>
|
||
<p>Return the list of trainable chunks from each layer </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">484</span> <span class="k">return</span> <span class="nb">sum</span><span class="p">([</span><span class="n">m</span><span class="o">.</span><span class="n">get_trainable_chunk</span><span class="p">()</span> <span class="k">for</span> <span class="n">m</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">module_list</span><span class="p">],</span> <span class="p">[])</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-132'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-132'>#</a>
|
||
</div>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">486</span> <span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">):</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-133'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-133'>#</a>
|
||
</div>
|
||
<p>Make sure gradient back up is complete </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">488</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">current_stream</span><span class="p">()</span><span class="o">.</span><span class="n">wait_stream</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">backup_stream</span><span class="p">)</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-134'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-134'>#</a>
|
||
</div>
|
||
<p>Forward pass </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">491</span> <span class="k">for</span> <span class="n">m</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">module_list</span><span class="p">:</span>
|
||
<span class="lineno">492</span> <span class="n">x</span> <span class="o">=</span> <span class="n">m</span><span class="p">(</span><span class="n">x</span><span class="p">)</span></pre></div>
|
||
</div>
|
||
</div>
|
||
<div class='section' id='section-135'>
|
||
<div class='docs'>
|
||
<div class='section-link'>
|
||
<a href='#section-135'>#</a>
|
||
</div>
|
||
<p> </p>
|
||
|
||
</div>
|
||
<div class='code'>
|
||
<div class="highlight"><pre><span class="lineno">495</span> <span class="k">return</span> <span class="n">x</span></pre></div>
|
||
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|
||
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|
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