All nits
Browse files- Accelerate.ipynb +11 -12
- CLI.gif +0 -0
- index.html +6 -3
Accelerate.ipynb
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@@ -15,15 +15,6 @@
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"---"
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{
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"attachments": {},
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"cell_type": "markdown",
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"id": "f2333422",
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"metadata": {},
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"source": [
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"## Test Gradio {background-iframe=\"https://muellerzr-accelerate-presentation.hf.space\"}"
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"cell_type": "markdown",
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"id": "45e61402-f734-4500-8eb6-fcdd6f17a0d4",
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@@ -366,7 +357,7 @@
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"accelerator = Accelerator(gradient_accumulation_steps=4)\n",
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"...\n",
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"for batch in dataloader:\n",
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" with accelerator.accumulate(model)
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" optimizer.zero_grad()\n",
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" inputs, targets = batch\n",
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" outputs = model(inputs)\n",
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@@ -522,7 +513,7 @@
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" my_model = ModelClass(...)\n",
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"\n",
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"my_model = load_checkpoint_and_dispatch(\n",
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"
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")\n",
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"```\n",
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"`device_map=\"auto\"` will tell π€ Accelerate that it should determine where to put each layer of the model:\n",
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" my_model = ModelClass(...)\n",
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"\n",
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"my_model = load_checkpoint_and_dispatch(\n",
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"
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")\n",
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"my_model.eval()\n",
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"\n",
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"```"
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{
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"cell_type": "markdown",
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"id": "6f5122b2-f4fe-4237-aff2-d2a69f85b692",
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"---"
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]
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},
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{
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"cell_type": "markdown",
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"id": "45e61402-f734-4500-8eb6-fcdd6f17a0d4",
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"accelerator = Accelerator(gradient_accumulation_steps=4)\n",
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"...\n",
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"for batch in dataloader:\n",
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" with accelerator.accumulate(model):\n",
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" optimizer.zero_grad()\n",
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" inputs, targets = batch\n",
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" outputs = model(inputs)\n",
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" my_model = ModelClass(...)\n",
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"\n",
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"my_model = load_checkpoint_and_dispatch(\n",
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" my_model, \"sharded-weights\", device_map=\"auto\"\n",
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")\n",
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"```\n",
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"`device_map=\"auto\"` will tell π€ Accelerate that it should determine where to put each layer of the model:\n",
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" my_model = ModelClass(...)\n",
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"\n",
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"my_model = load_checkpoint_and_dispatch(\n",
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" my_model, \"sharded-weights\", device_map=\"auto\"\n",
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")\n",
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"my_model.eval()\n",
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"\n",
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"```"
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]
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},
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{
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"cell_type": "markdown",
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"id": "23911045-44a7-4e1d-aebc-db46be856234",
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"metadata": {},
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"source": [
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"## Demo!"
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]
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},
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"cell_type": "markdown",
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"id": "6f5122b2-f4fe-4237-aff2-d2a69f85b692",
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CLI.gif
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index.html
CHANGED
@@ -581,7 +581,7 @@ Zachary Mueller
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<span id="cb13-2"><a href="#cb13-2"></a>accelerator <span class="op">=</span> Accelerator(gradient_accumulation_steps<span class="op">=</span><span class="dv">4</span>)</span>
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<span id="cb13-3"><a href="#cb13-3"></a>...</span>
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<span id="cb13-4"><a href="#cb13-4"></a><span class="cf">for</span> batch <span class="kw">in</span> dataloader:</span>
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<span id="cb13-5"><a href="#cb13-5"></a> <span class="cf">with</span> accelerator.accumulate(model)
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<span id="cb13-6"><a href="#cb13-6"></a> optimizer.zero_grad()</span>
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<span id="cb13-7"><a href="#cb13-7"></a> inputs, targets <span class="op">=</span> batch</span>
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<span id="cb13-8"><a href="#cb13-8"></a> outputs <span class="op">=</span> model(inputs)</span>
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@@ -682,7 +682,7 @@ Zachary Mueller
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<span id="cb17-4"><a href="#cb17-4"></a> my_model <span class="op">=</span> ModelClass(...)</span>
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<span id="cb17-5"><a href="#cb17-5"></a></span>
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<span id="cb17-6"><a href="#cb17-6"></a>my_model <span class="op">=</span> load_checkpoint_and_dispatch(</span>
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<span id="cb17-7"><a href="#cb17-7"></a>
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<span id="cb17-8"><a href="#cb17-8"></a>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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<p><code>device_map="auto"</code> will tell π€ Accelerate that it should determine where to put each layer of the model:</p>
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<ol type="1">
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@@ -699,12 +699,15 @@ Zachary Mueller
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<span id="cb18-4"><a href="#cb18-4"></a> my_model <span class="op">=</span> ModelClass(...)</span>
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<span id="cb18-5"><a href="#cb18-5"></a></span>
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<span id="cb18-6"><a href="#cb18-6"></a>my_model <span class="op">=</span> load_checkpoint_and_dispatch(</span>
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<span id="cb18-7"><a href="#cb18-7"></a>
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<span id="cb18-8"><a href="#cb18-8"></a>)</span>
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<span id="cb18-9"><a href="#cb18-9"></a>my_model.<span class="bu">eval</span>()</span>
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<span id="cb18-10"><a href="#cb18-10"></a></span>
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<span id="cb18-11"><a href="#cb18-11"></a><span class="cf">for</span> batch <span class="kw">in</span> dataloader:</span>
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<span id="cb18-12"><a href="#cb18-12"></a> output <span class="op">=</span> my_model(batch)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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</section></section>
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<section>
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<section id="thanks-for-listening" class="title-slide slide level1 center">
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<span id="cb13-2"><a href="#cb13-2"></a>accelerator <span class="op">=</span> Accelerator(gradient_accumulation_steps<span class="op">=</span><span class="dv">4</span>)</span>
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<span id="cb13-3"><a href="#cb13-3"></a>...</span>
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<span id="cb13-4"><a href="#cb13-4"></a><span class="cf">for</span> batch <span class="kw">in</span> dataloader:</span>
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<span id="cb13-5"><a href="#cb13-5"></a> <span class="cf">with</span> accelerator.accumulate(model):</span>
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<span id="cb13-6"><a href="#cb13-6"></a> optimizer.zero_grad()</span>
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<span id="cb13-7"><a href="#cb13-7"></a> inputs, targets <span class="op">=</span> batch</span>
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<span id="cb13-8"><a href="#cb13-8"></a> outputs <span class="op">=</span> model(inputs)</span>
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<span id="cb17-4"><a href="#cb17-4"></a> my_model <span class="op">=</span> ModelClass(...)</span>
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<span id="cb17-5"><a href="#cb17-5"></a></span>
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<span id="cb17-6"><a href="#cb17-6"></a>my_model <span class="op">=</span> load_checkpoint_and_dispatch(</span>
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<span id="cb17-7"><a href="#cb17-7"></a> my_model, <span class="st">"sharded-weights"</span>, device_map<span class="op">=</span><span class="st">"auto"</span></span>
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<span id="cb17-8"><a href="#cb17-8"></a>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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<p><code>device_map="auto"</code> will tell π€ Accelerate that it should determine where to put each layer of the model:</p>
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<ol type="1">
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<span id="cb18-4"><a href="#cb18-4"></a> my_model <span class="op">=</span> ModelClass(...)</span>
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<span id="cb18-5"><a href="#cb18-5"></a></span>
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<span id="cb18-6"><a href="#cb18-6"></a>my_model <span class="op">=</span> load_checkpoint_and_dispatch(</span>
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<span id="cb18-7"><a href="#cb18-7"></a> my_model, <span class="st">"sharded-weights"</span>, device_map<span class="op">=</span><span class="st">"auto"</span></span>
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<span id="cb18-8"><a href="#cb18-8"></a>)</span>
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<span id="cb18-9"><a href="#cb18-9"></a>my_model.<span class="bu">eval</span>()</span>
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<span id="cb18-10"><a href="#cb18-10"></a></span>
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<span id="cb18-11"><a href="#cb18-11"></a><span class="cf">for</span> batch <span class="kw">in</span> dataloader:</span>
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<span id="cb18-12"><a href="#cb18-12"></a> output <span class="op">=</span> my_model(batch)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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</section>
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<section id="demo" class="slide level2">
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<h2>Demo!</h2>
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</section></section>
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<section>
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<section id="thanks-for-listening" class="title-slide slide level1 center">
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