optimum/v1.7.0/en/habana/quickstart.html

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<h1 class="relative group"><a id="quickstart" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#quickstart"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a>
	<span>Quickstart
	</span></h1>

<p>🤗 Optimum Habana was designed with one goal in mind: <strong>making training and evaluation straightforward for any 🤗 Transformers user while leveraging the complete power of Gaudi processors</strong>.
There are two main classes one needs to know:</p>
<ul><li><a href="https://huggingface.co/docs/optimum/habana/package_reference/trainer" rel="nofollow"><code>GaudiTrainer</code></a>: the trainer class that takes care of compiling (lazy or eager mode) and distributing the model to run on HPUs, and of performing training and evaluation.</li>
<li><a href="https://huggingface.co/docs/optimum/habana/package_reference/gaudi_config" rel="nofollow"><code>GaudiConfig</code></a>: the class that enables to configure Habana Mixed Precision and to decide whether optimized operators and optimizers should be used or not.</li></ul>
<p>The <a href="https://huggingface.co/docs/optimum/habana/package_reference/trainer" rel="nofollow"><code>GaudiTrainer</code></a> is very similar to the <a href="https://huggingface.co/docs/transformers/main_classes/trainer" rel="nofollow">🤗 Transformers Trainer</a>, and adapting a script using the Trainer to make it work with Gaudi will mostly consist in simply swapping the <code>Trainer</code> class for the <code>GaudiTrainer</code> one.
That is how most of the <a href="https://github.com/huggingface/optimum-habana/tree/main/examples" rel="nofollow">example scripts</a> were adapted from their <a href="https://github.com/huggingface/transformers/tree/main/examples/pytorch" rel="nofollow">original counterparts</a>.</p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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	Copied</div></button></div>
	<pre><!-- HTML_TAG_START --><span class="hljs-deletion">-from transformers import Trainer, TrainingArguments</span>
<span class="hljs-addition">+from optimum.habana import GaudiTrainer, GaudiTrainingArguments</span>

# define the training arguments
<span class="hljs-deletion">-training_args = TrainingArguments(</span>
<span class="hljs-addition">+training_args = GaudiTrainingArguments(</span>
<span class="hljs-addition">+  use_habana=True,</span>
<span class="hljs-addition">+  use_lazy_mode=True,</span>
<span class="hljs-addition">+  use_hpu_graphs=True,</span>
<span class="hljs-addition">+  gaudi_config_name=gaudi_config_name,</span>
  ...
)

# Initialize our Trainer
<span class="hljs-deletion">-trainer = Trainer(</span>
<span class="hljs-addition">+trainer = GaudiTrainer(</span>
    model=model,
    args=training_args,
    train_dataset=train_dataset
    ... # other arguments
)<!-- HTML_TAG_END --></pre></div>
<p>where <code>gaudi_config_name</code> is the name of a model from the <a href="https://huggingface.co/Habana" rel="nofollow">Hub</a> (Gaudi configurations are stored in model repositories). You can also give the path to a custom Gaudi configuration written in a JSON file such as this one:</p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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	Copied</div></button></div>
	<pre><!-- HTML_TAG_START --><span class="hljs-punctuation">{</span>
  <span class="hljs-attr">&quot;use_habana_mixed_precision&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-keyword">true</span><span class="hljs-punctuation">,</span>
  <span class="hljs-attr">&quot;hmp_is_verbose&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-keyword">false</span><span class="hljs-punctuation">,</span>
  <span class="hljs-attr">&quot;use_fused_adam&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-keyword">true</span><span class="hljs-punctuation">,</span>
  <span class="hljs-attr">&quot;use_fused_clip_norm&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-keyword">true</span><span class="hljs-punctuation">,</span>
  <span class="hljs-attr">&quot;hmp_bf16_ops&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">[</span>
    <span class="hljs-string">&quot;add&quot;</span><span class="hljs-punctuation">,</span>
    <span class="hljs-string">&quot;addmm&quot;</span><span class="hljs-punctuation">,</span>
    <span class="hljs-string">&quot;bmm&quot;</span><span class="hljs-punctuation">,</span>
    <span class="hljs-string">&quot;div&quot;</span><span class="hljs-punctuation">,</span>
    <span class="hljs-string">&quot;dropout&quot;</span><span class="hljs-punctuation">,</span>
    <span class="hljs-string">&quot;gelu&quot;</span><span class="hljs-punctuation">,</span>
    <span class="hljs-string">&quot;iadd&quot;</span><span class="hljs-punctuation">,</span>
    <span class="hljs-string">&quot;linear&quot;</span><span class="hljs-punctuation">,</span>
    <span class="hljs-string">&quot;layer_norm&quot;</span><span class="hljs-punctuation">,</span>
    <span class="hljs-string">&quot;matmul&quot;</span><span class="hljs-punctuation">,</span>
    <span class="hljs-string">&quot;mm&quot;</span><span class="hljs-punctuation">,</span>
    <span class="hljs-string">&quot;rsub&quot;</span><span class="hljs-punctuation">,</span>
    <span class="hljs-string">&quot;softmax&quot;</span><span class="hljs-punctuation">,</span>
    <span class="hljs-string">&quot;truediv&quot;</span>
  <span class="hljs-punctuation">]</span><span class="hljs-punctuation">,</span>
  <span class="hljs-attr">&quot;hmp_fp32_ops&quot;</span><span class="hljs-punctuation">:</span> <span class="hljs-punctuation">[</span>
    <span class="hljs-string">&quot;embedding&quot;</span><span class="hljs-punctuation">,</span>
    <span class="hljs-string">&quot;nll_loss&quot;</span><span class="hljs-punctuation">,</span>
    <span class="hljs-string">&quot;log_softmax&quot;</span>
  <span class="hljs-punctuation">]</span>
<span class="hljs-punctuation">}</span><!-- HTML_TAG_END --></pre></div>
<p>If you prefer to instantiate a Gaudi configuration to work on it before giving it to the trainer, you can do it as follows:</p>

	<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5   text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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	Copied</div></button></div>
	<pre><!-- HTML_TAG_START -->gaudi_config = GaudiConfig.from_pretrained(
    gaudi_config_name,
    cache_dir=model_args.cache_dir,
    revision=model_args.model_revision,
    use_auth_token=<span class="hljs-literal">True</span> <span class="hljs-keyword">if</span> model_args.use_auth_token <span class="hljs-keyword">else</span> <span class="hljs-literal">None</span>,
)<!-- HTML_TAG_END --></pre></div>
<h2 class="relative group"><a id="stable-diffusion" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#stable-diffusion"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a>
	<span>Stable Diffusion
	</span></h2>

<p>🤗 Optimum Habana also features HPU-optimized support for the 🤗 Diffusers library.
Thus, you can easily deploy Stable Diffusion on Gaudi for performing text-to-image generation.</p>
<p>Here is how to use it and the differences with the 🤗 Diffusers library:</p>

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	Copied</div></button></div>
	<pre><!-- HTML_TAG_START --><span class="hljs-deletion">- from diffusers import DDIMScheduler, StableDiffusionPipeline</span>
<span class="hljs-addition">+ from optimum.habana.diffusers import GaudiDDIMScheduler, GaudiStableDiffusionPipeline</span>


model_name = &quot;CompVis/stable-diffusion-v1-4&quot;

<span class="hljs-deletion">- scheduler = DDIMScheduler.from_pretrained(model_name, subfolder=&quot;scheduler&quot;)</span>
<span class="hljs-addition">+ scheduler = GaudiDDIMScheduler.from_pretrained(model_name, subfolder=&quot;scheduler&quot;)</span>

<span class="hljs-deletion">- pipeline = StableDiffusionPipeline.from_pretrained(</span>
<span class="hljs-addition">+ pipeline = GaudiStableDiffusionPipeline.from_pretrained(</span>
    model_name,
    scheduler=scheduler,
<span class="hljs-addition">+   use_habana=True,</span>
<span class="hljs-addition">+   use_hpu_graphs=True,</span>
<span class="hljs-addition">+   gaudi_config=&quot;Habana/stable-diffusion&quot;,</span>
)

outputs = generator(
    [&quot;An image of a squirrel in Picasso style&quot;],
    num_images_per_prompt=16,
<span class="hljs-addition">+   batch_size=4,</span>
)<!-- HTML_TAG_END --></pre></div>


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