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Model optimization subsite docs.
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‎tensorflow_model_optimization/g3doc/_book.yaml‎

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upper_tabs:
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# Tabs left of dropdown menu
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- include: /_upper_tabs_left.yaml
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- include: /api_docs/_upper_tabs_api.yaml
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# Dropdown menu
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- name: Resources
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path: /resources
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is_default: true
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menu:
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- include: /resources/_menu_toc.yaml
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lower_tabs:
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# Subsite tabs
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other:
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- name: Guide
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contents:
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- title: Model optimization guide
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path: /model_optimization/guide
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- title: Get started
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path: /model_optimization/guide/get_started
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- title: Optimize further
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path: /model_optimization/guide/optimize_further
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- heading: Weight pruning
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- title: Overview
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path: /model_optimization/guide/pruning
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- title: Pruning with Keras
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path: /model_optimization/guide/pruning/pruning_with_keras
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- title: Train sparse models
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path: /model_optimization/guide/pruning/train_sparse_models
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- heading: Quantization
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- title: Overview
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path: /model_optimization/guide/quantization
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- title: Post-training quantization
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path: https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/tutorials/post_training_quant.ipynb
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status: external
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- name: API
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skip_translation: true
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contents:
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- include: /model_optimization/api_docs/python/_toc.yaml
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- include: /_upper_tabs_right.yaml

‎tensorflow_model_optimization/g3doc/_index.yaml‎

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book_path: /model_optimization/_book.yaml
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project_path: /model_optimization/_project.yaml
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description: <!--no description-->
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landing_page:
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custom_css_path: /site-assets/css/style.css
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rows:
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- heading: >
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Optimize machine learning models
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items:
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- classname: devsite-landing-row-50
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description: >
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The <em>TensorFlow Model Optimization Toolkit</em> is a suite of tools
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for optimizing ML models for deployment and execution. Among many uses,
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the toolkit supports techniques used to:
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<ul style="padding-left: 20px">
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<li>Reduce latency and inference cost for cloud and edge devices (e.g. mobile, IoT).</li>
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<li>
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Deploy models to edge devices with restrictions on processing,
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memory, power-consumption, network usage, and model storage space.
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</li>
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<li>
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Enable execution on and optimize for existing hardware or new special purpose accelerators.
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</li>
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</ul>
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<p style="margin-top: 30px">
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Choose the model and optimization tool depending on your task:
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</p>
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list:
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- heading: Improve performance with off-the-shelf models
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description: >
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In many cases, pre-optimized models can improve the efficiency of your application.
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path: /model_optimization/guide/get_started
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icon:
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icon_name: chevron_right
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foreground: theme
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background: grey
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- heading: Use the TensorFlow Model Optimization Toolkit
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description: >
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Try the post-training tools to optimize an already-trained TensorFlow model.
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path: /model_optimization/guide/get_started
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icon:
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icon_name: chevron_right
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foreground: theme
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background: grey
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- heading: Optimize further
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description: >
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Use training-time optimization tools and learn about the techniques.
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path: /model_optimization/guide/optimize_further
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icon:
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icon_name: chevron_right
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foreground: theme
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background: grey
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code_block: |
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<pre class = "prettyprint">
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import tensorflow as tf
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import tensorflow_model_optimization as tfmot
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model = tf.keras.Sequential([...])
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pruning_schedule = tfmot.sparsity.keras.PolynomialDecay(
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initial_sparsity=0.0, final_sparsity=0.5,
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begin_step=2000, end_step=4000)
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model_for_pruning = tfmot.sparsity.keras.prune_low_magnitude(
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model, pruning_schedule=pruning_schedule)
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...
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model_for_pruning.fit(...)
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</pre>
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- classname: devsite-landing-row-cards
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items:
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- heading: "Introducing the Model Optimization Toolkit for TensorFlow"
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path: https://medium.com/tensorflow/introducing-the-model-optimization-toolkit-for-tensorflow-254aca1ba0a3
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buttons:
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- label: "Read on TensorFlow blog"
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path: https://medium.com/tensorflow/introducing-the-model-optimization-toolkit-for-tensorflow-254aca1ba0a3
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- heading: "Model Optimization Toolkit on GitHub"
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path: https://github.com/tensorflow/model_optimization
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buttons:
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- label: "View on GitHub"
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path: https://github.com/tensorflow/model_optimization
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- classname: devsite-landing-row-item-hidden

‎tensorflow_model_optimization/g3doc/_project.yaml‎

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name: TensorFlow model optimization
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breadcrumb_name: Model optimization
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home_url: /model_optimization/
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parent_project_metadata_path: /_project.yaml
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description: >
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"Optimize machine learning models for deployment and execution."
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use_site_branding: true
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hide_from_products_list: true
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content_license: cc3-apache2
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buganizer_id: 316308
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include: /_project_included.yaml

‎tensorflow_model_optimization/g3doc/api_docs/python/_toc.yaml‎

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# Automatically generated file; please do not edit
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toc:
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- title: tfmot
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section:
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- title: Overview
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path: /model_optimization/api_docs/python/tfmot
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- title: tfmot.sparsity
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section:
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- title: Overview
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path: /model_optimization/api_docs/python/tfmot/sparsity
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- title: keras
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section:
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- title: Overview
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path: /model_optimization/api_docs/python/tfmot/sparsity/keras
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- title: ConstantSparsity
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path: /model_optimization/api_docs/python/tfmot/sparsity/keras/ConstantSparsity
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- title: PolynomialDecay
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path: /model_optimization/api_docs/python/tfmot/sparsity/keras/PolynomialDecay
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- title: PrunableLayer
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path: /model_optimization/api_docs/python/tfmot/sparsity/keras/PrunableLayer
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- title: prune_low_magnitude
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path: /model_optimization/api_docs/python/tfmot/sparsity/keras/prune_low_magnitude
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- title: prune_scope
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path: /model_optimization/api_docs/python/tfmot/sparsity/keras/prune_scope
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- title: PruningSchedule
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path: /model_optimization/api_docs/python/tfmot/sparsity/keras/PruningSchedule
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- title: PruningSummaries
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path: /model_optimization/api_docs/python/tfmot/sparsity/keras/PruningSummaries
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- title: strip_pruning
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path: /model_optimization/api_docs/python/tfmot/sparsity/keras/strip_pruning
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- title: UpdatePruningStep
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path: /model_optimization/api_docs/python/tfmot/sparsity/keras/UpdatePruningStep

‎tensorflow_model_optimization/g3doc/api_docs/python/index.md‎

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# All symbols in TensorFlow Model Optimization
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* <a href="./tfmot.md"><code>tfmot</code></a>
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* <a href="./tfmot/sparsity.md"><code>tfmot.sparsity</code></a>
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* <a href="./tfmot/sparsity/keras.md"><code>tfmot.sparsity.keras</code></a>
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* <a href="./tfmot/sparsity/keras/ConstantSparsity.md"><code>tfmot.sparsity.keras.ConstantSparsity</code></a>
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* <a href="./tfmot/sparsity/keras/PolynomialDecay.md"><code>tfmot.sparsity.keras.PolynomialDecay</code></a>
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* <a href="./tfmot/sparsity/keras/PrunableLayer.md"><code>tfmot.sparsity.keras.PrunableLayer</code></a>
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* <a href="./tfmot/sparsity/keras/PruningSchedule.md"><code>tfmot.sparsity.keras.PruningSchedule</code></a>
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* <a href="./tfmot/sparsity/keras/PruningSummaries.md"><code>tfmot.sparsity.keras.PruningSummaries</code></a>
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* <a href="./tfmot/sparsity/keras/UpdatePruningStep.md"><code>tfmot.sparsity.keras.UpdatePruningStep</code></a>
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* <a href="./tfmot/sparsity/keras/prune_low_magnitude.md"><code>tfmot.sparsity.keras.prune_low_magnitude</code></a>
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* <a href="./tfmot/sparsity/keras/prune_scope.md"><code>tfmot.sparsity.keras.prune_scope</code></a>
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* <a href="./tfmot/sparsity/keras/strip_pruning.md"><code>tfmot.sparsity.keras.strip_pruning</code></a>

‎tensorflow_model_optimization/g3doc/api_docs/python/tfmot.md‎

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<div itemscope itemtype="http://developers.google.com/ReferenceObject">
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<meta itemprop="name" content="tfmot" />
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<meta itemprop="path" content="Stable" />
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</div>
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# Module: tfmot
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Init module for TensorFlow Model Optimization Python API.
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Defined in
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[`__init__.py`](https://github.com/tensorflow/model-optimization/tree/master/tensorflow_model_optimization/__init__.py).
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<!-- Placeholder for "Used in" -->
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```
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import tensorflow_model_optimization as tfmot
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```
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## Modules
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[`sparsity`](./tfmot/sparsity.md) module: Module containing code for sparsity.

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