tensorflow/lite/g3doc/api_docs/python/tflite_model_maker/searcher/Searcher.md
page_type: reference description: Creates the similarity search model with ScaNN.
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Creates the similarity search model with ScaNN.
<pre class="devsite-click-to-copy prettyprint lang-py tfo-signature-link"> <code>tflite_model_maker.searcher.Searcher( serialized_scann_path: str, metadata: List[AnyStr], embedder_path: Optional[str] = None ) -> None </code></pre> <h3>Used in the notebooks</h3> <table class="vertical-rules"> <thead> <tr> <th>Used in the tutorials</th> </tr> </thead> <tbody> <tr> <td> <ul> <li><a href="https://www.tensorflow.org/lite/models/modify/model_maker/text_searcher">Text Searcher with TensorFlow Lite Model Maker</a></li> </ul> </td> </tr> </tbody> </table> <!-- Tabular view --> <table class="responsive fixed orange"> <colgroup><col width="214px"><col></colgroup> <tr><th colspan="2"><h2 class="add-link">Args</h2></th></tr> <tr> <td> `serialized_scann_path`<a id="serialized_scann_path"></a> </td> <td> Path to the dir that contains the ScaNN's artifacts. </td> </tr><tr> <td> `metadata`<a id="metadata"></a> </td> <td> The metadata for each of the embeddings in the database. Passed in the same order as the embeddings in ScaNN. </td> </tr><tr> <td> `embedder_path`<a id="embedder_path"></a> </td> <td> Path to the TFLite Embedder model file. </td> </tr> </table><a target="_blank" class="external" href="https://github.com/tensorflow/examples/blob/master/tensorflow_examples/lite/model_maker/core/task/searcher.py#L200-L245">View source</a>
<pre class="devsite-click-to-copy prettyprint lang-py tfo-signature-link"> <code>@classmethod</code> <code>create_from_data( data: <a href="../../tflite_model_maker/searcher/DataLoader"><code>tflite_model_maker.searcher.DataLoader</code></a>, scann_options: <a href="../../tflite_model_maker/searcher/ScaNNOptions"><code>tflite_model_maker.searcher.ScaNNOptions</code></a>, cache_dir: Optional[str] = None ) -> 'Searcher' </code></pre>"Creates the instance from data.
<!-- Tabular view --> <table class="responsive fixed orange"> <colgroup><col width="214px"><col></colgroup> <tr><th colspan="2">Args</th></tr> <tr> <td> `data` </td> <td> Data used to create scann. </td> </tr><tr> <td> `scann_options` </td> <td> Options to build the ScaNN index file. </td> </tr><tr> <td> `cache_dir` </td> <td> The cache directory to save serialized ScaNN and/or the tflite model. When cache_dir is not set, a temporary folder will be created and will **not** be removed automatically which makes it can be used later. </td> </tr> </table> <!-- Tabular view --> <table class="responsive fixed orange"> <colgroup><col width="214px"><col></colgroup> <tr><th colspan="2">Returns</th></tr> <tr class="alt"> <td colspan="2"> A Searcher instance. </td> </tr> </table> <h3 id="create_from_server_scann"><code>create_from_server_scann</code></h3><a target="_blank" class="external" href="https://github.com/tensorflow/examples/blob/master/tensorflow_examples/lite/model_maker/core/task/searcher.py#L180-L198">View source</a>
<pre class="devsite-click-to-copy prettyprint lang-py tfo-signature-link"> <code>@classmethod</code> <code>create_from_server_scann( serialized_scann_path: str, metadata: List[AnyStr], embedder_path: Optional[str] = None ) -> 'Searcher' </code></pre>Creates the instance from the serialized serving scann directory.
<!-- Tabular view --> <table class="responsive fixed orange"> <colgroup><col width="214px"><col></colgroup> <tr><th colspan="2">Args</th></tr> <tr> <td> `serialized_scann_path` </td> <td> Path to the dir that contains the ScaNN's artifacts. </td> </tr><tr> <td> `metadata` </td> <td> The metadata for each of the embeddings in the database. Passed in the same order as the embeddings in ScaNN. </td> </tr><tr> <td> `embedder_path` </td> <td> Path to the TFLite Embedder model file. </td> </tr> </table> <!-- Tabular view --> <table class="responsive fixed orange"> <colgroup><col width="214px"><col></colgroup> <tr><th colspan="2">Returns</th></tr> <tr class="alt"> <td colspan="2"> A Searcher instance. </td> </tr> </table> <h3 id="export"><code>export</code></h3><a target="_blank" class="external" href="https://github.com/tensorflow/examples/blob/master/tensorflow_examples/lite/model_maker/core/task/searcher.py#L247-L355">View source</a>
<pre class="devsite-click-to-copy prettyprint lang-py tfo-signature-link"> <code>export( export_format: <a href="../../tflite_model_maker/searcher/ExportFormat"><code>tflite_model_maker.searcher.ExportFormat</code></a>, export_filename: str, userinfo: AnyStr, compression: bool = True ) </code></pre>Export the searcher model.
<!-- Tabular view --> <table class="responsive fixed orange"> <colgroup><col width="214px"><col></colgroup> <tr><th colspan="2">Args</th></tr> <tr> <td> `export_format` </td> <td> Export format that could be tflite or on-device ScaNN index file, must be <a href="../../tflite_model_maker/audio_classifier/AudioClassifier#DEFAULT_EXPORT_FORMAT"><code>ExportFormat.TFLITE</code></a> or <a href="../../tflite_model_maker/searcher/ExportFormat#SCANN_INDEX_FILE"><code>ExportFormat.SCANN_INDEX_FILE</code></a>. </td> </tr><tr> <td> `export_filename` </td> <td> File name to save the exported file. The exported file can be TFLite model or on-device ScaNN index file. </td> </tr><tr> <td> `userinfo` </td> <td> A special field in the index file that can be an arbitrary string supplied by the user. </td> </tr><tr> <td> `compression` </td> <td> Whether to snappy compress the index file. </td> </tr> </table>