tensorflow/lite/g3doc/api_docs/python/tflite_model_maker/text_classifier/BertClassifierSpec.md
page_type: reference description: A specification of BERT model for text classification.
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A specification of BERT model for text classification.
<pre class="devsite-click-to-copy prettyprint lang-py tfo-signature-link"> <code>tflite_model_maker.text_classifier.BertClassifierSpec( uri='https://tfhub.dev/tensorflow/bert_en_uncased_L-12_H-768_A-12/1', model_dir=None, seq_len=128, dropout_rate=0.1, initializer_range=0.02, learning_rate=3e-05, distribution_strategy='mirrored', num_gpus=-1, tpu='', trainable=True, do_lower_case=True, is_tf2=True, name='Bert', tflite_input_name=None, default_batch_size=32, index_to_label=None ) </code></pre> <!-- Placeholder for "Used in" --> <!-- 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> `uri`<a id="uri"></a> </td> <td> TF-Hub path/url to Bert module. </td> </tr><tr> <td> `model_dir`<a id="model_dir"></a> </td> <td> The location of the model checkpoint files. </td> </tr><tr> <td> `seq_len`<a id="seq_len"></a> </td> <td> Length of the sequence to feed into the model. </td> </tr><tr> <td> `dropout_rate`<a id="dropout_rate"></a> </td> <td> The rate for dropout. </td> </tr><tr> <td> `initializer_range`<a id="initializer_range"></a> </td> <td> The stdev of the truncated_normal_initializer for initializing all weight matrices. </td> </tr><tr> <td> `learning_rate`<a id="learning_rate"></a> </td> <td> The initial learning rate for Adam. </td> </tr><tr> <td> `distribution_strategy`<a id="distribution_strategy"></a> </td> <td> A string specifying which distribution strategy to use. Accepted values are 'off', 'one_device', 'mirrored', 'parameter_server', 'multi_worker_mirrored', and 'tpu' -- case insensitive. 'off' means not to use Distribution Strategy; 'tpu' means to use TPUStrategy using `tpu_address`. </td> </tr><tr> <td> `num_gpus`<a id="num_gpus"></a> </td> <td> How many GPUs to use at each worker with the DistributionStrategies API. The default is -1, which means utilize all available GPUs. </td> </tr><tr> <td> `tpu`<a id="tpu"></a> </td> <td> TPU address to connect to. </td> </tr><tr> <td> `trainable`<a id="trainable"></a> </td> <td> boolean, whether pretrain layer is trainable. </td> </tr><tr> <td> `do_lower_case`<a id="do_lower_case"></a> </td> <td> boolean, whether to lower case the input text. Should be True for uncased models and False for cased models. </td> </tr><tr> <td> `is_tf2`<a id="is_tf2"></a> </td> <td> boolean, whether the hub module is in TensorFlow 2.x format. </td> </tr><tr> <td> `name`<a id="name"></a> </td> <td> The name of the object. </td> </tr><tr> <td> `tflite_input_name`<a id="tflite_input_name"></a> </td> <td> Dict, input names for the TFLite model. </td> </tr><tr> <td> `default_batch_size`<a id="default_batch_size"></a> </td> <td> Default batch size for training. </td> </tr><tr> <td> `index_to_label`<a id="index_to_label"></a> </td> <td> List of labels in the training data. e.g. ['neg', 'pos']. </td> </tr> </table><a target="_blank" class="external" href="https://github.com/tensorflow/examples/blob/master/tensorflow_examples/lite/model_maker/core/task/model_spec/text_spec.py#L438-L445">View source</a>
<pre class="devsite-click-to-copy prettyprint lang-py tfo-signature-link"> <code>build() </code></pre>Builds the class. Used for lazy initialization.
<h3 id="convert_examples_to_features"><code>convert_examples_to_features</code></h3><a target="_blank" class="external" href="https://github.com/tensorflow/examples/blob/master/tensorflow_examples/lite/model_maker/core/task/model_spec/text_spec.py#L544-L549">View source</a>
<pre class="devsite-click-to-copy prettyprint lang-py tfo-signature-link"> <code>convert_examples_to_features( examples, tfrecord_file, label_names ) </code></pre>Converts examples to features and write them into TFRecord file.
<h3 id="create_model"><code>create_model</code></h3><a target="_blank" class="external" href="https://github.com/tensorflow/examples/blob/master/tensorflow_examples/lite/model_maker/core/task/model_spec/text_spec.py#L551-L577">View source</a>
<pre class="devsite-click-to-copy prettyprint lang-py tfo-signature-link"> <code>create_model( num_classes, optimizer='adam', with_loss_and_metrics=True ) </code></pre>Creates the keras model.
<h3 id="get_config"><code>get_config</code></h3><a target="_blank" class="external" href="https://github.com/tensorflow/examples/blob/master/tensorflow_examples/lite/model_maker/core/task/model_spec/text_spec.py#L623-L626">View source</a>
<pre class="devsite-click-to-copy prettyprint lang-py tfo-signature-link"> <code>get_config() </code></pre>Gets the configuration.
<h3 id="get_default_quantization_config"><code>get_default_quantization_config</code></h3><a target="_blank" class="external" href="https://github.com/tensorflow/examples/blob/master/tensorflow_examples/lite/model_maker/core/task/model_spec/text_spec.py#L420-L424">View source</a>
<pre class="devsite-click-to-copy prettyprint lang-py tfo-signature-link"> <code>get_default_quantization_config() </code></pre>Gets the default quantization configuration.
<h3 id="get_name_to_features"><code>get_name_to_features</code></h3><a target="_blank" class="external" href="https://github.com/tensorflow/examples/blob/master/tensorflow_examples/lite/model_maker/core/task/model_spec/text_spec.py#L523-L532">View source</a>
<pre class="devsite-click-to-copy prettyprint lang-py tfo-signature-link"> <code>get_name_to_features() </code></pre>Gets the dictionary describing the features.
<h3 id="reorder_input_details"><code>reorder_input_details</code></h3><a target="_blank" class="external" href="https://github.com/tensorflow/examples/blob/master/tensorflow_examples/lite/model_maker/core/task/model_spec/text_spec.py#L426-L436">View source</a>
<pre class="devsite-click-to-copy prettyprint lang-py tfo-signature-link"> <code>reorder_input_details( tflite_input_details ) </code></pre>Reorders the tflite input details to map the order of keras model.
<h3 id="run_classifier"><code>run_classifier</code></h3><a target="_blank" class="external" href="https://github.com/tensorflow/examples/blob/master/tensorflow_examples/lite/model_maker/core/task/model_spec/text_spec.py#L579-L621">View source</a>
<pre class="devsite-click-to-copy prettyprint lang-py tfo-signature-link"> <code>run_classifier( train_ds, validation_ds, epochs, steps_per_epoch, num_classes, **kwargs ) </code></pre>Creates classifier and runs the classifier training.
<!-- Tabular view --> <table class="responsive fixed orange"> <colgroup><col width="214px"><col></colgroup> <tr><th colspan="2">Args</th></tr> <tr> <td> `train_ds` </td> <td> tf.data.Dataset, training data to be fed in tf.keras.Model.fit(). </td> </tr><tr> <td> `validation_ds` </td> <td> tf.data.Dataset, validation data to be fed in tf.keras.Model.fit(). </td> </tr><tr> <td> `epochs` </td> <td> Integer, training epochs. </td> </tr><tr> <td> `steps_per_epoch` </td> <td> Integer or None. Total number of steps (batches of samples) before declaring one epoch finished and starting the next epoch. If `steps_per_epoch` is None, the epoch will run until the input dataset is exhausted. </td> </tr><tr> <td> `num_classes` </td> <td> Interger, number of classes. </td> </tr><tr> <td> `**kwargs` </td> <td> Other parameters used in the tf.keras.Model.fit(). </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"> tf.keras.Model, the keras model that's already trained. </td> </tr> </table> <h3 id="save_vocab"><code>save_vocab</code></h3><a target="_blank" class="external" href="https://github.com/tensorflow/examples/blob/master/tensorflow_examples/lite/model_maker/core/task/model_spec/text_spec.py#L447-L452">View source</a>
<pre class="devsite-click-to-copy prettyprint lang-py tfo-signature-link"> <code>save_vocab( vocab_filename ) </code></pre>Prints the file path to the vocabulary.
<h3 id="select_data_from_record"><code>select_data_from_record</code></h3><a target="_blank" class="external" href="https://github.com/tensorflow/examples/blob/master/tensorflow_examples/lite/model_maker/core/task/model_spec/text_spec.py#L534-L542">View source</a>
<pre class="devsite-click-to-copy prettyprint lang-py tfo-signature-link"> <code>select_data_from_record( record ) </code></pre>Dispatches records to features and labels.
<!-- Tabular view --> <table class="responsive fixed orange"> <colgroup><col width="214px"><col></colgroup> <tr><th colspan="2"><h2 class="add-link">Class Variables</h2></th></tr> <tr> <td> compat_tf_versions<a id="compat_tf_versions"></a> </td> <td> `[2]` </td> </tr><tr> <td> convert_from_saved_model_tf2<a id="convert_from_saved_model_tf2"></a> </td> <td> `True` </td> </tr><tr> <td> need_gen_vocab<a id="need_gen_vocab"></a> </td> <td> `False` </td> </tr> </table>