class_docstr: APIs to help create and train an Average Word Embedding text classifier.
class_docstr_tok: ["APIs","to","help","create","and","train","an","Average","Word","Embedding","text","classifier","."]
docstr: Creates an Average Word Embedding model.
code: def _create_model(self):
      """Creates an Average Word Embedding model."""
      self._model = tf.keras.Sequential(
          [
              tf.keras.layers.InputLayer(
                  input_shape=[self._model_options.seq_len],
                  dtype=tf.int32,
                  name="input_ids",
              ),
              tf.keras.layers.Embedding(
                  len(self._text_preprocessor.get_vocab()),
                  self._model_options.wordvec_dim,
                  input_length=self._model_options.seq_len,
              ),
              tf.keras.layers.GlobalAveragePooling1D(),
              tf.keras.layers.Dense(
                  self._model_options.wordvec_dim, activation=tf.nn.relu
              ),
              tf.keras.layers.Dropout(self._model_options.dropout_rate),
              tf.keras.layers.Dense(
                  self._num_classes, activation="softmax"
              ),
          ]
      )
  
imports: import abc
  import os
  import tempfile
  from typing import Any, Optional, Sequence, Tuple
  import tensorflow
  from tensorflow_addons import optimizers
  import tensorflow_hub
  from mediapipe.model_maker.python.core.data import dataset
  from mediapipe.model_maker.python.core.tasks import classifier
  from mediapipe.model_maker.python.core.utils import hub_loader
  from mediapipe.model_maker.python.core.utils import loss_functions
  from mediapipe.model_maker.python.core.utils import metrics
  from mediapipe.model_maker.python.core.utils import model_util
  from mediapipe.model_maker.python.core.utils import quantization
  from mediapipe.model_maker.python.text.text_classifier import bert_tokenizer
  from mediapipe.model_maker.python.text.text_classifier import dataset
  from mediapipe.model_maker.python.text.text_classifier import hyperparameters
  from mediapipe.model_maker.python.text.text_classifier import model_options
  from mediapipe.model_maker.python.text.text_classifier import model_spec
  from mediapipe.model_maker.python.text.text_classifier import model_with_tokenizer
  from mediapipe.model_maker.python.text.text_classifier import preprocessor
  from mediapipe.model_maker.python.text.text_classifier import text_classifier_options
  from mediapipe.tasks.python.metadata.metadata_writers import metadata_writer
  from mediapipe.tasks.python.metadata.metadata_writers import text_classifier
label_desc: Use image node_id 5 for calling the _AverageWordEmbeddingClassifier obj's underlying member method code with example usage: obj._create_model() without return types