class_docstr: GestureRecognizer for building hand gesture recognizer model.
  
  Attributes:
    embedding_size: Size of the input gesture embedding vector.
docstr: Initializes GestureRecognizer class.
  
  Args:
    label_names: A list of label names for the classes.
    model_options: options to create gesture recognizer model.
    hparams: The hyperparameters for training hand gesture recognizer model.
docstr_tok: ["Initializes","GestureRecognizer","class",".","Args",":","label_names",":","A","list","of","label","names","for","the","classes",".","model_options",":","options","to","create","gesture","recognizer","model",".","hparams",":","The","hyperparameters","for","training","hand","gesture","recognizer","model","."]
code: def __init__(
      self,
      label_names: List[str],
      model_options: model_opt.GestureRecognizerModelOptions,
      hparams: hp.HParams,
  ):
      """Initializes GestureRecognizer class.
  
      Args:
        label_names: A list of label names for the classes.
        model_options: options to create gesture recognizer model.
        hparams: The hyperparameters for training hand gesture recognizer model.
      """
      super().__init__(
          model_spec=None,
          label_names=label_names,
          shuffle=hparams.shuffle,
      )
      self._model_options = model_options
      self._hparams = hparams
      self._loss_function = loss_functions.FocalLoss(
          gamma=self._hparams.gamma
      )
      self._metric_functions = ["categorical_accuracy"]
      self._optimizer = "adam"
      self._callbacks = self._get_callbacks()
      self._history = None
      self.embedding_size = _EMBEDDING_SIZE
  
imports: import os
  from typing import List
  import tensorflow
  from mediapipe.model_maker.python.core.data import classification_dataset
  from mediapipe.model_maker.python.core.tasks import classifier
  from mediapipe.model_maker.python.core.utils import loss_functions
  from mediapipe.model_maker.python.core.utils import model_util
  from mediapipe.model_maker.python.vision.gesture_recognizer import constants
  from mediapipe.model_maker.python.vision.gesture_recognizer import gesture_recognizer_options
  from mediapipe.model_maker.python.vision.gesture_recognizer import hyperparameters
  from mediapipe.model_maker.python.vision.gesture_recognizer import metadata_writer
  from mediapipe.model_maker.python.vision.gesture_recognizer import model_options
  from mediapipe.tasks.python.metadata.metadata_writers import metadata_writer
label_desc: Use image node_id 1 to create a new GestureRecognizer object from inherited base classes: classifier with example: obj = GestureRecognizer(label_names, model_options, hparams)