List / Dict of the input tensors of the TFLite model. The
order should be the same as the keras model if it's a list. It also
accepts tensor directly if the model has only 1 input.
Returns
List of the output tensors for multi-output models, otherwise just
the output tensor. The order should be the same as the keras model.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-05-07 UTC."],[],[],null,["# mediapipe_model_maker.model_util.LiteRunner\n\n\u003cbr /\u003e\n\n|------------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/google/mediapipe/blob/master/mediapipe/model_maker/python/core/utils/model_util.py#L267-L339) |\n\nA runner to do inference with the TFLite model.\n\n#### View aliases\n\n\n**Main aliases**\n\n[`mediapipe_model_maker.face_stylizer.face_stylizer.face_stylizer_options.model_opt.loss_functions.model_util.LiteRunner`](https://www.tensorflow.org/mediapipe/api/solutions/python/mediapipe_model_maker/model_util/LiteRunner), [`mediapipe_model_maker.face_stylizer.face_stylizer.loss_functions.model_util.LiteRunner`](https://www.tensorflow.org/mediapipe/api/solutions/python/mediapipe_model_maker/model_util/LiteRunner), [`mediapipe_model_maker.face_stylizer.face_stylizer.model_opt.loss_functions.model_util.LiteRunner`](https://www.tensorflow.org/mediapipe/api/solutions/python/mediapipe_model_maker/model_util/LiteRunner), [`mediapipe_model_maker.face_stylizer.face_stylizer.model_util.LiteRunner`](https://www.tensorflow.org/mediapipe/api/solutions/python/mediapipe_model_maker/model_util/LiteRunner), [`mediapipe_model_maker.face_stylizer.face_stylizer_options.model_opt.loss_functions.model_util.LiteRunner`](https://www.tensorflow.org/mediapipe/api/solutions/python/mediapipe_model_maker/model_util/LiteRunner), [`mediapipe_model_maker.face_stylizer.model_options.loss_functions.model_util.LiteRunner`](https://www.tensorflow.org/mediapipe/api/solutions/python/mediapipe_model_maker/model_util/LiteRunner)\n\n\u003cbr /\u003e\n\n mediapipe_model_maker.model_util.LiteRunner(\n tflite_model: bytearray\n )\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|----------------|---------------------------------------------------|\n| `tflite_model` | A valid flatbuffer representing the TFLite model. |\n\n\u003cbr /\u003e\n\nMethods\n-------\n\n### `run`\n\n[View source](https://github.com/google/mediapipe/blob/master/mediapipe/model_maker/python/core/utils/model_util.py#L281-L339) \n\n run(\n input_tensors: Union[List[tf.Tensor], Dict[str, tf.Tensor]]\n ) -\u003e Union[List[tf.Tensor], tf.Tensor]\n\nRuns inference with the TFLite model.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ||\n|-----------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `input_tensors` | List / Dict of the input tensors of the TFLite model. The order should be the same as the keras model if it's a list. It also accepts tensor directly if the model has only 1 input. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ||\n|---|---|\n| List of the output tensors for multi-output models, otherwise just the output tensor. The order should be the same as the keras model. ||\n\n\u003cbr /\u003e"]]