Classifier API for natural language classification tasks, categorizes string into different classes.

The API expects a TFLite model with the following input/output tensor:

• Input tensor (kTfLiteString)
  • input of the model, accepts a string.
• Output score tensor (kTfLiteUInt8/kTfLiteInt8/kTfLiteInt16/kTfLiteFloat32/kTfLiteFloat64/kTfLiteBool)
  • output scores for each class, if type is one of the Int types, dequantize it, if it is Bool type, convert the values to 0.0 and 1.0 respectively.
  • can have an optional associated file in metadata for labels, the file should be a plain text file with one label per line, the number of labels should match the number of categories the model outputs. Output label tensor: optional (kTfLiteString) - output classname for each class, should be of the same length with scores. If this tensor is not present, the API uses score indices as classnames. - will be ignored if output score tensor already has an associated label file.
• Optional Output label tensor (kTfLiteString/kTfLiteInt32)
  • output classname for each class, should be of the same length with scores. If this tensor is not present, the API uses score indices as classnames.
  • will be ignored if output score tensor already has an associated labe file.

By default the API tries to find the input/output tensors with default configurations in NLClassifier.NLClassifierOptions, with tensor name prioritized over tensor index. The option is configurable for different TFLite models.