class_docstr: Rule based sentiment detector, which calculates a score based on
  predefined keywords.
  
  This is the instantiated model of the :class:`.SentimentDetector`. For
  training your own model, please see the documentation of that class.
  
  By default, the sentiment score will be assigned labels ``"positive"`` if
  the score is ``>= 0``, else ``"negative"``.
  
  For extended examples of usage, see the `Examples
  <https://github.com/JohnSnowLabs/spark-nlp/blob/master/examples/python/training/english/dictionary-sentiment/sentiment.ipynb>`__.
  
  ====================== ======================
  Input Annotation types Output Annotation type
  ====================== ======================
  ``TOKEN, DOCUMENT``    ``SENTIMENT``
  ====================== ======================
  
  Parameters
  ----------
  None
code: def __init__(
      self,
      classname="com.johnsnowlabs.nlp.annotators.sda.pragmatic.SentimentDetectorModel",
      java_model=None,
  ):
      super(SentimentDetectorModel, self).__init__(
          classname=classname, java_model=java_model
      )
  
file_path: spark-nlp/python/sparknlp/annotator/sentiment/sentiment_detector.py
imports: from sparknlp.common import *
label_desc: Use image node_id 1 to create a new SentimentDetectorModel object from inherited base classes: AnnotatorModel with example: obj = SentimentDetectorModel(classname, java_model)