          "tag": "class",
          "source": "spacy/pipeline.pyx"
      },
  
      "tensorizer": {
          "title": "Tensorizer",
          "teaser": "Add a tensor with position-sensitive meaning representations to a document.",
          "tag": "class",
          "tag_new": 2,
          "source": "spacy/pipeline.pyx"
      },
  
      "goldparse": {
          "title": "GoldParse",
          "tag": "class",
          "source": "spacy/gold.pyx"
      },
 
</s> remove     +row
        +cell #[+api("tensorizer") #[code Tensorizer]]
        +cell
            |  Add tensors with position-sensitive meaning representations to
            |  #[code Doc] objects.

 </s> add  </s> remove     |  tensor is then
    |  summarized by concatenating max and mean pooling, and a multilayer
    |  perceptron is used to predict an output vector of length #[code nr_class],
    |  before a logistic activation is applied elementwise. The value of each
    |  output neuron is the probability that some class is present.
 </s> add     |  tensor is then summarized by concatenating max and mean pooling, and a
    |  multilayer perceptron is used to predict an output vector of length
    |  #[code nr_class], before a logistic activation is applied elementwise.
    |  The value of each output neuron is the probability that some class is
    |  present. </s> remove     |  As the first component of the
    |  #[+a("/usage/processing-pipelines") processing pipeline], the
    |  tensorizer encodes a document's internal meaning representations as an
 </s> add     |  As the  #[+a("/usage/processing-pipelines") processing pipeline] is
    |  applied spaCy encodes a document's internal meaning representations as an </s> remove     |  document. This step is similar to the #[+api("tensorizer") #[code Tensorizer]]
    |  component, but the #[code TextCategorizer] uses its own CNN model, to
 </s> add     |  document. The #[code TextCategorizer] uses its own CNN model, to </s> remove             "Tensorizer": "tensorizer",
 </s> add 
          "tag": "class",
          "source": "spacy/pipeline.pyx"
      },
  








      "goldparse": {
          "title": "GoldParse",
          "tag": "class",
          "source": "spacy/gold.pyx"
      },
keep keep keep keep replace replace replace replace replace replace replace replace keep keep keep keep keep
 Don't document the tensorizer for now 
website/api/_data.json