Class: Informers::ZeroShotClassificationPipeline

Inherits:
Pipeline
  • Object
show all
Defined in:
lib/informers/pipelines.rb

Instance Method Summary collapse

Constructor Details

#initialize(**options) ⇒ ZeroShotClassificationPipeline

Returns a new instance of ZeroShotClassificationPipeline.



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# File 'lib/informers/pipelines.rb', line 407

def initialize(**options)
  super(**options)

  @label2id = @model.config[:label2id].transform_keys(&:downcase)

  @entailment_id = @label2id["entailment"]
  if @entailment_id.nil?
    warn "Could not find 'entailment' in label2id mapping. Using 2 as entailment_id."
    @entailment_id = 2
  end

  @contradiction_id = @label2id["contradiction"] || @label2id["not_entailment"]
  if @contradiction_id.nil?
    warn "Could not find 'contradiction' in label2id mapping. Using 0 as contradiction_id."
    @contradiction_id = 0
  end
end

Instance Method Details

#call(texts, candidate_labels, hypothesis_template: "This example is {}.", multi_label: false) ⇒ Object 



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# File 'lib/informers/pipelines.rb', line 425

def call(texts, candidate_labels, hypothesis_template: "This example is {}.", multi_label: false)
  is_batched = texts.is_a?(Array)
  if !is_batched
    texts = [texts]
  end
  if !candidate_labels.is_a?(Array)
    candidate_labels = [candidate_labels]
  end

  # Insert labels into hypothesis template
  hypotheses = candidate_labels.map { |x| hypothesis_template.sub("{}", x) }

  # How to perform the softmax over the logits:
  #  - true:  softmax over the entailment vs. contradiction dim for each label independently
  #  - false: softmax the "entailment" logits over all candidate labels
  softmax_each = multi_label || candidate_labels.length == 1

  to_return = []
  texts.each do |premise|
    entails_logits = []

    hypotheses.each do |hypothesis|
      inputs = @tokenizer.(
        premise,
        text_pair: hypothesis,
        padding: true,
        truncation: true
      )
      outputs = @model.(inputs)

      if softmax_each
        entails_logits << [
          outputs.logits[0][@contradiction_id],
          outputs.logits[0][@entailment_id]
        ]
      else
        entails_logits << outputs.logits[0][@entailment_id]
      end
    end

    scores =
      if softmax_each
        entails_logits.map { |x| Utils.softmax(x)[1] }
      else
        Utils.softmax(entails_logits)
      end

    # Sort by scores (desc) and return scores with indices
    scores_sorted = scores.map.with_index { |x, i| [x, i] }.sort_by { |v| -v[0] }

    to_return << {
      sequence: premise,
      labels: scores_sorted.map { |x| candidate_labels[x[1]] },
      scores: scores_sorted.map { |x| x[0] }
    }
  end
  is_batched ? to_return : to_return[0]
end