Class: SkillExtractor::MLP
- Inherits:
-
Object
- Object
- SkillExtractor::MLP
- Defined in:
- lib/skill_extractor/mlp.rb
Instance Method Summary collapse
-
#initialize(path) ⇒ MLP
constructor
A new instance of MLP.
-
#predict_proba(xs) ⇒ Object
xs: array of 384-dim L2-normalized embeddings -> array of P(skill).
Constructor Details
#initialize(path) ⇒ MLP
Returns a new instance of MLP.
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# File 'lib/skill_extractor/mlp.rb', line 8 def initialize(path) spec = JSON.parse(File.read(path)) unless spec["format"] == "mlp-weights-v1" raise ArgumentError, "unsupported weights format: #{spec["format"]}" end @layers = spec["layers"].map do |l| { rows: l["shape"][0], cols: l["shape"][1], w: Base64.decode64(l["weights_b64"]).unpack("e*"), b: Base64.decode64(l["bias_b64"]).unpack("e*") } end end |
Instance Method Details
#predict_proba(xs) ⇒ Object
xs: array of 384-dim L2-normalized embeddings -> array of P(skill)
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# File 'lib/skill_extractor/mlp.rb', line 24 def predict_proba(xs) last = @layers.length - 1 xs.map do |x| h = x @layers.each_with_index do |l, i| cols = l[:cols] w = l[:w] nxt = l[:b].dup h.each_with_index do |hv, r| next if hv.zero? off = r * cols cols.times { |j| nxt[j] += hv * w[off + j] } end nxt.map! { |v| v.negative? ? 0.0 : v } if i < last # relu h = nxt end 1.0 / (1.0 + Math.exp(-h[0])) # logistic end end |