Class: DNN::Regularizers::L1L2

Inherits:
Regularizer show all
Defined in:
lib/dnn/core/regularizers.rb

Instance Attribute Summary collapse

Attributes inherited from Regularizer

#param

Instance Method Summary collapse

Methods inherited from Regularizer

from_hash

Constructor Details

#initialize(l1_lambda = 0.01, l2_lambda = 0.01) ⇒ L1L2

Returns a new instance of L1L2.

Parameters:

  • l1_lambda (Float) (defaults to: 0.01) —

    L1 regularizer coefficient.

  • l2_lambda (Float) (defaults to: 0.01) —

    L2 regularizer coefficient.



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# File 'lib/dnn/core/regularizers.rb', line 94

def initialize(l1_lambda = 0.01, l2_lambda = 0.01)
  @l1_lambda = l1_lambda
  @l2_lambda = l2_lambda
end

Instance Attribute Details

#l1_lambda ⇒ Object

Returns the value of attribute l1_lambda.



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# File 'lib/dnn/core/regularizers.rb', line 89

def l1_lambda
  @l1_lambda
end

#l2_lambda ⇒ Object

Returns the value of attribute l2_lambda.



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# File 'lib/dnn/core/regularizers.rb', line 90

def l2_lambda
  @l2_lambda
end

Instance Method Details

#backward ⇒ Object 



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# File 'lib/dnn/core/regularizers.rb', line 105

def backward
  dparam = Xumo::SFloat.ones(*@param.data.shape)
  dparam[@param.data < 0] = -1
  @param.grad += @l1_lambda * dparam
  @param.grad += @l2_lambda * @param.data
end

#forward(x) ⇒ Object 



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# File 'lib/dnn/core/regularizers.rb', line 99

def forward(x)
  l1 = @l1_lambda * @param.data.abs.sum
  l2 = 0.5 * @l2_lambda * (@param.data ** 2).sum
  x + l1 + l2
end

#load_hash(hash) ⇒ Object 



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# File 'lib/dnn/core/regularizers.rb', line 116

def load_hash(hash)
  initialize(hash[:l1_lambda], hash[:l2_lambda])
end

#to_hash ⇒ Object 



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# File 'lib/dnn/core/regularizers.rb', line 112

def to_hash
  super(l1_lambda: l1_lambda, l2_lambda: l2_lambda)
end