Module: DNN::Layers::LayerNode

Included in:
Add, AvgPool2D, BatchNormalization, Concatenate, Conv2D, Conv2DTranspose, Dense, Div, Dot, Dropout, ELU, Embedding, Exp, Lasso, LeakyReLU, Log, MaxPool2D, Mean, Mish, Mul, Neg, Pow, RNN, ReLU, Reshape, Ridge, Sigmoid, Softplus, Softsign, Split, Sqrt, Sub, Sum, Swish, Tanh, UnPool2D, DNN::Losses::Hinge, DNN::Losses::HuberLoss, DNN::Losses::MeanAbsoluteError, DNN::Losses::MeanSquaredError, DNN::Losses::SigmoidCrossEntropy, DNN::Losses::SoftmaxCrossEntropy
Defined in:
lib/dnn/core/layers/basic_layers.rb

Instance Method Summary collapse

Instance Method Details

#backward_node(*dys) ⇒ Object

Raises:

  • (NotImplementedError) 


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# File 'lib/dnn/core/layers/basic_layers.rb', line 19

def backward_node(*dys)
  raise NotImplementedError, "Class '#{self.class.name}' has implement method 'backward_node'"
end

#forward(*inputs) ⇒ Object 



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# File 'lib/dnn/core/layers/basic_layers.rb', line 5

def forward(*inputs)
  xs = inputs.map(&:data)
  prevs = inputs.map { |input| input.is_a?(Tensor) ? input.link : input }
  ys = forward_node(*xs)
  num_outputs = (ys.is_a?(Array) ? ys.length : 1)
  link = Link.new(prevs: prevs, layer_node: self, num_outputs: num_outputs)
  prevs.map { |prev| prev.next = link if prev.is_a?(Link) }
  Tensor.convert(ys, link)
end

#forward_node(*xs) ⇒ Object

Raises:

  • (NotImplementedError) 


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# File 'lib/dnn/core/layers/basic_layers.rb', line 15

def forward_node(*xs)
  raise NotImplementedError, "Class '#{self.class.name}' has implement method 'forward_node'"
end