Class: DNN::Layers::SimpleRNNDense

Inherits:
Layer
  • Object
show all
Includes:
LayerNode
Defined in:
lib/dnn/core/layers/rnn_layers.rb

Instance Attribute Summary collapse

Attributes inherited from Layer

#input_shape

Instance Method Summary collapse

Methods included from LayerNode

#backward, #forward

Methods inherited from Layer

#build, #built?, #call, call, #clean, #forward, from_hash, #load_hash, #output_shape, #to_hash

Constructor Details

#initialize(weight, recurrent_weight, bias, activation) ⇒ SimpleRNNDense

Returns a new instance of SimpleRNNDense.



144
145
146
147
148
149
150
 
# File 'lib/dnn/core/layers/rnn_layers.rb', line 144

def initialize(weight, recurrent_weight, bias, activation)
  @weight = weight
  @recurrent_weight = recurrent_weight
  @bias = bias
  @activation = activation.clone
  @trainable = true
end

Instance Attribute Details

#trainable ⇒ Object

Returns the value of attribute trainable.



142
143
144
 
# File 'lib/dnn/core/layers/rnn_layers.rb', line 142

def trainable
  @trainable
end

Instance Method Details

#backward_node(dh2) ⇒ Object 



160
161
162
163
164
165
166
167
168
169
170
 
# File 'lib/dnn/core/layers/rnn_layers.rb', line 160

def backward_node(dh2)
  dh2 = @activation.backward_node(dh2)
  if @trainable
    @weight.grad += @x.transpose.dot(dh2)
    @recurrent_weight.grad += @h.transpose.dot(dh2)
    @bias.grad += dh2.sum(0) if @bias
  end
  dx = dh2.dot(@weight.data.transpose)
  dh = dh2.dot(@recurrent_weight.data.transpose)
  [dx, dh]
end

#forward_node(x, h) ⇒ Object 



152
153
154
155
156
157
158
 
# File 'lib/dnn/core/layers/rnn_layers.rb', line 152

def forward_node(x, h)
  @x = x
  @h = h
  h2 = x.dot(@weight.data) + h.dot(@recurrent_weight.data)
  h2 += @bias.data if @bias
  @activation.forward_node(h2)
end