Class: DNN::Layers::Conv2D

Inherits:
HasParamLayer show all
Includes:
Initializers, Convert
Defined in:
lib/dnn/core/layers.rb

Instance Attribute Summary

Attributes inherited from HasParamLayer

#grads, #params

Instance Method Summary collapse

Methods included from Convert

#col2im, #im2col, #padding

Methods inherited from HasParamLayer

#update

Methods inherited from Layer

#prev_layer

Constructor Details

#initialize(num_filters, filter_height, filter_width, weight_initializer: nil, bias_initializer: nil, strides: [1, 1], padding: 0, weight_decay: 0) ⇒ Conv2D

Returns a new instance of Conv2D.



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# File 'lib/dnn/core/layers.rb', line 165

def initialize(num_filters, filter_height, filter_width,
               weight_initializer: nil,
               bias_initializer: nil,
               strides: [1, 1],
               padding: 0,
               weight_decay: 0)
  super()
  @num_filters = num_filters
  @filter_height = filter_height
  @filter_width = filter_width
  @weight_initializer = (weight_initializer || RandomNormal.new)
  @bias_initializer = (bias_initializer || Zeros.new)
  @strides = strides
  @weight_decay = weight_decay
  @padding = padding
end

Instance Method Details

#backward(dout) ⇒ Object 



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# File 'lib/dnn/core/layers.rb', line 197

def backward(dout)
  dout = dout.transpose(0, 2, 3, 1)
  dout = dout.reshape(dout.shape[0..2].reduce(:*), dout.shape[3])
  @grads[:weight] = @col.transpose.dot(dout)
  if @weight_decay > 0
    dridge = @weight_decay * @params[:weight]
    @grads[:weight] += dridge
  end
  @grads[:bias] = dout.sum(0)
  dcol = dout.dot(@params[:weight].transpose)
  col2im(dcol, @x_shape, @out_height, @out_width, @filter_height, @filter_width, @strides)
end

#forward(x) ⇒ Object 



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# File 'lib/dnn/core/layers.rb', line 189

def forward(x)
  x = padding(x, 2) if @padding > 0
  @x_shape = x.shape
  @col = im2col(x, @out_height, @out_width, @filter_height, @filter_width, @strides)
  out = @col.dot(@params[:weight])
  out.reshape(@model.batch_size, @out_height, @out_width, out.shape[3]).transpose(0, 3, 1, 2)
end

#init(model) ⇒ Object 



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# File 'lib/dnn/core/layers.rb', line 182

def init(model)
  super
  prev_height, prev_width = prev_layer.shape[1], prev_layer.shape[2]
  @out_height = (prev_height + @padding * 2 - @filter_height) / @strides[0] + 1
  @out_width = (prev_width + @padding * 2 - @filter_width) / @strides[1] + 1
end

#shape ⇒ Object 



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# File 'lib/dnn/core/layers.rb', line 210

def shape
  [@num_filters, @out_height, @out_width]
end