Class: DNN::Layers::Dense
Instance Attribute Summary collapse
Attributes inherited from Connection
#bias, #bias_initializer, #bias_regularizer, #weight, #weight_initializer, #weight_regularizer
#trainable
Attributes inherited from Layer
#input_shape, #output_shape
Instance Method Summary
collapse
Methods included from LayerNode
#forward
Methods inherited from Connection
#get_params, #regularizers, #use_bias
#clean, #get_params
Methods inherited from Layer
#<<, #built?, #call, call, #clean, #forward, from_hash
Constructor Details
#initialize(num_units, weight_initializer: Initializers::RandomNormal.new, bias_initializer: Initializers::Zeros.new, weight_regularizer: nil, bias_regularizer: nil, use_bias: true) ⇒ Dense
Returns a new instance of Dense.
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# File 'lib/dnn/core/layers/basic_layers.rb', line 240
def initialize(num_units,
weight_initializer: Initializers::RandomNormal.new,
bias_initializer: Initializers::Zeros.new,
weight_regularizer: nil,
bias_regularizer: nil,
use_bias: true)
super(weight_initializer: weight_initializer, bias_initializer: bias_initializer,
weight_regularizer: weight_regularizer, bias_regularizer: bias_regularizer, use_bias: use_bias)
@num_units = num_units
end
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Instance Attribute Details
#num_units ⇒ Object
Returns the value of attribute num_units.
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# File 'lib/dnn/core/layers/basic_layers.rb', line 237
def num_units
@num_units
end
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Instance Method Details
#backward_node(dy) ⇒ Object
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# File 'lib/dnn/core/layers/basic_layers.rb', line 269
def backward_node(dy)
if @trainable
@weight.grad += @x.transpose.dot(dy)
@bias.grad += dy.sum(0) if @bias
end
dy.dot(@weight.data.transpose)
end
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#build(input_shape) ⇒ Object
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# File 'lib/dnn/core/layers/basic_layers.rb', line 251
def build(input_shape)
unless input_shape.length == 1
raise DNNShapeError, "Input shape is #{input_shape}. But input shape must be 1 dimensional."
end
super
num_prev_units = input_shape[0]
@weight.data = Xumo::SFloat.new(num_prev_units, @num_units)
@bias.data = Xumo::SFloat.new(@num_units) if @bias
init_weight_and_bias
end
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#compute_output_shape ⇒ Object
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# File 'lib/dnn/core/layers/basic_layers.rb', line 277
def compute_output_shape
[@num_units]
end
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#forward_node(x) ⇒ Object
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# File 'lib/dnn/core/layers/basic_layers.rb', line 262
def forward_node(x)
@x = x
y = x.dot(@weight.data)
y += @bias.data if @bias
y
end
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#load_hash(hash) ⇒ Object
#to_hash ⇒ Object
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# File 'lib/dnn/core/layers/basic_layers.rb', line 281
def to_hash
super(num_units: @num_units)
end
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