Class: Torch::Optim::SGD

Inherits:
Optimizer show all
Defined in:
lib/torch/optim/sgd.rb

Instance Attribute Summary

Attributes inherited from Optimizer

#param_groups

Instance Method Summary collapse

Methods inherited from Optimizer

#add_param_group, #load_state_dict, #state_dict, #zero_grad

Constructor Details

#initialize(params, lr:, momentum: 0, dampening: 0, weight_decay: 0, nesterov: false) ⇒ SGD

Returns a new instance of SGD.

Raises:

  • (ArgumentError) 


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# File 'lib/torch/optim/sgd.rb', line 5

def initialize(params, lr:, momentum: 0, dampening: 0, weight_decay: 0, nesterov: false)
  raise ArgumentError, "Invalid learning rate: #{lr}" if lr < 0.0
  raise ArgumentError, "Invalid momentum value: #{momentum}" if momentum < 0.0
  raise ArgumentError, "Invalid weight_decay value: #{weight_decay}" if weight_decay < 0.0

  defaults = {lr: lr, momentum: momentum, dampening: dampening, weight_decay: weight_decay, nesterov: nesterov}

  if nesterov && (momentum <= 0 || dampening != 0)
    raise ArgumentError, "Nesterov momentum requires a momentum and zero dampening"
  end

  super(params, defaults)
end

Instance Method Details

#step(closure = nil) ⇒ Object 



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# File 'lib/torch/optim/sgd.rb', line 19

def step(closure = nil)
  loss = nil
  if closure
    loss = closure.call
  end

  @param_groups.each do |group|
    weight_decay = group[:weight_decay]
    momentum = group[:momentum]
    dampening = group[:dampening]
    nesterov = group[:nesterov]

    group[:params].each do |p|
      next unless p.grad
      d_p = p.grad.data
      if weight_decay != 0
        d_p.add!(weight_decay, p.data)
      end
      if momentum != 0
        param_state = @state[p]
        if !param_state.key(:momentum_buffer)
          buf = param_state[:momentum_buffer] = Torch.clone(d_p).detach
        else
          buf = param_state[:momentum_buffer]
          buf.mul!(momentum).add!(1 - dampening, d_p)
        end
        if nesterov
          d_p = d_p.add(momentum, buf)
        else
          d_p = buf
        end
      end

      p.data.add!(-group[:lr], d_p)
    end
  end

  loss
end