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adding gradient clipping support for SGD #162

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adding gradient clipping support for SGD #162

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11 changes: 9 additions & 2 deletions sgd.lua
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Original file line number Diff line number Diff line change
Expand Up @@ -36,6 +36,7 @@ function optim.sgd(opfunc, x, config, state)
local nesterov = config.nesterov or false
local lrs = config.learningRates
local wds = config.weightDecays
local clip = config.clipval
state.evalCounter = state.evalCounter or 0
local nevals = state.evalCounter
assert(not nesterov or (mom > 0 and damp == 0), "Nesterov momentum requires a momentum and zero dampening")
Expand Down Expand Up @@ -71,7 +72,13 @@ function optim.sgd(opfunc, x, config, state)
-- (4) learning rate decay (annealing)
local clr = lr / (1 + nevals*lrd)

-- (5) parameter update with single or individual learning rates
-- (5) gradient clipping
ndfdx = dfdx:norm()
if clip and ndfdx >= clip then
dfdx:div(ndfdx):mul(clip)
end

-- (6) parameter update with single or individual learning rates
if lrs then
if not state.deltaParameters then
state.deltaParameters = torch.Tensor():typeAs(x):resizeAs(dfdx)
Expand All @@ -82,7 +89,7 @@ function optim.sgd(opfunc, x, config, state)
x:add(-clr, dfdx)
end

-- (6) update evaluation counter
-- (7) update evaluation counter
state.evalCounter = state.evalCounter + 1

-- return x*, f(x) before optimization
Expand Down