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checkpoints.lua
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checkpoints.lua
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-- checkpoints.lua
require 'lfs'
local checkpoint = {}
local function deepCopy(tbl)
-- creates a copy of a network with new modules and the same tensors
local copy = {}
for k, v in pairs(tbl) do
if type(v) == 'table' then
copy[k] = deepCopy(v)
else
copy[k] = v
end
end
if torch.typename(tbl) then
torch.setmetatable(copy, torch.typename(tbl))
end
return copy
end
function checkpoint.latest(opt)
if opt.resume == 'none' then
return nil
end
local latestPath = paths.concat(opt.resume, 'latest.t7')
if not paths.filep(latestPath) then
return nil
end
print('=> Loading checkpoint ' .. latestPath)
local latest = torch.load(latestPath)
local optimState = torch.load(paths.concat(opt.resume, latest.optimFile))
return latest, optimState
end
function checkpoint.save(opt, epoch, model, optimState, bestModel)
-- Don't save the DataParallelTable for easier loading on other machines
if torch.type(model) == 'nn.DataParallelTable' then
model = model:get(1)
end
model = deepCopy(model):float():clearState()
local modelFile = paths.concat(opt.save, 'model_' .. epoch .. '.t7')
local optimFile = paths.concat(opt.save, 'optimState_' .. epoch .. '.t7')
torch.save(paths.concat(opt.save, modelFile), model)
torch.save(paths.concat(opt.save, optimFile), optimState)
torch.save(paths.concat(opt.save, 'latest.t7'), {
epoch = epoch,
modelFile = modelFile,
optimFile = optimFile,
})
print("Deleting old models from disk")
local modelFile = paths.concat(opt.save, 'model_' .. (epoch-2) .. '.t7')
local optimFile = paths.concat(opt.save, 'optimState_' .. (epoch-2) .. '.t7')
if lfs.attributes(modelFile) then
os.remove(modelFile)
end
if lfs.attributes(optimFile) then
os.remove(optimFile)
end
print("Saving model to disk")
if bestModel then
torch.save(paths.concat(opt.save, 'model_best.t7'), model)
end
end
return checkpoint