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checkpoints.lua
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checkpoints.lua
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--
-- Copyright (c) 2016-2017, Fangchang Ma.
-- Copyright (c) 2016, Facebook, Inc.
-- All rights reserved.
--
-- This source code is licensed under the BSD-style license found in the
-- LICENSE file in the root directory of this source tree. An additional grant
-- of patent rights can be found in the PATENTS file in the same directory.
--
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)
checkpoint.saveDir = opt.saveDir
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(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
-- create a clean copy on the CPU without modifying the original network
model = deepCopy(model):float():clearState()
local modelFile = paths.concat(checkpoint.saveDir, 'model_' .. epoch .. '.t7')
local optimFile = paths.concat(checkpoint.saveDir, 'optimState_' .. epoch .. '.t7')
-- local modelFile = paths.concat(checkpoint.saveDir, 'model_latest.t7')
-- local oldModelFile = paths.concat(checkpoint.saveDir, 'model_latest_backup.t7')
local optimFile = paths.concat(checkpoint.saveDir, 'optimState_latest.t7')
local latestFile = paths.concat(checkpoint.saveDir, 'latest.t7')
if epoch>=3 then
print('=> Saving latest model to ' .. modelFile .. '. Do not interrupt..')
torch.save(modelFile, model)
if epoch>1 then
local oldModelFile = paths.concat(checkpoint.saveDir, 'model_' .. epoch-1 .. '.t7')
if paths.filep(oldModelFile) then
os.execute('rm ' .. oldModelFile)
end
end
print('=> Saving latest model completes')
torch.save(optimFile, optimState)
torch.save(latestFile, {
epoch = epoch,
modelFile = modelFile,
optimFile = optimFile,
})
if bestModel then
local bestModelFile = paths.concat(checkpoint.saveDir, 'model_best.t7')
print('=> Saving best model to ' .. bestModelFile .. '. Do not interrupt..')
os.execute('cp ' .. modelFile .. ' ' .. bestModelFile)
print('=> Saving best model completes')
end
else
print('=> Skip saving any result until epoch>=3 for the sake of efficiency.')
end
end
return checkpoint