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nn.utils = {}
function nn.utils.recursiveType(param, type_str)
if torch.type(param) == 'table' then
for k, v in pairs(param) do
param[k] = nn.utils.recursiveType(v, type_str)
end
elseif torch.isTypeOf(param, 'nn.Module') or
torch.isTypeOf(param, 'nn.Criterion') then
param:type(type_str)
elseif torch.isTensor(param) then
param = param:type(type_str)
end
return param
end
function nn.utils.recursiveResizeAs(t1,t2)
if torch.type(t2) == 'table' then
t1 = (torch.type(t1) == 'table') and t1 or {t1}
for key,_ in pairs(t2) do
t1[key], t2[key] = nn.utils.recursiveResizeAs(t1[key], t2[key])
end
elseif torch.isTensor(t2) then
t1 = torch.isTensor(t1) and t1 or t2.new()
t1:resizeAs(t2)
else
error("expecting nested tensors or tables. Got "..
torch.type(t1).." and "..torch.type(t2).." instead")
end
return t1, t2
end
function nn.utils.recursiveFill(t2, val)
if torch.type(t2) == 'table' then
for key,_ in pairs(t2) do
t2[key] = nn.utils.recursiveFill(t2[key], val)
end
elseif torch.isTensor(t2) then
t2:fill(val)
else
error("expecting tensor or table thereof. Got "
..torch.type(t2).." instead")
end
return t2
end
function nn.utils.recursiveAdd(t1, val, t2)
if not t2 then
assert(val, "expecting at least two arguments")
t2 = val
val = 1
end
val = val or 1
if torch.type(t2) == 'table' then
t1 = (torch.type(t1) == 'table') and t1 or {t1}
for key,_ in pairs(t2) do
t1[key], t2[key] = nn.utils.recursiveAdd(t1[key], val, t2[key])
end
elseif torch.isTensor(t2) and torch.isTensor(t2) then
t1:add(val, t2)
else
error("expecting nested tensors or tables. Got "..
torch.type(t1).." and "..torch.type(t2).." instead")
end
return t1, t2
end
function nn.utils.addSingletonDimension(t, dim)
assert(torch.isTensor(t), "input tensor expected")
local dim = dim or 1
assert(dim > 0 and dim <= t:dim(), "invalid dimension: " .. dim)
local view = t.new()
local size = torch.LongStorage(t:dim() + 1)
local stride = torch.LongStorage(t:dim() + 1)
for d = 1, dim - 1 do
size[d] = t:size(d)
stride[d] = t:stride(d)
end
size[dim] = 1
stride[dim] = 1
for d = dim + 1, t:dim() + 1 do
size[d] = t:size(d - 1)
stride[d] = t:stride(d - 1)
end
view:set(t:storage(), t:storageOffset(), size, stride)
return view
end
table.unpack = table.unpack or unpack
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