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function torch.CudaTensor.apply(self, func)
local x = torch.FloatTensor(self:size()):copy(self)
x:apply(func)
self:copy(x)
return self
end
local function Tensor__type(self,type)
local current = torch.typename(self)
if not type then return current end
if type ~= current then
local new = torch.getmetatable(type).new()
if self:nElement() > 0 then
new:resize(self:size()):copy(self)
end
return new
else
return self
end
end
local function Tensor__typeAs(self,tensor)
return self:type(tensor:type())
end
local function Tensor__cuda(self)
return self:type('torch.CudaTensor')
end
local function Tensor__double(self)
return self:type('torch.DoubleTensor')
end
local function Tensor__float(self)
return self:type('torch.FloatTensor')
end
local function Tensor__byte(self)
return self:type('torch.ByteTensor')
end
local function Tensor__char(self)
return self:type('torch.CharTensor')
end
local function Tensor__int(self)
return self:type('torch.IntTensor')
end
local function Tensor__short(self)
return self:type('torch.ShortTensor')
end
local function Tensor__long(self)
return self:type('torch.LongTensor')
end
rawset(torch.getmetatable('torch.DoubleTensor'), 'cuda', Tensor__cuda)
rawset(torch.getmetatable('torch.FloatTensor'), 'cuda', Tensor__cuda)
rawset(torch.getmetatable('torch.ByteTensor'), 'cuda', Tensor__cuda)
rawset(torch.getmetatable('torch.CharTensor'), 'cuda', Tensor__cuda)
rawset(torch.getmetatable('torch.IntTensor'), 'cuda', Tensor__cuda)
rawset(torch.getmetatable('torch.ShortTensor'), 'cuda', Tensor__cuda)
rawset(torch.getmetatable('torch.LongTensor'), 'cuda', Tensor__cuda)
rawset(torch.getmetatable('torch.CudaTensor'), 'cuda', Tensor__cuda)
rawset(torch.getmetatable('torch.CudaTensor'), 'type', Tensor__type)
rawset(torch.getmetatable('torch.CudaTensor'), 'typeAs', Tensor__typeAs)
rawset(torch.getmetatable('torch.CudaTensor'), 'double', Tensor__double)
rawset(torch.getmetatable('torch.CudaTensor'), 'float', Tensor__float)
rawset(torch.getmetatable('torch.CudaTensor'), 'byte', Tensor__byte)
rawset(torch.getmetatable('torch.CudaTensor'), 'char', Tensor__char)
rawset(torch.getmetatable('torch.CudaTensor'), 'int', Tensor__int)
rawset(torch.getmetatable('torch.CudaTensor'), 'short', Tensor__short)
rawset(torch.getmetatable('torch.CudaTensor'), 'long', Tensor__long)
do
local metatable = torch.getmetatable('torch.CudaTensor')
for _,func in pairs{'expand', 'expandAs', 'view', 'viewAs', 'repeatTensor',
'permute', 'split', 'chunk'} do
rawset(metatable, func, torch[func])
end
end
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