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Tensor.lua
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include('THZCi.lua')
local argcheck = require 'argcheck'
local ffi=require 'ffi'
-- local torch = require 'torch'
require 'pprint'
local ztorch = require 'ztorch'
local THZCudaTensor_abs = C['THZCudaTensor_abs']
local THZCudaTensor_arg = C['THZCudaTensor_arg']
local THZCudaTensor_norm = C['THZCudaTensor_norm']
local THZCudaTensor_real = C['THZCudaTensor_real']
local THZCudaTensor_imag = C['THZCudaTensor_imag']
local THZCudaTensor_sign = C['THZCudaTensor_sign']
local THZCudaTensor_zabs = C['THZCudaTensor_zabs']
local THZCudaTensor_zarg = C['THZCudaTensor_zarg']
local THZCudaTensor_znorm = C['THZCudaTensor_znorm']
local THZCudaTensor_zreal = C['THZCudaTensor_zreal']
local THZCudaTensor_zimag = C['THZCudaTensor_zimag']
local THZCudaTensor_normall = C['THZCudaTensor_normall']
local THZCudaTensor_normDim = C['THZCudaTensor_normDim']
local THZCudaTensor_cim = C['THZCudaTensor_cim']
local THZCudaTensor_cre = C['THZCudaTensor_cre']
local THZCudaTensor_copyIm = C['THZCudaTensor_copyIm']
local THZCudaTensor_copyRe = C['THZCudaTensor_copyRe']
local THZCudaTensor_fillim = C['THZCudaTensor_fillim']
local THZCudaTensor_fillre = C['THZCudaTensor_fillre']
local THZCudaTensor_polar = C['THZCudaTensor_polar']
-- local THZCudaTensor_polarabs = C['THZCudaTensor_polarabs']
-- local THZCudaTensor_polararg = C['THZCudaTensor_polararg']
local THZCudaTensor_copy = C['THZCudaTensor_copy']
local THZCudaTensor_copyByte = C['THZCudaTensor_copyByte']
local THZCudaTensor_copyChar = C['THZCudaTensor_copyChar']
local THZCudaTensor_copyShort = C['THZCudaTensor_copyShort']
local THZCudaTensor_copyInt = C['THZCudaTensor_copyInt']
local THZCudaTensor_copyLong = C['THZCudaTensor_copyLong']
local THZCudaTensor_copyFloat = C['THZCudaTensor_copyFloat']
local THZCudaTensor_copyDouble = C['THZCudaTensor_copyDouble']
local THZCudaTensor_copyZFloat = C['THZCudaTensor_copyZFloat']
local THZFloatTensor_copyZCuda = C['THZFloatTensor_copyZCuda']
local THZCudaTensor_copyZCuda = C['THZCudaTensor_copyZCuda']
local THZCudaTensor_copyAsyncZFloat = C['THZCudaTensor_copyAsyncZFloat']
local THZFloatTensor_copyAsyncZCuda = C['THZFloatTensor_copyAsyncZCuda']
local THZCudaTensor_fft = C['THZCudaTensor_fft']
local THZCudaTensor_fftBatched = C['THZCudaTensor_fftBatched']
local THZCudaTensor_ifft = C['THZCudaTensor_ifft']
local THZCudaTensor_ifftBatched = C['THZCudaTensor_ifftBatched']
local THZCudaTensor_ifftU = C['THZCudaTensor_ifftU']
local THZCudaTensor_ifftBatchedU = C['THZCudaTensor_ifftBatchedU']
local THZCudaTensor_add = C['THZCudaTensor_add']
local THZCudaTensor_mul = C['THZCudaTensor_mul']
local THZCudaTensor_div = C['THZCudaTensor_div']
local THZCudaTensor_addcmul = C['THZCudaTensor_addcmul']
local THZCudaTensor_addcdiv = C['THZCudaTensor_addcdiv']
local THZCudaTensor_cmul = C['THZCudaTensor_cmul']
local THZCudaTensor_cmulZR = C['THZCudaTensor_cmulZR']
local THZCudaTensor_cadd = C['THZCudaTensor_cadd']
local THZCudaTensor_cpow = C['THZCudaTensor_cpow']
local THZCudaTensor_cdiv = C['THZCudaTensor_cdiv']
local THZCudaTensor_cdivZR = C['THZCudaTensor_cdivZR']
local THZCudaTensor_narrow = C['THZCudaTensor_narrow']
local THZCudaTensor_select = C['THZCudaTensor_select']
local THZCudaTensor_newNarrow = C['THZCudaTensor_newNarrow']
local THZCudaTensor_newSelect = C['THZCudaTensor_newSelect']
local THZCudaTensor_resize = C['THZCudaTensor_resize']
local THZCudaTensor_resizeAs = C['THZCudaTensor_resizeAs']
local THZCudaTensor_resize4d = C['THZCudaTensor_resize4d']
local THZCudaTensor_dot = C['THZCudaTensor_dot']
local THZCudaTensor_maskedFill = C['THZCudaTensor_maskedFill']
function torch.ZCudaTensor.apply(self, func)
local x = torch.ZFloatTensor(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__zcuda(self)
local zfloat = self:type('torch.ZFloatTensor')
return Tensor__type(zfloat,"torch.ZCudaTensor")
end
local function ZFTensor__zcuda(self)
return torch.ZCudaTensor(self:size()):copy(self)
end
local function Tensor__zcuda_device(self)
-- TODO
end
local function Tensor__double(self)
return self:type('torch.DoubleTensor')
end
local function Tensor__zfloat(self)
return self:type('torch.ZFloatTensor')
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
local ZTensor = {}
local typename = "torch.ZCudaTensor"
local ctypename = "torch.CudaTensor"
local storageType = 'torch.ZCudaStorage'
local THZCudaTensor_new = C['THZCudaTensor_new']
local THZCudaTensor_newWithTensor = C['THZCudaTensor_newWithTensor']
local THZCudaTensor_newWithStorage = C['THZCudaTensor_newWithStorage']
local THZCudaTensor_newWithSize4d = C['THZCudaTensor_newWithSize4d']
local THZCudaTensor_newClone = C['THZCudaTensor_newClone']
local THZCudaTensor_free = C['THZCudaTensor_free']
local THZCudaTensor_newWithSize = C['THZCudaTensor_newWithSize']
local function free(t)
THZCudaTensor_free(cutorch._state,t)
end
local function wrapcdata(cdata)
-- print('wrapcdata')
return torch.ZCudaTensor().wrapcdata(cdata)
end
ZTensor.__new = argcheck{
nonamed=true,
call =
function()
local self = wrapcdata(THZCudaTensor_new(cutorch._state))
-- ffi.gc(self, THZCudaTensor_free)
return self
end
}
ZTensor.__new = argcheck{
{name='storage', type=storageType},
{name='storageOffset', type='number', default=1},
{name='size', type='table', opt=true},
{name='stride', type='table', opt=true},
nonamed=true,
overload = ZTensor.__new,
call =
function(storage, storageOffset, size, stride)
if size then
size = torch.LongStorage(size):cdata()
end
if stride then
stride = torch.LongStorage(stride):cdata()
end
local self = wrapcdata(THZCudaTensor_newWithStorage(cutorch._state,storage:cdata(), storageOffset-1, size, stride))
-- ffi.gc(self, free)
return self
end
}
ZTensor.__new = argcheck{
{name='dim1', type='number'},
{name='dim2', type='number', default=0},
{name='dim3', type='number', default=0},
{name='dim4', type='number', default=0},
nonamed=true,
overload = ZTensor.__new,
call =
function(dim1, dim2, dim3, dim4)
local self = wrapcdata(THZCudaTensor_newWithSize4d(cutorch._state,dim1, dim2, dim3, dim4))
-- print(type(self))
-- print(self)
-- ffi.gc(self, free)
return self
end
}
ZTensor.__new = argcheck{
{name='dimt', type='table'},
nonamed=true,
overload = ZTensor.__new,
call =
function(dimt)
local dim1 = dimt[1] or 0
local dim2 = dimt[2] or 0
local dim3 = dimt[3] or 0
local dim4 = dimt[4] or 0
-- pprint(dimt)
local self = wrapcdata(THZCudaTensor_newWithSize4d(cutorch._state,dim1, dim2, dim3, dim4))
-- self = torch.ZCudaTensor(self)
-- print(type(self))
-- print(self)
-- ffi.gc(self, free)
return self
end
}
ZTensor.__new = argcheck{
{name='size', type='torch.LongStorage'},
nonamed=true,
overload = ZTensor.__new,
call =
function(size)
local self = wrapcdata(THZCudaTensor_newWithSize(cutorch._state,size:cdata(), nil))
-- ffi.gc(self, free)
return self
end
}
ZTensor.__new = argcheck{
{name='tensor', type=typename},
nonamed=true,
overload = ZTensor.__new,
call =
function(tensor)
-- print('new with tensor')
local self = wrapcdata(THZCudaTensor_newWithTensor(cutorch._state,tensor:cdata()))
-- ffi.gc(self, free)
return self
end
}
ZTensor.newClone = argcheck{
{name='tensor', type=typename},
nonamed=true,
call =
function(tensor)
local self = wrapcdata(THZCudaTensor_newClone(cutorch._state,tensor:cdata()))
-- ffi.gc(self, free)
return self
end
}
ZTensor.__call = ZTensor.__new
ZTensor.new = ZTensor.__new
ZTensor.copyIm = argcheck{
nonamed=true,
{name="dst", type=typename},
{name="src", type=ctypename},
call = function(dst, src)
THZCudaTensor_copyIm(cutorch._state,dst:cdata(), src:cdata())
return dst
end
}
ZTensor.copyRe = argcheck{
nonamed=true,
{name="dst", type=typename},
{name="src", type=ctypename},
call = function(dst, src)
THZCudaTensor_copyRe(cutorch._state,dst:cdata(), src:cdata())
return dst
end
}
ZTensor.fillIm = argcheck{
nonamed=true,
{name="src", type=typename},
{name="v", type="number"},
call = function( src, v)
THZCudaTensor_fillim(cutorch._state, src:cdata(),v)
return src
end
}
ZTensor.fillRe = argcheck{
nonamed=true,
{name="src", type=typename},
{name="v", type="number"},
call = function( src, v)
THZCudaTensor_fillre(cutorch._state, src:cdata(),v)
return src
end
}
ZTensor.abs = argcheck{
nonamed=true,
{name="src", type=typename},
call = function(src)
local dst = torch.CudaTensor()
THZCudaTensor_abs(cutorch._state,dst:cdata(), src:cdata())
return dst
end
}
ZTensor.abs = argcheck{
nonamed=true,
{name="dst", type=typename},
{name="src", type=typename},
overload=ZTensor.abs,
call = function(dst, src)
THZCudaTensor_zabs(cutorch._state,dst:cdata(), src:cdata())
return dst
end
}
ZTensor.abs = argcheck{
nonamed=true,
{name="dst", type=ctypename},
{name="src", type=typename},
overload=ZTensor.abs,
call = function(dst, src)
THZCudaTensor_abs(cutorch._state,dst:cdata(), src:cdata())
return dst
end
}
ZTensor.arg = argcheck{
nonamed=true,
{name="src", type=typename},
call = function(src)
local dst = torch.CudaTensor()
THZCudaTensor_arg(cutorch._state,dst:cdata(), src:cdata())
return dst
end
}
ZTensor.arg = argcheck{
nonamed=true,
{name="dst", type=typename},
{name="src", type=typename},
overload=ZTensor.arg,
call = function(dst, src)
THZCudaTensor_zarg(cutorch._state,dst:cdata(), src:cdata())
return dst
end
}
ZTensor.arg = argcheck{
nonamed=true,
{name="dst", type=ctypename},
{name="src", type=typename},
overload=ZTensor.arg,
call = function(dst, src)
THZCudaTensor_arg(cutorch._state,dst:cdata(), src:cdata())
return dst
end
}
ZTensor.re = argcheck{
nonamed=true,
{name="src", type=typename},
call = function(src)
local dst = torch.CudaTensor()
THZCudaTensor_real(cutorch._state,dst:cdata(), src:cdata())
return dst
end
}
ZTensor.re = argcheck{
nonamed=true,
{name="dst", type=typename},
{name="src", type=typename},
overload=ZTensor.re,
call = function(dst, src)
THZCudaTensor_zreal(cutorch._state,dst:cdata(), src:cdata())
return dst
end
}
ZTensor.re = argcheck{
nonamed=true,
{name="dst", type=ctypename},
{name="src", type=typename},
overload=ZTensor.re,
call = function(dst, src)
THZCudaTensor_real(cutorch._state,dst:cdata(), src:cdata())
return dst
end
}
ZTensor.sign = argcheck{
nonamed=true,
{name="src", type=typename},
call = function(src)
local dst = torch.CudaTensor()
THZCudaTensor_sign(cutorch._state,dst:cdata(), src:cdata())
return dst
end
}
ZTensor.im = argcheck{
nonamed=true,
{name="src", type=typename},
call = function(src)
local dst = torch.CudaTensor()
THZCudaTensor_imag(cutorch._state,dst:cdata(), src:cdata())
return dst
end
}
ZTensor.im = argcheck{
nonamed=true,
{name="dst", type=typename},
{name="src", type=typename},
overload=ZTensor.im,
call = function(dst, src)
THZCudaTensor_zimag(cutorch._state,dst:cdata(), src:cdata())
return dst
end
}
ZTensor.im = argcheck{
nonamed=true,
{name="dst", type=ctypename},
{name="src", type=typename},
overload=ZTensor.im,
call = function(dst, src)
THZCudaTensor_imag(cutorch._state,dst:cdata(), src:cdata())
return dst
end
}
ZTensor.norm = argcheck{
nonamed=true,
{name="dst", type=ctypename},
{name="src", type=typename},
overload=ZTensor.norm,
call = function(dst, src)
THZCudaTensor_norm(cutorch._state,dst:cdata(), src:cdata())
return dst
end
}
ZTensor.norm = argcheck{
nonamed=true,
{name="dst", type=typename},
{name="src", type=typename, opt=true},
overload=ZTensor.norm,
call = function(dst, src)
src = src or dst
THZCudaTensor_znorm(cutorch._state,dst:cdata(), src:cdata())
return dst
end
}
ZTensor.normall = argcheck{
nonamed=true,
{name="self", type=typename},
{name="value", type="number", default = 2},
call = function(self, value)
return THZCudaTensor_normall(cutorch._state,self:cdata(), value)
end
}
ZTensor.normDim = argcheck{
nonamed=true,
{name="self", type=typename},
{name="src", type=typename},
{name="value", type="number"},
{name="dimension", type="number"},
call = function(self, src, value, dimension)
THZCudaTensor_normDim(cutorch._state,self:cdata(), src:cdata(), value, dimension)
return self
end
}
ZTensor.polar = argcheck{
nonamed=true,
{name="self", type=typename},
{name="src1", type=ctypename},
{name="src2", type=ctypename},
call = function(self, src1, src2)
THZCudaTensor_polar(cutorch._state,self:cdata(), src1:cdata(), src2:cdata())
return self
end
}
ZTensor.polar = argcheck{
nonamed=true,
{name="self", type=typename},
{name="src1", type="number"},
{name="src2", type=ctypename},
overload=ZTensor.polar,
call = function(self, src1, src2)
local s1 = src2:clone():fill(src1)
THZCudaTensor_polar(cutorch._state,self:cdata(), s1:cdata(), src2:cdata())
return self
end
}
ZTensor.polar = argcheck{
nonamed=true,
{name="self", type=typename},
{name="src1", type=ctypename},
{name="src2", type="number"},
overload=ZTensor.polar,
call = function(self, src1, src2)
local s2 = src1:clone():fill(src2)
THZCudaTensor_polar(cutorch._state,self:cdata(), src1:cdata(), s2:cdata())
return self
end
}
ZTensor.cim = argcheck{
nonamed=true,
{name="self", type=typename},
{name="src2", type=ctypename},
call = function(self, src2)
THZCudaTensor_cim(cutorch._state,self:cdata(), self:cdata(), src2:cdata())
return self
end
}
ZTensor.cim = argcheck{
nonamed=true,
{name="self", type=typename},
{name="src1", type=typename},
{name="src2", type=ctypename},
overload=ZTensor.cim,
call = function(self, src1, src2)
THZCudaTensor_cim(cutorch._state,self:cdata(), src1:cdata(), src2:cdata())
return self
end
}
ZTensor.cre = argcheck{
nonamed=true,
{name="self", type=typename},
{name="src2", type=ctypename},
call = function(self, src2)
THZCudaTensor_cre(cutorch._state,self:cdata(), self:cdata(), src2:cdata())
return self
end
}
ZTensor.cre = argcheck{
nonamed=true,
{name="self", type=typename},
{name="src1", type=typename},
{name="src2", type=ctypename},
overload=ZTensor.cre,
call = function(self, src1, src2)
THZCudaTensor_cre(cutorch._state,self:cdata(), src1:cdata(), src2:cdata())
return self
end
}
-- local THZCudaTensor_fft = C['THZCudaTensor_fft']
-- local THZCudaTensor_fftBatched = C['THZCudaTensor_fftBatched']
-- local THZCudaTensor_ifft = C['THZCudaTensor_ifft']
-- local THZCudaTensor_ifftBatched = C['THZCudaTensor_ifftBatched']
-- local THZCudaTensor_ifftU = C['THZCudaTensor_ifftU']
-- local THZCudaTensor_ifftBatchedU = C['THZCudaTensor_ifftBatchedU']
-- local THZCudaTensor_fftShiftedInplace = C['THZCudaTensor_fftShiftedInplace']
-- local THZCudaTensor_fftShifted = C['THZCudaTensor_fftShifted']
-- local THZCudaTensor_fftShiftInplace = C['THZCudaTensor_fftShiftInplace']
-- local THZCudaTensor_fftShift = C['THZCudaTensor_fftShift']
-- local THZCudaTensor_ifftShiftInplace = C['THZCudaTensor_ifftShiftInplace']
-- local THZCudaTensor_ifftShift = C['THZCudaTensor_ifftShift']
ZTensor.dot = argcheck{
nonamed=true,
{name="dst", type=typename},
{name="src1", type=typename, opt=true},
call =
function(dst, src1)
src1 = src1 or dst
local result = THZCudaTensor_dot(cutorch._state,src1:cdata(), dst:cdata())
-- print('in dot ',result)
return result
end
}
ZTensor.fft = argcheck{
nonamed=true,
{name="dst", type=typename},
{name="src1", type=typename, opt=true},
call =
function(dst, src1)
src1 = src1 or dst
THZCudaTensor_fft(cutorch._state,src1:cdata(), dst:cdata())
dst:div(math.sqrt(dst:nElement()))
return dst
end
}
ZTensor.fftshift = argcheck{
nonamed=true,
{name="dst", type=typename},
{name="src1", type=typename, opt=true},
call =
function(dst, src1)
if src1 then
dst:copy(src1)
end
local ndim = dst:dim()
local t = torch.getdefaulttensortype()
torch.setdefaulttensortype('torch.FloatTensor')
local axes = torch.linspace(1,ndim,ndim)
torch.setdefaulttensortype(t)
for _, k in pairs(axes:totable()) do
local n = dst:size(k)
local p2 = math.floor((n+1)/2)
local half1 = {p2+1,n}
local half2 = {1,p2}
-- pprint(half1)
-- pprint(half2)
local indextable = {{},{}}
-- pprint(indextable)
for i=1,ndim do
-- print(k .. '_' .. i)
if i ~= k then
indextable[1][i] = {}
indextable[2][i] = {}
-- pprint(indextable)
else
indextable[1][i] = half1
indextable[2][i] = half2
-- pprint(indextable)
end
end
-- pprint(indextable[1])
-- pprint(indextable[2])
local tmp = dst[indextable[1]]:clone()
-- pprint(tmp)
-- pprint(dst)
dst[indextable[1]]:copy(dst[indextable[2]])
dst[indextable[2]]:copy(tmp)
end
return dst
end
}
ZTensor.ifftshift = argcheck{
nonamed=true,
{name="dst", type=typename},
{name="src1", type=typename, opt=true},
call =
function(dst, src1)
if src1 then
dst:copy(src1)
end
local ndim = dst:dim()
local t = torch.getdefaulttensortype()
torch.setdefaulttensortype('torch.FloatTensor')
local axes = torch.linspace(1,ndim,ndim)
torch.setdefaulttensortype(t)
for _, k in pairs(axes:totable()) do
local n = dst:size(k)
local p2 = math.floor(n-(n+1)/2)
local half1 = {p2+1,n}
local half2 = {1,p2}
-- pprint(half1)
-- pprint(half2)
local indextable = {{},{}}
-- pprint(indextable)
for i=1,ndim do
-- print(k .. '_' .. i)
if i ~= k then
indextable[1][i] = {}
indextable[2][i] = {}
-- pprint(indextable)
else
indextable[1][i] = half1
indextable[2][i] = half2
-- pprint(indextable)
end
end
-- pprint(indextable[1])
-- pprint(indextable[2])
local tmp = dst[indextable[1]]:clone()
-- pprint(tmp)
-- pprint(dst)
dst[indextable[1]]:copy(dst[indextable[2]])
dst[indextable[2]]:copy(tmp)
end
return dst
end
}
ZTensor.fftBatched = argcheck{
nonamed=true,
{name="dst", type=typename, opt=true},
{name="src1", type=typename},
call =
function(dst, src1)
dst = dst or src1
THZCudaTensor_fftBatched(cutorch._state,src1:cdata(), dst:cdata())
dst:div(math.sqrt(dst[1]:nElement()))
return dst
end
}
ZTensor.ifft = argcheck{
nonamed=true,
{name="dst", type=typename, opt=true},
{name="src1", type=typename},
call =
function(dst, src1)
dst = dst or src1
THZCudaTensor_ifftU(cutorch._state,src1:cdata(), dst:cdata())
dst:div(math.sqrt(dst:nElement()))
return dst
end
}
ZTensor.ifftBatched = argcheck{
nonamed=true,
{name="dst", type=typename, opt=true},
{name="src1", type=typename},
call =
function(dst, src1)
dst = dst or src1
THZCudaTensor_ifftBatchedU(cutorch._state,src1:cdata(), dst:cdata())
dst:div(math.sqrt(dst[1]:nElement()))
return dst
end
}
ZTensor.ifftU = argcheck{
nonamed=true,
{name="dst", type=typename, opt=true},
{name="src1", type=typename},
call =
function(dst, src1)
dst = dst or src1
THZCudaTensor_ifftU(cutorch._state,src1:cdata(), dst:cdata())
return dst
end
}
ZTensor.ifftBatchedU = argcheck{
nonamed=true,
{name="dst", type=typename, opt=true},
{name="src1", type=typename},
call =
function(dst, src1)
dst = dst or src1
THZCudaTensor_ifftBatchedU(cutorch._state,src1:cdata(), dst:cdata())
return dst
end
}
ZTensor.copy = argcheck{
nonamed=true,
name = "copy",
{name="dst", type=typename},
{name="src", type=typename},
call =
function(dst, src)
-- print('copy THZCudaTensor_copy')
THZCudaTensor_copy(cutorch._state,dst:cdata(), src:cdata())
return dst
end
}
ZTensor.copy = argcheck{
nonamed=true,
name = "copy",
{name="dst", type=typename},
{name="src", type='torch.ByteTensor'},
overload=ZTensor.copy,
call =
function(dst, src)
THZCudaTensor_copyByte(cutorch._state,dst:cdata(), src:cdata())
return dst
end
}
ZTensor.copy = argcheck{
nonamed=true,
name = "copy",
{name="dst", type=typename},
{name="src", type='torch.CharTensor'},
overload=ZTensor.copy,
call =
function(dst, src)
THZCudaTensor_copyChar(cutorch._state,dst:cdata(), src:cdata())
return dst
end
}
ZTensor.copy = argcheck{
nonamed=true,
name = "copy",
{name="dst", type=typename},
{name="src", type='torch.ShortTensor'},
overload=ZTensor.copy,
call =
function(dst, src)
THZCudaTensor_copyShort(cutorch._state,dst:cdata(), src:cdata())
return dst
end
}
ZTensor.copy = argcheck{
nonamed=true,
name = "copy",
{name="dst", type=typename},
{name="src", type='torch.IntTensor'},
overload=ZTensor.copy,
call =
function(dst, src)
THZCudaTensor_copyInt(cutorch._state,dst:cdata(), src:cdata())
return dst
end
}
ZTensor.copy = argcheck{
nonamed=true,
name = "copy",
{name="dst", type=typename},
{name="src", type='torch.LongTensor'},
overload=ZTensor.copy,
call =
function(dst, src)
-- print('copy 5')
THZCudaTensor_copyLong(cutorch._state,dst:cdata(), src:cdata())
return dst
end
}
ZTensor.copy = argcheck{
nonamed=true,
name = "copy",
{name="dst", type=typename},
{name="src", type='torch.FloatTensor'},
overload=ZTensor.copy,
call =
function(dst, src)
-- print('copy 4')
THZCudaTensor_copyFloat(cutorch._state,dst:cdata(), src:cdata())
return dst
end
}
ZTensor.copy = argcheck{
nonamed=true,
name = "copy",
{name="dst", type=typename},
{name="src", type='torch.ZFloatTensor'},
overload=ZTensor.copy,
call =
function(dst, src)
-- print('copy zfloat')
THZCudaTensor_copyZFloat(cutorch._state,dst:cdata(), src)
return dst
end
}
ZTensor.copy = argcheck{
nonamed=true,
name = "copy",
{name="dst", type=typename},
{name="src", type='torch.DoubleTensor'},
overload=ZTensor.copy,
call =
function(dst, src)
-- print('copy 3')
THZCudaTensor_copyDouble(dst:cdata(), src:cdata())
return dst
end
}
ZTensor.mul = argcheck{
nonamed=true,
{name="dst", type=typename, opt=true},
{name="src", type=typename},
{name="value", type="number"},
call =
function(dst, src, value)
dst = dst or src
THZCudaTensor_mul(cutorch._state, dst:cdata(), src:cdata(), value)
return dst
end
}
ZTensor.mul = argcheck{
nonamed=true,
{name="dst", type=typename, opt=true},
{name="src", type=typename},
{name="value", type="cdata", check=ztorch.isComplex},
overload=ZTensor.mul,
call =
function(dst, src, value)
dst = dst or src
THZCudaTensor_mul(cutorch._state, dst:cdata(), src:cdata(), value)
return dst
end
}
ZTensor.add = argcheck{
nonamed=true,
{name="dst", type=typename, opt=true},
{name="src1", type=typename},
{name="v", type='number'},
call =
function(dst, src1, v)
dst = dst or src1
THZCudaTensor_add(cutorch._state,dst:cdata(), src1:cdata(),v)
return dst
end
}
ZTensor.add = argcheck{
nonamed=true,
{name="dst", type=typename, opt=true},
{name="src1", type=typename},
{name="v", type="cdata", check=ztorch.isComplex},
call =
function(dst, src1, v)
dst = dst or src1
THZCudaTensor_add(cutorch._state,dst:cdata(), src1:cdata(),v)
return dst
end
}
ZTensor.maskedFill = argcheck{
nonamed=true,
{name="dst", type=typename, opt=true},
{name="mask", type=ctypename},
{name="v", type="cdata", check=ztorch.isComplex},
call =
function(dst, mask, v)
THZCudaTensor_maskedFill(cutorch._state,dst:cdata(), mask:cdata(),v)
return dst
end
}
ZTensor.cmul = argcheck{
nonamed=true,
{name="dst", type=typename, opt=true},
{name="src1", type=typename},
{name="src2", type=typename},
call =
function(dst, src1, src2)
dst = dst or src1
THZCudaTensor_cmul(cutorch._state,dst:cdata(), src1:cdata(), src2:cdata())
return dst
end
}
ZTensor.cmul = argcheck{
nonamed=true,
{name="dst", type=typename, opt=true},
{name="src1", type=typename},
{name="src2", type=ctypename},
overload=ZTensor.cmul,
call =
function(dst, src1, src2)
dst = dst or src1
THZCudaTensor_cmulZR(cutorch._state,dst:cdata(), src1:cdata(), src2:cdata())
return dst
end
}
ZTensor.cdiv = argcheck{
nonamed=true,
{name="dst", type=typename, opt=true},
{name="src1", type=typename},
{name="src2", type=typename},
call =
function(dst, src1, src2)
dst = dst or src1
THZCudaTensor_cdiv(cutorch._state,dst:cdata(), src1:cdata(), src2:cdata())
return dst
end
}
ZTensor.cdiv = argcheck{
nonamed=true,
{name="dst", type=typename, opt=true},
{name="src1", type=typename},
{name="src2", type=ctypename},
overload=ZTensor.cdiv,
call =
function(dst, src1, src2)
dst = dst or src1
THZCudaTensor_cdivZR(cutorch._state,dst:cdata(), src1:cdata(), src2:cdata())
return dst
end
}
ZTensor.add = argcheck{
nonamed=true,
{name="dst", type=typename, opt=true},