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Tensor.lua
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Tensor.lua
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--
-- Copyright (c) 2015, 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 argcheck = require 'argcheck'
local C = require 'ztorch.THZ'
local torch = require 'torch'
local ztorch = require 'ztorch.env'
local ffi=require 'ffi'
local display=require 'ztorch.display'
for _,Real in ipairs{'Float', 'Double'} do
local storageType = 'torch.Z' .. Real .. 'Storage'
local typename = 'torch.Z' .. Real .. 'Tensor'
local Tensor = torch[Real .. 'Tensor']
local THZTensor = 'THZ' .. Real .. 'Tensor'
local THZTensor_Real_abs = C[THZTensor .. '_' .. Real .. '_abs']
local THZTensor_Real_arg = C[THZTensor .. '_' .. Real .. '_arg']
local THZTensor_Real_im = C[THZTensor .. '_' .. Real .. '_im']
local THZTensor_Real_re = C[THZTensor .. '_' .. Real .. '_re']
local THZTensor_zabs = C[THZTensor .. '_zabs']
local THZTensor_zarg = C[THZTensor .. '_zarg']
local THZTensor_zim = C[THZTensor .. '_zim']
local THZTensor_zre = C[THZTensor .. '_zre']
local THZTensor_add = C[THZTensor .. '_add']
local THZTensor_addcdiv = C[THZTensor .. '_addcdiv']
local THZTensor_addcmul = C[THZTensor .. '_addcmul']
local THZTensor_cadd = C[THZTensor .. '_cadd']
local THZTensor_cat = C[THZTensor .. '_cat']
local THZTensor_cdiv = C[THZTensor .. '_cdiv']
local THZTensor_cmul = C[THZTensor .. '_cmul']
local THZTensor_conv2Dcmul = C[THZTensor .. '_conv2Dcmul']
local THZTensor_conv2Dmul = C[THZTensor .. '_conv2Dmul']
local THZTensor_conv2Dmv = C[THZTensor .. '_conv2Dmv']
local THZTensor_conv3Dcmul = C[THZTensor .. '_conv3Dcmul']
local THZTensor_conv3Dmul = C[THZTensor .. '_conv3Dmul']
local THZTensor_conv3Dmv = C[THZTensor .. '_conv3Dmv']
local THZTensor_copy = C[THZTensor .. '_copy']
local THZTensor_copyByte = C[THZTensor .. '_copyByte']
local THZTensor_copyChar = C[THZTensor .. '_copyChar']
local THZTensor_copyDouble = C[THZTensor .. '_copyDouble']
local THZTensor_copyFloat = C[THZTensor .. '_copyFloat']
local THZTensor_copyInt = C[THZTensor .. '_copyInt']
local THZTensor_copyLong = C[THZTensor .. '_copyLong']
local THZTensor_copyShort = C[THZTensor .. '_copyShort']
local THZTensor_cross = C[THZTensor .. '_cross']
local THZTensor_cumprod = C[THZTensor .. '_cumprod']
local THZTensor_cumsum = C[THZTensor .. '_cumsum']
local THZTensor_diag = C[THZTensor .. '_diag']
local THZTensor_dist = C[THZTensor .. '_dist']
local THZTensor_div = C[THZTensor .. '_div']
local THZTensor_dot = C[THZTensor .. '_dot']
local THZTensor_fill = C[THZTensor .. '_fill']
local THZTensor_free = C[THZTensor .. '_free']
local THZTensor_geev = C[THZTensor .. '_geev']
local THZTensor_gels = C[THZTensor .. '_gels']
local THZTensor_gesv = C[THZTensor .. '_gesv']
local THZTensor_gesvd = C[THZTensor .. '_gesvd']
local THZTensor_isContiguous = C[THZTensor .. '_isContiguous']
local THZTensor_max = C[THZTensor .. '_max']
local THZTensor_maxall = C[THZTensor .. '_maxall']
local THZTensor_mean = C[THZTensor .. '_mean']
local THZTensor_meanall = C[THZTensor .. '_meanall']
local THZTensor_min = C[THZTensor .. '_min']
local THZTensor_minall = C[THZTensor .. '_minall']
local THZTensor_mul = C[THZTensor .. '_mul']
local THZTensor_nElement = C[THZTensor .. '_nElement']
local THZTensor_narrow = C[THZTensor .. '_narrow']
local THZTensor_new = C[THZTensor .. '_new']
local THZTensor_newClone = C[THZTensor .. '_newClone']
local THZTensor_newContiguous = C[THZTensor .. '_newContiguous']
local THZTensor_newNarrow = C[THZTensor .. '_newNarrow']
local THZTensor_newSelect = C[THZTensor .. '_newSelect']
local THZTensor_newTranspose = C[THZTensor .. '_newTranspose']
local THZTensor_newWithSize = C[THZTensor .. '_newWithSize']
local THZTensor_newWithSize4d = C[THZTensor .. '_newWithSize4d']
local THZTensor_newWithStorage = C[THZTensor .. '_newWithStorage']
local THZTensor_newWithTensor = C[THZTensor .. '_newWithTensor']
local THZTensor_norm = C[THZTensor .. '_norm']
local THZTensor_normall = C[THZTensor .. '_normall']
local THZTensor_pow = C[THZTensor .. '_pow']
local THZTensor_prod = C[THZTensor .. '_prod']
local THZTensor_reshape = C[THZTensor .. '_reshape']
local THZTensor_resize = C[THZTensor .. '_resize']
local THZTensor_resize4d = C[THZTensor .. '_resize4d']
local THZTensor_resizeAs = C[THZTensor .. '_resizeAs']
local THZTensor_select = C[THZTensor .. '_select']
local THZTensor_set = C[THZTensor .. '_set']
local THZTensor_setStorage = C[THZTensor .. '_setStorage']
local THZTensor_sort = C[THZTensor .. '_sort']
local THZTensor_squeeze = C[THZTensor .. '_squeeze']
local THZTensor_std = C[THZTensor .. '_std']
local THZTensor_stdall = C[THZTensor .. '_stdall']
local THZTensor_sum = C[THZTensor .. '_sum']
local THZTensor_sumall = C[THZTensor .. '_sumall']
local THZTensor_syev = C[THZTensor .. '_syev']
local THZTensor_trace = C[THZTensor .. '_trace']
local THZTensor_transpose = C[THZTensor .. '_transpose']
local THZTensor_tril = C[THZTensor .. '_tril']
local THZTensor_triu = C[THZTensor .. '_triu']
local THZTensor_unfold = C[THZTensor .. '_unfold']
local THZTensor_var = C[THZTensor .. '_var']
local THZTensor_varall = C[THZTensor .. '_varall']
local THZTensor_zero = C[THZTensor .. '_zero']
local THZStorage = 'THZ' .. Real .. 'Storage'
local THZStorage_free = C[THZStorage .. '_free']
local THZStorage_retain = C[THZStorage .. '_retain']
local ZTensor = {}
ZTensor.__new = argcheck{
nonamed=true,
call =
function()
local self = THZTensor_new()
ffi.gc(self, THZTensor_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 = THZTensor_newWithStorage(storage, storageOffset-1, size, stride)
ffi.gc(self, THZTensor_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 = THZTensor_newWithSize4d(dim1, dim2, dim3, dim4)
ffi.gc(self, THZTensor_free)
return self
end
}
ZTensor.__new = argcheck{
{name='size', type='torch.LongStorage'},
nonamed=true,
overload = ZTensor.__new,
call =
function(size)
local self = THZTensor_newWithSize(size:cdata(), nil)
ffi.gc(self, THZTensor_free)
return self
end
}
ZTensor.__new = argcheck{
{name='tensor', type=typename},
nonamed=true,
overload = ZTensor.__new,
call =
function(tensor)
local self = THZTensor_newWithTensor(tensor)
ffi.gc(self, THZTensor_free)
return self
end
}
ZTensor.new = ZTensor.__new
-- access methods
local NULL = (not jit) and ffi.C.NULL or nil
ZTensor.storage = argcheck{
{name='self', type=typename},
nonamed=true,
call =
function(self)
if self.__storage == NULL then
return nil
end
local storage = self.__storage[0]
THZStorage_retain(storage)
ffi.gc(storage, THZStorage_free)
return storage
end
}
ZTensor.storageOffset= argcheck{
{name='self', type=typename},
nonamed=true,
call =
function(self)
return tonumber(self.__storageOffset+1)
end
}
ZTensor.offset = ZTensor.storageOffset
ZTensor.nDimension = argcheck{
{name='self', type=typename},
nonamed=true,
call =
function(self)
return tonumber(self.__nDimension)
end
}
ZTensor.dim = ZTensor.nDimension
ZTensor.size = argcheck{
{name='self', type=typename},
{name='dim', type='number', opt=true},
nonamed=true,
call =
function(self, dim)
if dim then
assert(dim > 0 and dim <= self.__nDimension, 'out of range')
return tonumber(self.__size[dim-1])
else
local dim = tonumber(self.__nDimension)
local size = torch.LongStorage(dim)
ffi.copy(size:data(), self.__size, ffi.sizeof('long') * dim)
return size
end
end
}
ZTensor.stride = argcheck{
{name='self', type=typename},
{name='dim', type='number', opt=true},
nonamed=true,
call =
function(self, dim)
if dim then
assert(dim > 0 and dim <= self.__nDimension, 'out of range')
return tonumber(self.__stride[dim-1])
else
local dim = tonumber(self.__nDimension)
local stride = torch.LongStorage(dim)
ffi.copy(stride:data(), self.__stride, ffi.sizeof('long') * dim)
return stride
end
end
}
ZTensor.data = argcheck{
{name='self', type=typename},
nonamed=true,
call =
function(self)
if self.__storage then
return self.__storage.__data+self.__storageOffset
end
end
}
ZTensor.clone = argcheck{
{name='self', type=typename},
nonamed=true,
call =
function(self)
local tensor = THZTensor_newClone(self)
ffi.gc(tensor, THZTensor_free)
return tensor
end
}
ZTensor.contiguous = argcheck{
{name='self', type=typename},
nonamed=true,
call =
function(self)
local tensor = THZTensor_newContiguous(self)
ffi.gc(tensor, THZTensor_free)
return tensor
end
}
ZTensor.set = argcheck{
{name='self', type=typename},
{name='src', type=typename},
nonamed=true,
call =
function(self, src)
THZTensor_set(self, src)
return self
end
}
ZTensor.set = argcheck{
{name='self', type=typename},
{name='storage', type=storageType},
{name='storageOffset', type='number', default=1},
{name='size', type='torch.LongStorage', opt=true},
{name='stride', type='torch.LongStorage', opt=true},
nonamed=true,
overload = ZTensor.set,
call =
function(self, storage, storageOffset, size, stride)
local scdata, stdata
if size then scdata = size:cdata() end
if stride then stdata = stride:cdata() end
THZTensor_setStorage(self, storage, storageOffset-1, scdata, stdata)
return self
end
}
ZTensor.resize = argcheck{
{name='self', type=typename},
{name='size', type='table'},
{name='stride', type='table', opt=true},
nonamed=true,
call =
function(self, size, stride)
local dim = #size
assert(not stride or (#stride == dim), 'inconsistent size/stride sizes')
size = torch.LongStorage(size)
local stridecdata
if stride then
stride = torch.LongStorage(stride)
stridecdata = stride:cdata()
end
THZTensor_resize(self, size:cdata(), stridecdata)
return self
end
}
ZTensor.resize = argcheck{
{name='self', type=typename},
{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.resize,
call =
function(self, dim1, dim2, dim3, dim4)
THZTensor_resize4d(self, dim1, dim2, dim3, dim4)
return self
end
}
ZTensor.resize = argcheck{
{name='self', type=typename},
{name='size', type='torch.LongStorage'},
{name='stride', type='torch.LongStorage', opt=true},
nonamed=true,
overload = ZTensor.resize,
call =
function(self, size, stride)
if stride then stride = stride:cdata() end
THZTensor_resize(self, size:cdata(), stride)
return self
end
}
ZTensor.resizeAs = argcheck{
{name='self', type=typename},
{name='src', type=typename},
nonamed=true,
call =
function(self, src)
THZTensor_resizeAs(self, src)
return self
end
}
ZTensor.fill = argcheck{
nonamed=true,
{name="dst", type=typename},
{name="value", type="number"},
call =
function(dst, value)
THZTensor_fill(dst, value)
return dst
end
}
ZTensor.fill = argcheck{
nonamed=true,
{name="self", type=typename},
{name="value", type="cdata", check=ztorch.isComplex},
overload=ZTensor.fill,
call = function(dst, value)
THZTensor_fill(dst, value)
return dst
end
}
ZTensor.mean = argcheck{
nonamed=true,
{name="src", type=typename},
call =
function(src)
return THZTensor_meanall(src)
end
}
ZTensor.mean = argcheck{
nonamed=true,
name = "mean",
{name="dst", type=typename, opt=true},
{name="src", type=typename},
{name="dim", type="number"},
overload=ZTensor.mean,
call =
function(dst, src, dim)
dst = dst or src
THZTensor_mean(dst, src, dim-1)
return dst
end
}
ZTensor.std = argcheck{
nonamed=true,
{name="src", type=typename},
call =
function(src)
return THZTensor_stdall(src)
end
}
ZTensor.std = argcheck{
nonamed=true,
name = "std",
{name="dst", type=typename, opt=true},
{name="src", type=typename},
{name="dim", type="number"},
{name="flag", type="boolean", default=false},
overload=ZTensor.std,
call =
function(dst, src, dim, flag)
dst = dst or src
THZTensor_std(dst, src, dim-1, flag and 1 or 0)
return dst
end
}
ZTensor.var = argcheck{
nonamed=true,
{name="src", type=typename},
call =
function(src)
return THZTensor_varall(src)
end
}
ZTensor.var = argcheck{
nonamed=true,
{name="dst", type=typename, opt=true},
{name="src", type=typename},
{name="dim", type="number"},
{name="flag", type="boolean", default=false},
overload=ZTensor.var,
call =
function(dst, src, dim, flag)
dst = dst or src
THZTensor_var(dst, src, dim-1, flag and 1 or 0)
return dst
end
}
ZTensor.norm = argcheck{
nonamed=true,
{name="src", type=typename},
{name="n", type="number", default=2},
call = THZTensor_normall
}
ZTensor.norm = argcheck{
nonamed=true,
{name="dst", type=typename},
{name="src", type=typename, opt=true},
{name="n", type="number"},
{name="dim", type="number"},
overload = ZTensor.norm,
call =
function(dst, src, n, dim)
dst = dst or src
THZTensor_norm(dst, src, n, dim-1)
return dst
end
}
ZTensor.dist = argcheck{
nonamed=true,
name = "dist",
{name="dst", type=typename},
{name="src", type=typename},
{name="n", type="number", default=2},
call = THZTensor_dist
}
ZTensor.re = argcheck{
nonamed=true,
{name="src", type=typename},
call = function(src)
local dst = Tensor.new()
THZTensor_Real_re(dst:cdata(), src)
return dst
end
}
ZTensor.re = argcheck{
nonamed=true,
{name="dst", type=typename},
{name="src", type=typename},
overload=ZTensor.re,
call = function(dst, src)
THZTensor_zre(dst, src)
return dst
end
}
ZTensor.im = argcheck{
nonamed=true,
{name="src", type=typename},
call = function(src)
local dst = Tensor.new()
THZTensor_Real_im(dst:cdata(), src)
return dst
end
}
ZTensor.im = argcheck{
nonamed=true,
{name="dst", type=typename},
{name="src", type=typename},
overload=ZTensor.im,
call = function(dst, src)
THZTensor_zim(dst, src)
return dst
end
}
-- Add re and im functions to torch.FloatTensor and torch.DoubleTensor
for _,BaseReal in ipairs{'Float', 'Double'} do
local basename = 'torch.' .. BaseReal .. 'Tensor'
local metatable = torch.getmetatable(basename)
for _,funcname in pairs{'re','im'} do
local func = C[THZTensor .. '_' .. BaseReal .. '_' .. funcname]
rawset(metatable, funcname, argcheck{
{name='dst', type=basename},
{name='src', type=typename},
nonamed=true,
overload = rawget(metatable, funcname),
call =
function(dst, src)
func(dst:cdata(), src)
return dst
end
})
end
end
ZTensor.abs = argcheck{
nonamed=true,
{name="src", type=typename},
call = function(src)
local dst = Tensor.new()
THZTensor_Real_abs(dst:cdata(), src)
return dst
end
}
ZTensor.abs = argcheck{
nonamed=true,
{name="dst", type=typename},
{name="src", type=typename},
overload=ZTensor.abs,
call = function(dst, src)
THZTensor_zabs(dst, src)
return dst
end
}
ZTensor.arg = argcheck{
nonamed=true,
{name="src", type=typename},
call = function(src)
local dst = Tensor.new()
THZTensor_Real_arg(dst:cdata(), src)
return dst
end
}
ZTensor.arg = argcheck{
nonamed=true,
{name="dst", type=typename},
{name="src", type=typename},
overload=ZTensor.arg,
call = function(dst, src)
THZTensor_zarg(dst, src)
return dst
end
}
for _,name in ipairs{'log', 'exp', 'cos', 'acos', 'cosh', 'sin', 'asin',
'sinh', 'tan', 'atan', 'tanh', 'sqrt',
'conj', 'proj'} do
local func = C['THZ' .. Real .. 'Tensor_' .. name]
ZTensor[name] = argcheck{
nonamed=true,
name = name,
{name="dst", type=typename, opt=true},
{name="src", type=typename},
call =
function(dst, src)
dst = dst or src
func(dst, src)
return dst
end
}
end
ZTensor.pow = argcheck{
nonamed=true,
name = "pow",
{name="dst", type=typename, opt=true},
{name="src", type=typename},
{name="value", type="number"},
call =
function(dst, src, value)
dst = dst or src
THZTensor_pow(dst, src)
return dst
end
}
ZTensor.narrow = argcheck{
{name='self', type=typename},
{name='src', type=typename, opt=true},
{name='dim', type='number'},
{name='idx', type='number'},
{name='size', type='number'},
nonamed=true,
call =
function(self, src, dim, idx, size)
if src then
THZTensor_narrow(self, src, dim-1, idx-1, size)
return self
else
local tensor = THZTensor_newNarrow(self, dim-1, idx-1, size)
ffi.gc(tensor, THZTensor_free)
return tensor
end
end
}
ZTensor.select = argcheck{
nonamed=true,
{name='self', type=typename},
{name='src', type=typename, opt=true},
{name='dim', type='number'},
{name='idx', type='number'},
call =
function(self, src, dim, idx)
if src then
THZTensor_select(self, src, dim-1, idx-1)
return self
else
local tensor = THZTensor_newSelect(self, dim-1, idx-1)
ffi.gc(tensor, THZTensor_free)
return tensor
end
end
}
ZTensor.t = argcheck{
nonamed=true,
{name='self', type=typename},
{name='src', type=typename, opt=true},
call =
function(self, src)
if src then
assert(src.__nDimension == 2, 'tensor to be transposed must be 2D')
THZTensor_transpose(self, src, 0, 1)
return self
else
assert(self.__nDimension == 2, 'tensor to be transposed must be 2D')
local tensor = THZTensor_newTranspose(self, 0, 1)
ffi.gc(tensor, THZTensor_free)
return tensor
end
end
}
ZTensor.transpose = argcheck{
nonamed=true,
{name='self', type=typename},
{name='src', type=typename, opt=true},
{name='dim1', type='number'},
{name='dim2', type='number'},
call =
function(self, src, dim1, dim2)
if src then
THZTensor_transpose(self, src, dim1-1, dim2-1)
return self
else
local tensor = THZTensor_newTranspose(self, dim1-1, dim2-1)
ffi.gc(tensor, THZTensor_free)
return tensor
end
end
}
ZTensor.unfold = argcheck{
nonamed=true,
{name='self', type=typename},
{name='src', type=typename, opt=true},
{name='dim', type='number'},
{name='size', type='number'},
{name='step', type='number'},
call =
function(self, src, dim, size, step)
if src then
THZTensor_unfold(self, src, dim-1, size, step)
return self
else
local tensor = THZTensor_newTranspose(self, src, dim-1, size, step)
ffi.gc(tensor, THZTensor_free)
return tensor
end
end
}
ZTensor.squeeze = argcheck{
nonamed=true,
{name='self', type=typename},
{name='src', type=typename, opt=true},
call =
function(self, src)
local dst = src and self or ZTensor.new()
src = src or self
if src.__nDimension == 0 then
return
elseif src.__nDimension == 1 and src:size(1) == 1 then
return src:data()[0]
else
THZTensor_squeeze(dst, src)
return dst
end
end
}
ZTensor.isContiguous = argcheck{
nonamed=true,
{name='self', type=typename},
call =
function(self)
return THZTensor_isContiguous(self) == 1
end
}
ZTensor.nElement = argcheck{
nonamed=true,
{name='self', type=typename},
call =
function(self)
return tonumber(THZTensor_nElement(self))
end
}
ZTensor.zero = argcheck{
nonamed=true,
{name="dst", type=typename},
call =
function(dst)
THZTensor_zero(dst)
return dst
end
}
ZTensor.dot = argcheck{
nonamed=true,
{name="src1", type=typename},
{name="src2", type=typename},
call =
function(src1, src2)
return THZTensor_dot(src1, src2)
end
}
ZTensor.min = argcheck{
nonamed=true,
{name="src", type=typename},
call =
function(src)
return tonumber(THZTensor_minall(src))
end
}
ZTensor.min = argcheck {
nonamed=true,
{name="dst", type=typename, opt=true},
{name="idx", type="torch.LongTensor", opt=true},
{name="src", type=typename},
{name="dim", type="number"},
overload=ZTensor.min,
call =
function(dst, idx, src, dim)
dst = dst or src
idx = idx or torch.LongTensor()
THZTensor_min(dst, idx, src, dim-1)
idx:add(1)
return dst, idx
end
}
ZTensor.max = argcheck{
nonamed=true,
{name="src", type=typename},
call =
function(src)
return tonumber(THZTensor_maxall(src))
end
}
ZTensor.max = argcheck {
nonamed=true,
{name="dst", type=typename, opt=true},
{name="idx", type="torch.LongTensor", opt=true},
{name="src", type=typename},
{name="dim", type="number"},
overload=ZTensor.max,
call =
function(dst, idx, src, dim)
dst = dst or src
idx = idx or torch.LongTensor()
THZTensor_max(dst, idx, src, dim-1)
idx:add(1)
return dst, idx
end
}
ZTensor.sum = argcheck{
nonamed=true,
{name="src", type=typename},
call =
function(src)
return THZTensor_sumall(src)
end
}
ZTensor.sum = argcheck {
nonamed=true,
{name="dst", type=typename, opt=true},
{name="src", type=typename},
{name="dim", type="number"},
overload=ZTensor.sum,
call =
function(dst, src, dim)
dst = dst or src
THZTensor_sum(dst, src, dim-1)
return dst
end
}
ZTensor.add = 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
THZTensor_add(dst, src, value)
return dst
end
}
ZTensor.add = argcheck{
nonamed=true,
{name="dst", type=typename, opt=true},
{name="src", type=typename},
{name="value", type="cdata", check=ztorch.isComplex},
call =
function(dst, src, value)
dst = dst or src
THZTensor_add(dst, src, value)
return dst
end
}
ZTensor.add = argcheck{
nonamed=true,
{name="dst", type=typename, opt=true},
{name="src1", type=typename},
{name="value", type="number", default=1},
{name="src2", type=typename},
overload=ZTensor.add,
call =
function(dst, src1, value, src2)
dst = dst or src1
THZTensor_cadd(dst, src1, value, src2)
return dst
end
}
ZTensor.add = argcheck{
nonamed=true,
{name="dst", type=typename, opt=true},
{name="src1", type=typename},
{name="value", type="cdata", check=ztorch.isComplex},
{name="src2", type=typename},
overload=ZTensor.add,
call =
function(dst, src1, value, src2)
dst = dst or src1
THZTensor_cadd(dst, src1, value, src2)
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
THZTensor_mul(dst, src, 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
THZTensor_mul(dst, src, value)
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
THZTensor_cmul(dst, src1, src2)
return dst
end
}
ZTensor.div = argcheck{
nonamed=true,
{name="dst", type=typename, opt=true},
{name="src", type=typename},
{name="value", type="cdata", check=ztorch.isComplex},
call =
function(dst, src, value)
dst = dst or src
THZTensor_div(dst, src, value)
return dst
end
}
ZTensor.div = 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
THZTensor_div(dst, src, value)
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)