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TensorMath.lua
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TensorMath.lua
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local wrap = require 'cwrap'
local interface = wrap.CInterface.new()
local method = wrap.CInterface.new()
local argtypes = wrap.CInterface.argtypes
argtypes['ptrdiff_t'] = {
helpname = function(arg)
return 'ptrdiff_t'
end,
declare = function(arg)
-- if it is a number we initialize here
local default = tonumber(tostring(arg.default)) or 0
return string.format("%s arg%d = %g;", 'ptrdiff_t', arg.i, default)
end,
check = function(arg, idx)
return string.format("lua_isinteger(L, %d)", idx)
end,
read = function(arg, idx)
return string.format("arg%d = (%s)lua_tointeger(L, %d);", arg.i, 'ptrdiff_t', idx)
end,
init = function(arg)
-- otherwise do it here
if arg.default then
local default = tostring(arg.default)
if not tonumber(default) then
return string.format("arg%d = %s;", arg.i, default)
end
end
end,
carg = function(arg)
return string.format('arg%d', arg.i)
end,
creturn = function(arg)
return string.format('arg%d', arg.i)
end,
precall = function(arg)
if arg.returned then
return string.format('lua_pushinteger(L, (lua_Integer)arg%d);', arg.i)
end
end,
postcall = function(arg)
if arg.creturned then
return string.format('lua_pushinteger(L, (lua_Integer)arg%d);', arg.i)
end
end
}
interface:print('/* WARNING: autogenerated file */')
interface:print('')
interface:print('#include "THC.h"')
interface:print('#include "luaT.h"')
interface:print('#include "torch/utils.h"')
interface:print('')
interface:print('')
interface:print([[
static int torch_isnonemptytable(lua_State *L, int idx)
{
int empty;
if (!lua_istable(L, idx)) return 0;
lua_rawgeti(L, idx, 1);
empty = lua_isnil(L, -1);
lua_pop(L, 1);
return !empty;
}
]])
-- Lua 5.2 compatibility
local unpack = unpack or table.unpack
-- specific to CUDA
local typenames = {
'CudaByteTensor',
'CudaCharTensor',
'CudaShortTensor',
'CudaIntTensor',
'CudaLongTensor',
'CudaTensor',
'CudaDoubleTensor',
'CudaHalfTensor'
}
for _, typename in ipairs(typenames) do
-- cut and paste from wrap/types.lua
wrap.types[typename] = {
helpname = function(arg)
if arg.dim then
return string.format('%s~%dD', typename, arg.dim)
else
return typename
end
end,
declare = function(arg)
local txt = {}
table.insert(txt, string.format("TH%s *arg%d = NULL;", typename, arg.i))
if arg.returned then
table.insert(txt, string.format("int arg%d_idx = 0;", arg.i));
end
return table.concat(txt, '\n')
end,
check = function(arg, idx)
if arg.dim then
return string.format('(arg%d = luaT_toudata(L, %d, "torch.%s")) && (arg%d->nDimension == %d)', arg.i, idx, typename, arg.i, arg.dim)
else
return string.format('(arg%d = luaT_toudata(L, %d, "torch.%s"))', arg.i, idx, typename)
end
end,
read = function(arg, idx)
if arg.returned then
return string.format("arg%d_idx = %d;", arg.i, idx)
end
end,
init = function(arg)
if type(arg.default) == 'boolean' then
return string.format('arg%d = TH%s_new(cutorch_getstate(L));', arg.i, typename)
elseif type(arg.default) == 'number' then
return string.format('arg%d = %s;', arg.i, arg.args[arg.default]:carg())
else
error('unknown default tensor type value')
end
end,
carg = function(arg)
return string.format('arg%d', arg.i)
end,
creturn = function(arg)
return string.format('arg%d', arg.i)
end,
precall = function(arg)
local txt = {}
if arg.default and arg.returned then
table.insert(txt, string.format('if(arg%d_idx)', arg.i)) -- means it was passed as arg
table.insert(txt, string.format('lua_pushvalue(L, arg%d_idx);', arg.i))
table.insert(txt, string.format('else'))
if type(arg.default) == 'boolean' then -- boolean: we did a new()
table.insert(txt, string.format('luaT_pushudata(L, arg%d, "torch.%s");', arg.i, typename))
else -- otherwise: point on default tensor --> retain
table.insert(txt, string.format('{'))
table.insert(txt, string.format('TH%s_retain(arg%d);', typename, arg.i)) -- so we need a retain
table.insert(txt, string.format('luaT_pushudata(L, arg%d, "torch.%s");', arg.i, typename))
table.insert(txt, string.format('}'))
end
elseif arg.default then
-- we would have to deallocate the beast later if we did a new
-- unlikely anyways, so i do not support it for now
if type(arg.default) == 'boolean' then
error('a tensor cannot be optional if not returned')
end
elseif arg.returned then
table.insert(txt, string.format('lua_pushvalue(L, arg%d_idx);', arg.i))
end
return table.concat(txt, '\n')
end,
postcall = function(arg)
local txt = {}
if arg.creturned then
-- if a tensor is returned by a wrapped C function, the refcount semantics
-- are ambiguous (transfer ownership vs. shared ownership).
-- We never actually do this, so lets just not allow it.
error('a tensor cannot be creturned')
end
return table.concat(txt, '\n')
end
}
wrap.types[typename .. 'Array'] = {
helpname = function(arg)
return string.format('{%s+}', typename)
end,
declare = function(arg)
local txt = {}
table.insert(txt, string.format('TH%s **arg%d_data = NULL;', typename, arg.i))
table.insert(txt, string.format('long arg%d_size = 0;', arg.i))
table.insert(txt, string.format('int arg%d_i = 0;', arg.i))
return table.concat(txt, '\n')
end,
check = function(arg, idx)
return string.format('torch_isnonemptytable(L, %d)', idx)
end,
read = function(arg, idx)
local txt = {}
-- Iterate over the array to find its length, leave elements on stack.
table.insert(txt, string.format('do'))
table.insert(txt, string.format('{'))
table.insert(txt, string.format(' arg%d_size++;', arg.i))
table.insert(txt, string.format(' lua_checkstack(L, 1);'))
table.insert(txt, string.format(' lua_rawgeti(L, %d, arg%d_size);', idx, arg.i))
table.insert(txt, string.format('}'))
table.insert(txt, string.format('while (!lua_isnil(L, -1));'))
table.insert(txt, string.format('arg%d_size--;', arg.i))
-- Pop nil element from stack.
table.insert(txt, string.format('lua_pop(L, 1);'))
-- Allocate tensor pointers and read values from stack backwards.
table.insert(txt, string.format('arg%d_data = (TH%s**)THAlloc(arg%d_size * sizeof(TH%s*));', arg.i, typename, arg.i, typename))
table.insert(txt, string.format('for (arg%d_i = arg%d_size - 1; arg%d_i >= 0; arg%d_i--)', arg.i, arg.i, arg.i, arg.i))
table.insert(txt, string.format('{'))
table.insert(txt, string.format(' if (!(arg%d_data[arg%d_i] = luaT_toudata(L, -1, "torch.%s")))', arg.i, arg.i, typename))
table.insert(txt, string.format(' luaL_error(L, "expected %s in tensor array");', typename))
table.insert(txt, string.format(' lua_pop(L, 1);'))
table.insert(txt, string.format('}'))
table.insert(txt, string.format(''))
return table.concat(txt, '\n')
end,
init = function(arg)
end,
carg = function(arg)
return string.format('arg%d_data,arg%d_size', arg.i, arg.i)
end,
creturn = function(arg)
error('TensorArray cannot be returned.')
end,
precall = function(arg)
end,
postcall = function(arg)
return string.format('THFree(arg%d_data);', arg.i)
end
}
end
local function interpretdefaultvalue(arg)
local default = arg.default
if type(default) == 'boolean' then
if default then
return '1'
else
return '0'
end
elseif type(default) == 'number' then
return tostring(default)
elseif type(default) == 'string' then
return default
elseif type(default) == 'function' then
default = default(arg)
assert(type(default) == 'string', 'a default function must return a string')
return default
elseif type(default) == 'nil' then
return nil
else
error('unknown default type value')
end
end
wrap.types.half = {
helpname = function(arg)
return "half"
end,
declare = function(arg)
-- if it is a number we initialize here
local default = tonumber(interpretdefaultvalue(arg)) or 0
return string.format("half arg%d = THC_float2half((float) %d);", arg.i, tonumber(default))
end,
check = function(arg, idx)
return string.format("lua_isnumber(L, %d)", idx)
end,
read = function(arg, idx)
return string.format("arg%d = THC_float2half((float) lua_tonumber(L, %d));", arg.i, idx)
end,
init = function(arg)
-- otherwise do it here
if arg.default then
local default = interpretdefaultvalue(arg)
if not tonumber(default) then
return string.format("arg%d = THC_float2half((float) %s);", arg.i, default)
end
end
end,
carg = function(arg)
return string.format('arg%d', arg.i)
end,
creturn = function(arg)
return string.format('arg%d', arg.i)
end,
precall = function(arg)
if arg.returned then
return string.format('lua_pushnumber(L, (lua_Number) THC_half2float(arg%d));', arg.i)
end
end,
postcall = function(arg)
if arg.creturned then
return string.format('lua_pushnumber(L, (lua_Number) THC_half2float(arg%d));', arg.i)
end
end
}
wrap.types.LongArg = {
vararg = true,
helpname = function(arg)
return "(LongStorage | dim1 [dim2...])"
end,
declare = function(arg)
return string.format("THLongStorage *arg%d = NULL;", arg.i)
end,
init = function(arg)
if arg.default then
error('LongArg cannot have a default value')
end
end,
check = function(arg, idx)
return string.format("cutorch_islongargs(L, %d)", idx)
end,
read = function(arg, idx)
return string.format("arg%d = cutorch_checklongargs(L, %d);", arg.i, idx)
end,
carg = function(arg, idx)
return string.format('arg%d', arg.i)
end,
creturn = function(arg, idx)
return string.format('arg%d', arg.i)
end,
precall = function(arg)
local txt = {}
if arg.returned then
table.insert(txt, string.format('luaT_pushudata(L, arg%d, "torch.LongStorage");', arg.i))
end
return table.concat(txt, '\n')
end,
postcall = function(arg)
local txt = {}
if arg.creturned then
-- this next line is actually debatable
table.insert(txt, string.format('THLongStorage_retain(arg%d);', arg.i))
table.insert(txt, string.format('luaT_pushudata(L, arg%d, "torch.LongStorage");', arg.i))
end
if not arg.returned and not arg.creturned then
table.insert(txt, string.format('THLongStorage_free(arg%d);', arg.i))
end
return table.concat(txt, '\n')
end
}
wrap.types.charoption = {
helpname = function(arg)
if arg.values then
return "(" .. table.concat(arg.values, '|') .. ")"
end
end,
declare = function(arg)
local txt = {}
table.insert(txt, string.format("const char *arg%d = NULL;", arg.i))
if arg.default then
table.insert(txt, string.format("char arg%d_default = '%s';", arg.i, arg.default))
end
return table.concat(txt, '\n')
end,
init = function(arg)
return string.format("arg%d = &arg%d_default;", arg.i, arg.i)
end,
check = function(arg, idx)
local txt = {}
local txtv = {}
table.insert(txt, string.format('(arg%d = lua_tostring(L, %d)) && (', arg.i, idx))
for _,value in ipairs(arg.values) do
table.insert(txtv, string.format("*arg%d == '%s'", arg.i, value))
end
table.insert(txt, table.concat(txtv, ' || '))
table.insert(txt, ')')
return table.concat(txt, '')
end,
read = function(arg, idx)
end,
carg = function(arg, idx)
return string.format('arg%d', arg.i)
end,
creturn = function(arg, idx)
end,
precall = function(arg)
end,
postcall = function(arg)
end
}
cutorch_state_code = function(varname)
local txt = {}
table.insert(txt, 'lua_getglobal(L, "cutorch");')
table.insert(txt, 'lua_getfield(L, -1, "_state");')
table.insert(txt, string.format('THCState *%s = lua_touserdata(L, -1);', varname))
table.insert(txt, 'lua_pop(L, 2);')
return table.concat(txt, '\n');
end
interface:registerDefaultArgument(cutorch_state_code)
method:registerDefaultArgument(cutorch_state_code)
local function wrap(...)
local args = {...}
-- interface
interface:wrap(...)
-- method: we override things possibly in method table field
for _,x in ipairs(args) do
if type(x) == 'table' then -- ok, now we have a list of args
for _, arg in ipairs(x) do
if arg.method then
for k,v in pairs(arg.method) do
if v == 'nil' then -- special case, we erase the field
arg[k] = nil
else
arg[k] = v
end
end
end
end
end
end
method:wrap(unpack(args))
end
local Tensor
-- functions to help take in arguments that are Tensor or CudaLongTensor (for backward compatibility)
-- used in scatter / gather for example
local function TensorToCudaLong_declare(dummy)
return function(arg)
local txt = {}
table.insert(txt, string.format("THCudaLongTensor *arg%d = NULL;", arg.i))
if dummy then
table.insert(txt, string.format("THCudaLongTensor *indexLongTensor = NULL;"))
table.insert(txt, string.format("TH%s *dummyIndexTensor = NULL;", Tensor))
end
return table.concat(txt, '\n')
end
end
local function TensorToCudaLong_check(arg, idx)
return string.format('(dummyIndexTensor = luaT_toudata(L, %d, "torch.%s"))', idx, Tensor)
end
local function TensorToCudaLong_read(arg, idx)
local copyname = Tensor:match("(%a+)Tensor")
if copyname == 'Cuda' then
copyname = 'CudaFloat'
end
local txt = {}
table.insert(txt, string.format('arg%d = THCudaLongTensor_new(default_arg1);', arg.i))
table.insert(txt, string.format('THLongStorage *indexSize = TH%s_newSizeOf(default_arg1, dummyIndexTensor);', Tensor))
table.insert(txt, string.format('THCudaLongTensor_resize(default_arg1, arg%d, indexSize, NULL);', arg.i))
table.insert(txt, string.format('THLongStorage_free(indexSize);'))
table.insert(txt, string.format('THCudaLongTensor_copy%s(default_arg1, arg%d, dummyIndexTensor);', copyname, arg.i))
table.insert(txt, string.format('indexLongTensor = arg%d;', arg.i))
return table.concat(txt, '\n')
end
local function TensorToCudaLong_postcall(arg)
return "if (indexLongTensor != NULL) THCudaLongTensor_free(default_arg1, indexLongTensor);\n"
end
-- function to initialize the gather call
local function gatherInit(arg)
return table.concat(
{
arg.__metatable.init(arg),
string.format("TH%s_checkGPU(cutorch_getstate(L), 1, %s);",
Tensor, arg.args[4]:carg()),
string.format(
[[
THCState *state = cutorch_getstate(L);
THLongStorage *indicesSize = THCudaLongTensor_newSizeOf(state, %s);
TH%s_resize(state, %s, indicesSize, NULL);
THLongStorage_free(indicesSize);
]], arg.args[4]:carg(), Tensor, arg:carg()),
}, '\n')
end
--
-- Non-CudaTensor type math, since these are less fully implemented than
-- CudaTensor
--
local handledTypenames = {
'CudaByteTensor',
'CudaCharTensor',
'CudaShortTensor',
'CudaIntTensor',
'CudaLongTensor',
'CudaDoubleTensor',
'CudaHalfTensor',
}
local handledTypereals = {
'unsigned char',
'char',
'short',
'int',
'long',
'double',
'half'
}
local handledTypeaccreals = {
'long',
'long',
'long',
'long',
'long',
'double',
'float'
}
for k, Tensor_ in pairs(handledTypenames) do
Tensor = Tensor_
if Tensor == 'CudaHalfTensor' then
interface:print("#ifdef CUDA_HALF_TENSOR")
end
local real = handledTypereals[k]
local accreal = handledTypeaccreals[k]
function interface.luaname2wrapname(self, name)
return string.format('cutorch_%s_%s', Tensor, name)
end
function method.luaname2wrapname(self, name)
return string.format('m_cutorch_%s_%s', Tensor, name)
end
local function cname(name)
return string.format('TH%s_%s', Tensor, name)
end
local function lastdim(argn)
return function(arg)
return string.format('TH%s_nDimension(cutorch_getstate(L), %s)',
Tensor, arg.args[argn]:carg())
end
end
local function lastdimarray(argn)
return function(arg)
return string.format('TH%s_nDimension(cutorch_getstate(L), arg%d_data[0])',
Tensor, arg.args[argn].i)
end
end
wrap("fill",
cname("fill"),
{{name=Tensor, returned=true},
{name=real}})
wrap("zero",
cname("zero"),
{{name=Tensor, returned=true}})
wrap("zeros",
cname("zeros"),
{{name=Tensor, default=true, returned=true, method={default='nil'}},
{name="LongArg"}})
wrap("ones",
cname("ones"),
{{name=Tensor, default=true, returned=true, method={default='nil'}},
{name="LongArg"}})
wrap("reshape",
cname("reshape"),
{{name=Tensor, default=true, returned=true},
{name=Tensor},
{name="LongArg"}})
wrap("numel",
cname("numel"),
{{name=Tensor},
{name="ptrdiff_t", creturned=true}})
wrap("add",
cname("add"),
{{name=Tensor, default=true, returned=true, method={default='nil'}},
{name=Tensor, method={default=1}},
{name=real}},
cname("cadd"),
{{name=Tensor, default=true, returned=true, method={default='nil'}},
{name=Tensor, method={default=1}},
{name=real, default=1},
{name=Tensor}})
wrap("csub",
cname("sub"),
{{name=Tensor, default=true, returned=true, method={default='nil'}},
{name=Tensor, method={default=1}},
{name=real}},
cname("csub"),
{{name=Tensor, default=true, returned=true, method={default='nil'}},
{name=Tensor, method={default=1}},
{name=real, default=1},
{name=Tensor}})
wrap("mul",
cname("mul"),
{{name=Tensor, default=true, returned=true, method={default='nil'}},
{name=Tensor, method={default=1}},
{name=real}})
wrap("clamp",
cname("clamp"),
{{name=Tensor, default=true, returned=true, method={default='nil'}},
{name=Tensor, method={default=1}},
{name=real},
{name=real}})
wrap("cross",
cname("cross"),
{{name=Tensor, default=true, returned=true},
{name=Tensor},
{name=Tensor},
{name="index", default=0}})
wrap("div",
cname("div"),
{{name=Tensor, default=true, returned=true, method={default='nil'}},
{name=Tensor, method={default=1}},
{name=real}})
wrap("fmod",
cname("fmod"),
{{name=Tensor, default=true, returned=true, method={default='nil'}},
{name=Tensor, method={default=1}},
{name=real}})
wrap("remainder",
cname("remainder"),
{{name=Tensor, default=true, returned=true, method={default='nil'}},
{name=Tensor, method={default=1}},
{name=real}})
wrap("equal",
cname("equal"),
{{name=Tensor},
{name=Tensor},
{name="boolean", creturned=true}})
for _, name in ipairs({"cmul", "cpow", "cdiv"}) do
wrap(name,
cname(name),
{{name=Tensor, default=true, returned=true, method={default='nil'}},
{name=Tensor, method={default=1}},
{name=Tensor}})
end
wrap("addcmul",
cname("addcmul"),
{{name=Tensor, default=true, returned=true, method={default='nil'}},
{name=Tensor, method={default=1}},
{name=real, default=1},
{name=Tensor},
{name=Tensor}})
wrap("addcdiv",
cname("addcdiv"),
{{name=Tensor, default=true, returned=true, method={default='nil'}},
{name=Tensor, method={default=1}},
{name=real, default=1},
{name=Tensor},
{name=Tensor}})
for _,name in ipairs({"min", "max"}) do
wrap(name,
cname(name .. "all"),
{{name=Tensor},
{name=real, creturned=true}},
cname(name),
{{name=Tensor, default=true, returned=true},
{name='CudaLongTensor', default=true, returned=true},
{name=Tensor},
{name="index"}})
end
for _,name in ipairs({"cmin", "cmax"}) do
wrap(name,
cname(name),
{{name=Tensor, default=true, returned=true},
{name=Tensor, method={default=1}},
{name=Tensor}},
cname(name .. "Value"),
{{name=Tensor, default=true, returned=true},
{name=Tensor, method={default=1}},
{name=real}})
end
if Tensor == 'CudaByteTensor' then
for _,name in pairs({'all', 'any'}) do
wrap(name,
cname('logical' .. name),
{{name=Tensor},
{name="boolean", creturned=true}})
end
end
for _,name in pairs({'lt','gt','le','ge','eq','ne'}) do
wrap(name,
cname(name .. 'Value'),
{{name='CudaByteTensor',default=true, returned=true},
{name=Tensor},
{name=real}},
cname(name .. 'ValueT'),
{{name=Tensor, returned=true},
{name=Tensor},
{name=real}},
cname(name .. 'Tensor'),
{{name='CudaByteTensor',default=true, returned=true},
{name=Tensor},
{name=Tensor}},
cname(name .. 'TensorT'),
{{name=Tensor, returned=true},
{name=Tensor},
{name=Tensor}})
end
wrap("sum",
cname("sumall"),
{{name=Tensor},
{name=accreal, creturned=true}},
cname("sum"),
{{name=Tensor, default=true, returned=true},
{name=Tensor},
{name="index"}})
for _, name in ipairs({"cumsum", "cumprod"}) do
wrap(name,
cname(name),
{{name=Tensor, default=true, returned=true},
{name=Tensor},
{name="index", default=1}})
end
wrap("prod",
cname("prodall"),
{{name=Tensor},
{name=accreal, creturned=true}},
cname("prod"),
{{name=Tensor, default=true, returned=true},
{name=Tensor},
{name="index"}})
wrap("mean",
cname("meanall"),
{{name=Tensor},
{name=accreal, creturned=true}},
cname("mean"),
{{name=Tensor, default=true, returned=true},
{name=Tensor},
{name="index"}})
wrap("maskedFill",
cname("maskedFill"),
{{name=Tensor, returned=true, method={default='nil'}},
{name='CudaByteTensor'},
{name=real}})
wrap("maskedCopy",
cname("maskedCopy"),
{{name=Tensor, returned=true, method={default='nil'}},
{name='CudaByteTensor'},
{name=Tensor}})
wrap("maskedSelect",
cname("maskedSelect"),
{{name=Tensor, returned=true, default=true},
{name=Tensor},
{name='CudaByteTensor'}})
wrap("gather",
cname("gather"),
{{name=Tensor, default=true, returned=true, init=gatherInit},
{name=Tensor},
{name="index"},
{name='CudaLongTensor'}},
cname("gather"), -- this is for backward-compatibility, and takes in "Tensor" as the indexing tensor
{{name=Tensor, default=true, returned=true, init=gatherInit},
{name=Tensor},
{name="index"},
{name=Tensor, declare=TensorToCudaLong_declare(true), check=TensorToCudaLong_check, read=TensorToCudaLong_read, postcall=TensorToCudaLong_postcall}})
wrap("scatter",
cname("scatter"),
{{name=Tensor, returned=true},
{name="index"},
{name='CudaLongTensor'},
{name=Tensor}},
cname("scatter"), -- this is for backward-compatibility, and takes in "Tensor" as the indexing tensor
{{name=Tensor, returned=true},
{name="index"},
{name=Tensor, declare=TensorToCudaLong_declare(true), check=TensorToCudaLong_check, read=TensorToCudaLong_read, postcall=TensorToCudaLong_postcall},
{name=Tensor}},
cname("scatterFill"),
{{name=Tensor, returned=true},
{name="index"},
{name='CudaLongTensor'},
{name=real}},
cname("scatterFill"), -- this is for backward-compatibility, and takes in "Tensor" as the indexing tensor
{{name=Tensor, returned=true},
{name="index"},
{name=Tensor, declare=TensorToCudaLong_declare(false), check=TensorToCudaLong_check, read=TensorToCudaLong_read, postcall=TensorToCudaLong_postcall},
{name=real}}
)
wrap("sort",
cname("sort"),
{{name=Tensor, default=true, returned=true},
{name="CudaLongTensor", default=true, returned=true, noreadadd=true},
{name=Tensor},
{name="index", default=lastdim(3)},
{name="boolean", default=0}}
)
wrap("squeeze",
cname("squeeze"),
{{name=Tensor, default=true, returned=true, postcall=function(arg)
local txt = {}
if arg.returned then
table.insert(txt, string.format('if(arg%d->nDimension == 1 && arg%d->size[0] == 1)', arg.i, arg.i)) -- number
if Tensor == 'CudaHalfTensor' then
table.insert(txt, string.format('lua_pushnumber(L, (lua_Number)THC_half2float(TH%s_get1d(cutorch_getstate(L), arg%d, 0)));', Tensor, arg.i))
else
table.insert(txt, string.format('lua_pushnumber(L, (lua_Number)(TH%s_get1d(cutorch_getstate(L), arg%d, 0)));', Tensor, arg.i))
end
end
return table.concat(txt, '\n')
end},
{name=Tensor}},
cname("squeeze1d"),
{{name=Tensor, default=true, returned=true,
postcall=
function(arg)
local txt = {}
if arg.returned then
table.insert(txt, string.format('if(!hasdims && arg%d->nDimension == 1 && arg%d->size[0] == 1)', arg.i, arg.i)) -- number
if Tensor == 'CudaHalfTensor' then
table.insert(txt, string.format('lua_pushnumber(L, (lua_Number)THC_half2float(TH%s_get1d(cutorch_getstate(L), arg%d, 0)));}', Tensor, arg.i))
else
table.insert(txt, string.format('lua_pushnumber(L, (lua_Number)(TH%s_get1d(cutorch_getstate(L), arg%d, 0)));}', Tensor, arg.i))
end
end
return table.concat(txt, '\n')
end},
{name=Tensor,
precall=
function(arg)
return string.format('{int hasdims = arg%d->nDimension > 1;', arg.i)
end},
{name="index"}})
wrap("abs",
cname("abs"),
{{name=Tensor, default=true, returned=true, method={default='nil'}},
{name=Tensor, method={default=1}}})
wrap("sign",
cname("sign"),
{{name=Tensor, default=true, returned=true, method={default='nil'}},
{name=Tensor, method={default=1}}})
wrap("cat",
cname("cat"),
{{name=Tensor, default=true, returned=true},
{name=Tensor},
{name=Tensor},
{name="index", default=lastdim(2)}},
cname("catArray"),
{{name=Tensor, default=true, returned=true},
{name=Tensor .. "Array"},
{name="index", default=lastdimarray(2)}})
wrap("geometric",
cname("geometric"),
{{name=Tensor, returned=true},
{name='double'}})
wrap("bernoulli",
cname("bernoulli"),
{{name=Tensor, returned=true},
{name='double', default=0.5}},
cname("bernoulli_FloatTensor"),
{{name=Tensor, returned=true},
{name="CudaTensor"}},
cname("bernoulli_DoubleTensor"),
{{name=Tensor, returned=true},
{name="CudaDoubleTensor"}})
wrap("nonzero",
cname("nonzero"),
{{name="CudaLongTensor", default=true, returned=true},
{name=Tensor}})
if real == 'float' or real == 'double' or real == 'half' then
for _,name in ipairs({"log", "log1p", "exp",
"cos", "acos", "cosh",
"sin", "asin", "sinh",
"tan", "atan", "tanh",
"sqrt", "rsqrt", "sigmoid",
"cinv", "ceil", "floor",
"neg", "round", "trunc", "frac"}) do
wrap(name,
cname(name),
{{name=Tensor, default=true, returned=true, method={default='nil'}},
{name=Tensor, method={default=1}}})
end
wrap("pow",
cname("pow"),
{{name=Tensor, default=true, returned=true, method={default='nil'}},
{name=Tensor, method={default=1}},
{name=real}},
cname("tpow"),
{{name=Tensor, default=true, returned=true, method={default='nil'}},
{name = real},
{name=Tensor, method={default=1}}})
wrap("rand",
cname("rand"),
{{name=Tensor, default=true, returned=true, method={default='nil'}},
{name="LongArg"}})
wrap("randn",
cname("randn"),
{{name=Tensor, default=true, returned=true, method={default='nil'}},
{name="LongArg"}})
wrap("multinomial",
cname("multinomial"),
{{name=Tensor, default=true, returned=true, method={default='nil'}},
{name=Tensor},
{name="int"},
{name="boolean", default=false}})
for _,f in ipairs({{name='uniform', a=0, b=1},
{name='cauchy', a=0, b=1},
{name='normal', a=0, b=1},
{name='logNormal', a=1, b=2}}) do
wrap(f.name,
cname(f.name),
{{name=Tensor, returned=true},
{name='double', default=f.a},
{name='double', default=f.b}})
end
wrap('exponential',
cname('exponential'),
{{name=Tensor, returned=true},
{name='double', default=nil}})
wrap("norm",
cname("normall"),
{{name=Tensor},
{name=real, default=2},
{name=accreal, creturned=true}},