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local argcheck = require 'argcheck'
local ffi = require 'ffi'
local env = require 'argcheck.env'
local SZ = tonumber(arg[1])
local N = tonumber(arg[2])
local scale = tonumber(arg[3]) or 1
local dbg = arg[4] == '1'
local named = arg[5] == '1'
if named then
print('warning: using named arguments!')
end
function env.istype(obj, typename)
if type(obj) == 'userdata' then
if typename == 'torch.DoubleTensor' then
return true
else
return false
end
end
return type(obj) == typename
end
ffi.cdef[[
typedef struct THLongStorage THLongStorage;
THLongStorage* THLongStorage_newWithSize2(long, long);
void THLongStorage_free(THLongStorage *storage);
typedef struct THGenerator THGenerator;
THGenerator* THGenerator_new();
void THRandom_manualSeed(THGenerator *_generator, unsigned long the_seed_);
typedef struct THDoubleTensor THDoubleTensor;
THDoubleTensor *THDoubleTensor_new(void);
void THDoubleTensor_free(THDoubleTensor *self);
void THDoubleTensor_rand(THDoubleTensor *r_, THGenerator *_generator, THLongStorage *size);
void THDoubleTensor_add(THDoubleTensor *r_, THDoubleTensor *t, double value);
void THDoubleTensor_cadd(THDoubleTensor *r_, THDoubleTensor *t, double value, THDoubleTensor *src);
double THDoubleTensor_normall(THDoubleTensor *t, double value);
]]
local status, C = pcall(ffi.load, ffi.os == 'OSX' and 'libTH.dylib' or 'libTH.so')
if not status then
error('please specify path to libTH in your (DY)LD_LIBRARY_PATH')
end
local DoubleTensor = {}
function DoubleTensor_new()
local self = C.THDoubleTensor_new()
ffi.gc(self, C.THDoubleTensor_free)
return self
end
function DoubleTensor:norm(l)
l = l or 2
return tonumber(C.THDoubleTensor_normall(self, l))
end
DoubleTensor_mt = {__index=DoubleTensor, __new=DoubleTensor_new}
DoubleTensor = ffi.metatype('THDoubleTensor', DoubleTensor_mt)
local _gen = C.THGenerator_new()
C.THRandom_manualSeed(_gen, 1111)
local function rand(a, b)
local size = C.THLongStorage_newWithSize2(a, b)
local self = DoubleTensor()
C.THDoubleTensor_rand(self, _gen, size)
C.THLongStorage_free(size)
return self
end
local add
local dotgraph
for _, RealTensor in ipairs{'torch.ByteTensor', 'torch.ShortTensor', 'torch.FloatTensor',
'torch.LongTensor', 'torch.IntTensor', 'torch.CharTensor',
'torch.DoubleTensor'} do
add = argcheck{
{name="res", type=RealTensor, opt=true},
{name="src", type=RealTensor},
{name="value", type="number"},
call =
function(res, src, value)
res = res or DoubleTensor()
C.THDoubleTensor_add(res, src, value)
return res
end
}
add, dotgraph = argcheck{
debug=dbg,
overload = add,
{name="res", type=RealTensor, opt=true},
{name="src1", type=RealTensor},
{name="value", type="number", default=1},
{name="src2", type=RealTensor},
call =
function(res, src1, value, src2)
res = res or torch.DoubleTensor()
C.THDoubleTensor_cadd(res, src1, value, src2)
return res
end
}
end
if dotgraph then
local f = io.open('argtree.dot', 'w')
f:write(dotgraph)
f:close()
end
local x = rand(SZ, SZ)
local y = rand(SZ, SZ)
print('x', x:norm())
print('y', x:norm())
print('running')
if named then
local clk = os.clock()
if scale == 1 then
for i=1,N do
add{res=y, src=x, value=5}
add{res=y, src1=x, src2=y}
end
else
for i=1,N do
add{res=y, src=x, value=5}
add{res=y, src1=x, value=scale, src2=y}
end
end
print('time (s)', os.clock()-clk)
else
local clk = os.clock()
if scale == 1 then
for i=1,N do
add(y, x, 5)
add(y, x, y)
end
else
for i=1,N do
add(y, x, 5)
add(y, x, scale, y)
end
end
print('time (s)', os.clock()-clk)
end
print('x', x:norm())
print('y', y:norm())
|
