test_pytorch_inline.py

from __future__ import print_function

import numpy as np

import PyTorch
import PyTorchHelpers


TorchClass = PyTorchHelpers.load_lua_class('TorchClass.lua', 'TorchClass')
cl = TorchClass()

v = list(range(10))
npv = np.asarray(v, dtype=np.float32)

cl.set(npv)
# cl.write()

npv2 = npv * 2
cl.set(npv2)
# cl.write()

cl.set(npv * 3)
# cl.write()

print('')
print('before allocating a simple array of zeros: cl.v\n', cl.v)
print(np.zeros(10, dtype=np.float32))

print('')
print('after: cl.v\n', cl.v)

TorchClass.lua

torch.setdefaulttensortype('torch.FloatTensor')




local TorchClass = torch.class('TorchClass')


function TorchClass:__init()
    print("<TorchClass> initialization")
end

function TorchClass:write()
    if self.v then
        print("<TorchClass> This is the value:")
        print(self.v)
    else
        print("<TorchClass> Value not defined")
    end
end

function TorchClass:set(vin)
    self.v = vin
end