add test/test_call_lua.py. Also add requirements.txt, test/requiremen…

…ts.txt, pytest.ini

.gitignore

@@ -65,3 +65,5 @@ docs/_build/
 
 # PyBuilder
 target/
+
+test/junit-pytest-report.xml

pytest.ini

@@ -0,0 +1,3 @@
+[pytest]
+addopts = --junitxml=test/junit-pytest-report.xml -ra
+testpaths = test

requirements.txt

@@ -0,0 +1,2 @@
+numpy
+docopt

simpleexample/luabit.lua

@@ -31,4 +31,3 @@ function Luabit:printTable(sometable, somestring, table2)
   end
   return {bear='happy', result=12.345, foo='bar'}
 end
-

simpleexample/pybit.py

@@ -1,5 +1,3 @@
-import sys
-import os
 import PyTorch
 import PyTorchHelpers
 import numpy as np
@@ -25,6 +23,5 @@
 print('outTensor', outTensor)
 
 res = luabit.printTable({'color': 'red', 'weather': 'sunny', 'anumber': 10, 'afloat': 1.234}, 'mistletoe', {
-  'row1': 'col1', 'meta': 'data'})
+    'row1': 'col1', 'meta': 'data'})
 print('res', res)
-

test/requirements.txt

@@ -0,0 +1,2 @@
+pytest
+python-mnist

test/test_call_lua.lua

@@ -0,0 +1,38 @@
+require 'torch'
+require 'nn'
+
+local TestCallLua = torch.class('TestCallLua')
+
+function TestCallLua:__init(someName)
+  print('TestCallLua:__init(', someName, ')')
+  self.someName = someName
+end
+
+function TestCallLua:getName()
+  return self.someName
+end
+
+function TestCallLua:getOut(inTensor, outSize, kernelSize)
+  local inSize = inTensor:size(3)
+  local m = nn.TemporalConvolution(inSize, outSize, kernelSize)
+  m:float()
+  local out = m:forward(inTensor)
+  print('out from lua', out)
+  return out
+end
+
+function TestCallLua:addOne(inTensor)
+  local outTensor = inTensor + 3
+  return outTensor
+end
+
+function TestCallLua:printTable(sometable, somestring, table2)
+  for k, v in pairs(sometable) do
+    print('TestCallLua:printTable ', k, v)
+  end
+  print('somestring', somestring)
+  for k, v in pairs(table2) do
+    print('TestCallLua table2 ', k, v)
+  end
+  return {bear='happy', result=12.345, foo='bar'}
+end

test/test_call_lua.py

@@ -0,0 +1,40 @@
+import PyTorch
+import PyTorchHelpers
+import numpy as np
+
+
+def test_call_lua():
+    TestCallLua = PyTorchHelpers.load_lua_class('test/test_call_lua.lua', 'TestCallLua')
+
+    batchSize = 2
+    numFrames = 4
+    inSize = 3
+    outSize = 3
+    kernelSize = 3
+
+    luabit = TestCallLua('green')
+    print(luabit.getName())
+    assert luabit.getName() == 'green'
+    print('type(luabit)', type(luabit))
+    assert str(type(luabit)) == '<class \'PyTorchLua.TestCallLua\'>'
+
+    np.random.seed(123)
+    inTensor = np.random.randn(batchSize, numFrames, inSize).astype('float32')
+    luain = PyTorch.asFloatTensor(inTensor)
+
+    luaout = luabit.getOut(luain, outSize, kernelSize)
+
+    outTensor = luaout.asNumpyTensor()
+    print('outTensor', outTensor)
+    # I guess we just assume if we got to this point, with no exceptions, then thats a good thing...
+    # lets add some new test...
+
+    outTensor = luabit.addOne(luain).asNumpyTensor()
+    assert isinstance(outTensor, np.ndarray)
+    assert inTensor.shape == outTensor.shape
+    assert np.abs((inTensor + 3) - outTensor).max() < 1e-4
+
+    res = luabit.printTable({'color': 'red', 'weather': 'sunny', 'anumber': 10, 'afloat': 1.234}, 'mistletoe', {
+        'row1': 'col1', 'meta': 'data'})
+    print('res', res)
+    assert res == {'foo': 'bar', 'result': 12.345, 'bear': 'happy'}