def testNumpy(self): numpy_arr = np.array([1.2, 2.3, 3.4, 4.5], dtype="float32") vec = swig_paddle.Vector.createVectorFromNumpy(numpy_arr) self.assertEqual(vec.isGpu(), swig_paddle.isUsingGpu()) vecData = vec.getData() for n, v in zip(numpy_arr, vecData): self.assertTrue(util.doubleEqual(n, v))
def test_numpy(self): numpy_mat = np.matrix([[1, 2], [3, 4], [5, 6]], dtype="float32") m = swig_paddle.Matrix.createDenseFromNumpy(numpy_mat) self.assertEqual((int(m.getHeight()), int(m.getWidth())), numpy_mat.shape) self.assertEqual(m.isGpu(), swig_paddle.isUsingGpu()) for a, e in zip(m.getData(), [1.0, 2.0, 3.0, 4.0, 5.0, 6.0]): self.assertAlmostEqual(a, e)
def test_create(self): m = swig_paddle.IVector.create(range(10), False) self.assertIsNotNone(m) for i in xrange(10): self.assertEqual(m[i], i) m = swig_paddle.IVector.create(range(10)) self.assertEqual(m.isGpu(), swig_paddle.isUsingGpu()) self.assertEqual(m.getData(), range(10))
def testCreateZero(self): v = swig_paddle.Vector.createZero(10, False) self.assertIsNotNone(v) for i in xrange(len(v)): self.assertTrue(util.doubleEqual(v[i], 0)) v[i] = i self.assertTrue(util.doubleEqual(v[i], i)) v = swig_paddle.Vector.createZero(10) self.assertEqual(v.isGpu(), swig_paddle.isUsingGpu()) self.assertEqual(v.getData(), [0] * 10)
def test_createZero(self): m = swig_paddle.IVector.createZero(10, False) self.assertIsNotNone(m) for i in xrange(10): self.assertEqual(m[i], 0) m[i] = i self.assertEqual(m[i], i) m = swig_paddle.IVector.createZero(10) self.assertEqual(m.isGpu(), swig_paddle.isUsingGpu()) self.assertEqual(m.getData(), [0] * 10)
def testCreate(self): v = swig_paddle.Vector.create([x / 100.0 for x in xrange(100)], False) self.assertIsNotNone(v) for i in xrange(len(v)): self.assertTrue(util.doubleEqual(v[i], i / 100.0)) self.assertEqual(100, len(v)) v = swig_paddle.Vector.create([x / 100.0 for x in xrange(100)]) self.assertEqual(v.isGpu(), swig_paddle.isUsingGpu()) self.assertEqual(100, len(v)) vdata = v.getData() for i in xrange(len(v)): self.assertTrue(util.doubleEqual(vdata[i], i / 100.0))
def test_numpy(self): vec = np.array([1, 3, 4, 65, 78, 1, 4], dtype="int32") iv = swig_paddle.IVector.createVectorFromNumpy(vec) self.assertEqual(iv.isGpu(), swig_paddle.isUsingGpu()) self.assertEqual(iv.getData(), list(vec))