def testCreateZero(self):
v = swig_paddle.Vector.createZero(10)
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))
def testCreateZero(self):
v = swig_paddle.Vector.createZero(10)
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))
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 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 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 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 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 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 backward_callback(param_):
self.isCalled = isinstance(param_, swig_paddle.Parameter)
assert isinstance(param_, swig_paddle.Parameter)
vec = param_.getBuf(swig_paddle.PARAMETER_VALUE)
assert isinstance(vec, swig_paddle.Vector)
vec = vec.copyToNumpyArray()
for val_ in vec:
self.assertTrue(util.doubleEqual(
val_, 0.1)) # Assert All Value is 0.1
vecs = list(param_.getBufs())
opt_ = optimizers[param_.getID()]
opt_.update(vecs, param_.getConfig())
def backward_callback(param_):
self.isCalled = isinstance(param_, swig_paddle.Parameter)
assert isinstance(param_, swig_paddle.Parameter)
vec = param_.getBuf(swig_paddle.PARAMETER_VALUE)
assert isinstance(vec, swig_paddle.Vector)
vec = vec.copyToNumpyArray()
for val_ in vec:
self.assertTrue(
util.doubleEqual(val_, 0.1)) # Assert All Value is 0.1
vecs = list(param_.getBufs())
opt_ = optimizers[param_.getID()]
opt_.update(vecs, param_.getConfig())
def testNumpy(self):
numpy_arr = np.array([1.2, 2.3, 3.4, 4.5], dtype="float32")
vec = swig_paddle.Vector.createCpuVectorFromNumpy(numpy_arr)
assert isinstance(vec, swig_paddle.Vector)
numpy_arr[0] = 0.1
for n, v in zip(numpy_arr, vec):
self.assertTrue(util.doubleEqual(n, v))
numpy_2 = vec.toNumpyArrayInplace()
vec[0] = 1.3
for x, y in zip(numpy_arr, numpy_2):
self.assertTrue(util.doubleEqual(x, y))
for x, y in zip(numpy_arr, vec):
self.assertTrue(util.doubleEqual(x, y))
numpy_3 = vec.copyToNumpyArray()
numpy_3[0] = 0.4
self.assertTrue(util.doubleEqual(vec[0], 1.3))
self.assertTrue(util.doubleEqual(numpy_3[0], 0.4))
for i in xrange(1, len(numpy_3)):
util.doubleEqual(numpy_3[i], vec[i])
def testCpuNumpy(self):
numpy_arr = np.array([1.2, 2.3, 3.4, 4.5], dtype="float32")
vec = swig_paddle.Vector.createCpuVectorFromNumpy(numpy_arr, False)
assert isinstance(vec, swig_paddle.Vector)
numpy_arr[0] = 0.1
for n, v in zip(numpy_arr, vec):
self.assertTrue(util.doubleEqual(n, v))
numpy_2 = vec.toNumpyArrayInplace()
vec[0] = 1.3
for x, y in zip(numpy_arr, numpy_2):
self.assertTrue(util.doubleEqual(x, y))
for x, y in zip(numpy_arr, vec):
self.assertTrue(util.doubleEqual(x, y))
numpy_3 = vec.copyToNumpyArray()
numpy_3[0] = 0.4
self.assertTrue(util.doubleEqual(vec[0], 1.3))
self.assertTrue(util.doubleEqual(numpy_3[0], 0.4))
for i in xrange(1, len(numpy_3)):
util.doubleEqual(numpy_3[i], vec[i])
def testCopyFromNumpy(self):
vec = swig_paddle.Vector.createZero(1, False)
arr = np.array([1.3, 3.2, 2.4], dtype="float32")
vec.copyFromNumpyArray(arr)
for i in xrange(len(vec)):
self.assertTrue(util.doubleEqual(vec[i], arr[i]))
def testCreate(self):
v = swig_paddle.Vector.create([x / 100.0 for x in xrange(100)])
self.assertIsNotNone(v)
for i in xrange(len(v)):
self.assertTrue(util.doubleEqual(v[i], i / 100.0))
self.assertEqual(100, len(v))
def testCopyFromNumpy(self):
vec = swig_paddle.Vector.createZero(1)
arr = np.array([1.3, 3.2, 2.4], dtype="float32")
vec.copyFromNumpyArray(arr)
for i in xrange(len(vec)):
self.assertTrue(util.doubleEqual(vec[i], arr[i]))
def testCreate(self):
v = swig_paddle.Vector.create([x / 100.0 for x in xrange(100)])
self.assertIsNotNone(v)
for i in xrange(len(v)):
self.assertTrue(util.doubleEqual(v[i], i / 100.0))
self.assertEqual(100, len(v))