class TestCPU(object):
def __init__(self):
# this code gets called prior to each test
self.be = CPU()
def test_empty_creation(self):
tns = self.be.empty((4, 3))
assert tns.shape == (4, 3)
def test_array_creation(self):
tns = self.be.array([[1, 2], [3, 4]])
assert tns.shape == (2, 2)
assert_tensor_equal(tns, CPUTensor([[1, 2], [3, 4]]))
def test_zeros_creation(self):
tns = self.be.zeros([3, 1])
assert tns.shape == (3, 1)
assert_tensor_equal(tns, CPUTensor([[0], [0], [0]]))
def test_ones_creation(self):
tns = self.be.ones([1, 4])
assert tns.shape == (1, 4)
assert_tensor_equal(tns, CPUTensor([[1, 1, 1, 1]]))
def test_all_equal(self):
left = self.be.ones([2, 2])
right = self.be.ones([2, 2])
out = self.be.empty([2, 2])
self.be.equal(left, right, out)
assert out.shape == (2, 2)
assert_tensor_equal(out, CPUTensor([[1, 1], [1, 1]]))
def test_some_equal(self):
left = self.be.ones([2, 2])
right = self.be.array([[0, 1], [0, 1]])
out = self.be.empty([2, 2])
self.be.equal(left, right, out)
assert out.shape == (2, 2)
assert_tensor_equal(out, CPUTensor([[0, 1], [0, 1]]))
def test_none_equal(self):
left = self.be.ones([2, 2])
right = self.be.zeros([2, 2])
out = self.be.empty([2, 2])
self.be.equal(left, right, out)
assert out.shape == (2, 2)
assert_tensor_equal(out, CPUTensor([[0, 0], [0, 0]]))
def test_all_not_equal(self):
left = self.be.ones([2, 2])
right = self.be.zeros([2, 2])
out = self.be.empty([2, 2])
self.be.not_equal(left, right, out)
assert out.shape == (2, 2)
assert_tensor_equal(out, CPUTensor([[1, 1], [1, 1]]))
def test_some_not_equal(self):
left = self.be.ones([2, 2])
right = self.be.array([[0, 1], [0, 1]])
out = self.be.empty([2, 2])
self.be.not_equal(left, right, out)
assert out.shape == (2, 2)
assert_tensor_equal(out, CPUTensor([[1, 0], [1, 0]]))
def test_none_not_equal(self):
left = self.be.ones([2, 2])
right = self.be.ones([2, 2])
out = self.be.empty([2, 2])
self.be.not_equal(left, right, out)
assert out.shape == (2, 2)
assert_tensor_equal(out, CPUTensor([[0, 0], [0, 0]]))
def test_greater(self):
left = self.be.array([[-1, 0], [1, 92]])
right = self.be.ones([2, 2])
out = self.be.empty([2, 2])
self.be.greater(left, right, out)
assert out.shape == (2, 2)
assert_tensor_equal(out, CPUTensor([[0, 0], [0, 1]]))
def test_greater_equal(self):
left = self.be.array([[-1, 0], [1, 92]])
right = self.be.ones([2, 2])
out = self.be.empty([2, 2])
self.be.greater_equal(left, right, out)
assert out.shape == (2, 2)
assert_tensor_equal(out, CPUTensor([[0, 0], [1, 1]]))
def test_less(self):
left = self.be.array([[-1, 0], [1, 92]])
right = self.be.ones([2, 2])
out = self.be.empty([2, 2])
self.be.less(left, right, out)
assert out.shape == (2, 2)
assert_tensor_equal(out, CPUTensor([[1, 1], [0, 0]]))
def test_less_equal(self):
left = self.be.array([[-1, 0], [1, 92]])
right = self.be.ones([2, 2])
out = self.be.empty([2, 2])
self.be.less_equal(left, right, out)
assert out.shape == (2, 2)
assert_tensor_equal(out, CPUTensor([[1, 1], [1, 0]]))
def test_argmin_noaxis(self):
be = CPU()
tsr = be.array([[-1, 0], [1, 92]])
out = be.empty([1, 1])
be.argmin(tsr, None, out)
assert_tensor_equal(out, CPUTensor([[0]]))
def test_argmin_axis0(self):
be = CPU()
tsr = be.array([[-1, 0], [1, 92]])
out = be.empty((1, 2))
be.argmin(tsr, 0, out)
assert_tensor_equal(out, CPUTensor([[0, 0]]))
def test_argmin_axis1(self):
be = CPU()
tsr = be.array([[-1, 10], [11, 9]])
out = be.empty((2, 1))
be.argmin(tsr, 1, out)
assert_tensor_equal(out, CPUTensor([0, 1]))
def test_argmax_noaxis(self):
be = CPU()
tsr = be.array([[-1, 0], [1, 92]])
out = be.empty([1, 1])
be.argmax(tsr, None, out)
assert_tensor_equal(out, CPUTensor(3))
def test_argmax_axis0(self):
be = CPU()
tsr = be.array([[-1, 0], [1, 92]])
out = be.empty((2, ))
be.argmax(tsr, 0, out)
assert_tensor_equal(out, CPUTensor([1, 1]))
def test_argmax_axis1(self):
be = CPU()
tsr = be.array([[-1, 10], [11, 9]])
out = be.empty((2, ))
be.argmax(tsr, 1, out)
assert_tensor_equal(out, CPUTensor([1, 0]))
def test_2norm(self):
tsr = self.be.array([[-1, 0], [1, 3]])
rpow = 1. / 2
# -> sum([[1, 0], [1, 9]], axis=0)**.5 -> sqrt([2, 9])
assert_tensor_equal(self.be.norm(tsr, order=2, axis=0),
CPUTensor([[2**rpow, 9**rpow]]))
# -> sum([[1, 0], [1, 9]], axis=1)**.5 -> sqrt([1, 10])
assert_tensor_equal(self.be.norm(tsr, order=2, axis=1),
CPUTensor([1**rpow, 10**rpow]))
def test_1norm(self):
tsr = self.be.array([[-1, 0], [1, 3]])
# -> sum([[1, 0], [1, 3]], axis=0)**1 -> [2, 3]
assert_tensor_equal(self.be.norm(tsr, order=1, axis=0),
CPUTensor([[2, 3]]))
# -> sum([[1, 0], [1, 3]], axis=1)**1 -> [1, 4]
assert_tensor_equal(self.be.norm(tsr, order=1, axis=1),
CPUTensor([1, 4]))
def test_0norm(self):
tsr = self.be.array([[-1, 0], [1, 3]])
# -> sum(tsr != 0, axis=0) -> [2, 1]
assert_tensor_equal(self.be.norm(tsr, order=0, axis=0),
CPUTensor([[2, 1]]))
# -> sum(tsr != 0, axis=1) -> [1, 2]
assert_tensor_equal(self.be.norm(tsr, order=0, axis=1),
CPUTensor([1, 2]))
def test_infnorm(self):
tsr = self.be.array([[-1, 0], [1, 3]])
# -> max(abs(tsr), axis=0) -> [1, 3]
assert_tensor_equal(self.be.norm(tsr, order=float('inf'), axis=0),
CPUTensor([[1, 3]]))
# -> max(abs(tsr), axis=1) -> [1, 3]
assert_tensor_equal(self.be.norm(tsr, order=float('inf'), axis=1),
CPUTensor([1, 3]))
def test_neginfnorm(self):
tsr = self.be.array([[-1, 0], [1, 3]])
# -> min(abs(tsr), axis=0) -> [1, 0]
assert_tensor_equal(self.be.norm(tsr, order=float('-inf'), axis=0),
CPUTensor([[1, 0]]))
# -> min(abs(tsr), axis=1) -> [0, 1]
assert_tensor_equal(self.be.norm(tsr, order=float('-inf'), axis=1),
CPUTensor([0, 1]))
def test_lrgnorm(self):
tsr = self.be.array([[-1, 0], [1, 3]])
rpow = 1. / 5
# -> sum([[1, 0], [1, 243]], axis=0)**rpow -> rpow([2, 243])
assert_tensor_equal(self.be.norm(tsr, order=5, axis=0),
CPUTensor([[2**rpow, 243**rpow]]))
# -> sum([[1, 0], [1, 243]], axis=1)**rpow -> rpow([1, 244])
# 244**.2 == ~3.002465 hence the near_equal test
assert_tensor_near_equal(self.be.norm(tsr, order=5, axis=1),
CPUTensor([1**rpow, 244**rpow]), 1e-6)
def test_negnorm(self):
tsr = self.be.array([[-1, -2], [1, 3]])
rpow = -1. / 3
# -> sum([[1, .125], [1, .037037]], axis=0)**rpow -> rpow([2, .162037])
assert_tensor_equal(self.be.norm(tsr, order=-3, axis=0),
CPUTensor([[2**rpow, .162037037037**rpow]]))
# -> sum([[1, .125], [1, .037037]], axis=1)**rpow ->
# rpow([1.125, 1.037037])
assert_tensor_near_equal(self.be.norm(tsr, order=-3, axis=1),
CPUTensor([1.125**rpow, 1.037037**rpow]),
1e-6)
def test_argmax_noaxis(self):
be = CPU()
tsr = be.array([[-1, 0], [1, 92]])
out = be.empty([1, 1])
be.argmax(tsr, None, out)
assert_tensor_equal(out, CPUTensor(3))
def test_argmax_axis1(self):
be = CPU()
tsr = be.array([[-1, 10], [11, 9]])
out = be.empty((2, ))
be.argmax(tsr, 1, out)
assert_tensor_equal(out, CPUTensor([1, 0]))
def test_argmin_axis0(self):
be = CPU()
tsr = be.array([[-1, 0], [1, 92]])
out = be.empty((1, 2))
be.argmin(tsr, 0, out)
assert_tensor_equal(out, CPUTensor([[0, 0]]))
class TestCPU(object):
def __init__(self):
# this code gets called prior to each test
self.be = CPU()
def test_empty_creation(self):
tns = self.be.empty((4, 3))
assert tns.shape == (4, 3)
def test_array_creation(self):
tns = self.be.array([[1, 2], [3, 4]])
assert tns.shape == (2, 2)
assert_tensor_equal(tns, CPUTensor([[1, 2], [3, 4]]))
def test_zeros_creation(self):
tns = self.be.zeros([3, 1])
assert tns.shape == (3, 1)
assert_tensor_equal(tns, CPUTensor([[0], [0], [0]]))
def test_ones_creation(self):
tns = self.be.ones([1, 4])
assert tns.shape == (1, 4)
assert_tensor_equal(tns, CPUTensor([[1, 1, 1, 1]]))
def test_all_equal(self):
left = self.be.ones([2, 2])
right = self.be.ones([2, 2])
out = self.be.empty([2, 2])
self.be.equal(left, right, out)
assert out.shape == (2, 2)
assert_tensor_equal(out, CPUTensor([[1, 1], [1, 1]]))
def test_some_equal(self):
left = self.be.ones([2, 2])
right = self.be.array([[0, 1], [0, 1]])
out = self.be.empty([2, 2])
self.be.equal(left, right, out)
assert out.shape == (2, 2)
assert_tensor_equal(out, CPUTensor([[0, 1], [0, 1]]))
def test_none_equal(self):
left = self.be.ones([2, 2])
right = self.be.zeros([2, 2])
out = self.be.empty([2, 2])
self.be.equal(left, right, out)
assert out.shape == (2, 2)
assert_tensor_equal(out, CPUTensor([[0, 0], [0, 0]]))
def test_all_not_equal(self):
left = self.be.ones([2, 2])
right = self.be.zeros([2, 2])
out = self.be.empty([2, 2])
self.be.not_equal(left, right, out)
assert out.shape == (2, 2)
assert_tensor_equal(out, CPUTensor([[1, 1], [1, 1]]))
def test_some_not_equal(self):
left = self.be.ones([2, 2])
right = self.be.array([[0, 1], [0, 1]])
out = self.be.empty([2, 2])
self.be.not_equal(left, right, out)
assert out.shape == (2, 2)
assert_tensor_equal(out, CPUTensor([[1, 0], [1, 0]]))
def test_none_not_equal(self):
left = self.be.ones([2, 2])
right = self.be.ones([2, 2])
out = self.be.empty([2, 2])
self.be.not_equal(left, right, out)
assert out.shape == (2, 2)
assert_tensor_equal(out, CPUTensor([[0, 0], [0, 0]]))
def test_greater(self):
left = self.be.array([[-1, 0], [1, 92]])
right = self.be.ones([2, 2])
out = self.be.empty([2, 2])
self.be.greater(left, right, out)
assert out.shape == (2, 2)
assert_tensor_equal(out, CPUTensor([[0, 0], [0, 1]]))
def test_greater_equal(self):
left = self.be.array([[-1, 0], [1, 92]])
right = self.be.ones([2, 2])
out = self.be.empty([2, 2])
self.be.greater_equal(left, right, out)
assert out.shape == (2, 2)
assert_tensor_equal(out, CPUTensor([[0, 0], [1, 1]]))
def test_less(self):
left = self.be.array([[-1, 0], [1, 92]])
right = self.be.ones([2, 2])
out = self.be.empty([2, 2])
self.be.less(left, right, out)
assert out.shape == (2, 2)
assert_tensor_equal(out, CPUTensor([[1, 1], [0, 0]]))
def test_less_equal(self):
left = self.be.array([[-1, 0], [1, 92]])
right = self.be.ones([2, 2])
out = self.be.empty([2, 2])
self.be.less_equal(left, right, out)
assert out.shape == (2, 2)
assert_tensor_equal(out, CPUTensor([[1, 1], [1, 0]]))
def test_argmin_noaxis(self):
be = CPU()
tsr = be.array([[-1, 0], [1, 92]])
out = be.empty([1, 1])
be.argmin(tsr, None, out)
assert_tensor_equal(out, CPUTensor([[0]]))
def test_argmin_axis0(self):
be = CPU()
tsr = be.array([[-1, 0], [1, 92]])
out = be.empty((1, 2))
be.argmin(tsr, 0, out)
assert_tensor_equal(out, CPUTensor([[0, 0]]))
def test_argmin_axis1(self):
be = CPU()
tsr = be.array([[-1, 10], [11, 9]])
out = be.empty((2, 1))
be.argmin(tsr, 1, out)
assert_tensor_equal(out, CPUTensor([0, 1]))
def test_argmax_noaxis(self):
be = CPU()
tsr = be.array([[-1, 0], [1, 92]])
out = be.empty([1, 1])
be.argmax(tsr, None, out)
assert_tensor_equal(out, CPUTensor(3))
def test_argmax_axis0(self):
be = CPU()
tsr = be.array([[-1, 0], [1, 92]])
out = be.empty((2, ))
be.argmax(tsr, 0, out)
assert_tensor_equal(out, CPUTensor([1, 1]))
def test_argmax_axis1(self):
be = CPU()
tsr = be.array([[-1, 10], [11, 9]])
out = be.empty((2, ))
be.argmax(tsr, 1, out)
assert_tensor_equal(out, CPUTensor([1, 0]))
def test_2norm(self):
tsr = self.be.array([[-1, 0], [1, 3]])
rpow = 1. / 2
# -> sum([[1, 0], [1, 9]], axis=0)**.5 -> sqrt([2, 9])
assert_tensor_equal(self.be.norm(tsr, order=2, axis=0),
CPUTensor([[2**rpow, 9**rpow]]))
# -> sum([[1, 0], [1, 9]], axis=1)**.5 -> sqrt([1, 10])
assert_tensor_equal(self.be.norm(tsr, order=2, axis=1),
CPUTensor([1**rpow, 10**rpow]))
def test_1norm(self):
tsr = self.be.array([[-1, 0], [1, 3]])
# -> sum([[1, 0], [1, 3]], axis=0)**1 -> [2, 3]
assert_tensor_equal(self.be.norm(tsr, order=1, axis=0),
CPUTensor([[2, 3]]))
# -> sum([[1, 0], [1, 3]], axis=1)**1 -> [1, 4]
assert_tensor_equal(self.be.norm(tsr, order=1, axis=1),
CPUTensor([1, 4]))
def test_0norm(self):
tsr = self.be.array([[-1, 0], [1, 3]])
# -> sum(tsr != 0, axis=0) -> [2, 1]
assert_tensor_equal(self.be.norm(tsr, order=0, axis=0),
CPUTensor([[2, 1]]))
# -> sum(tsr != 0, axis=1) -> [1, 2]
assert_tensor_equal(self.be.norm(tsr, order=0, axis=1),
CPUTensor([1, 2]))
def test_infnorm(self):
tsr = self.be.array([[-1, 0], [1, 3]])
# -> max(abs(tsr), axis=0) -> [1, 3]
assert_tensor_equal(self.be.norm(tsr, order=float('inf'), axis=0),
CPUTensor([[1, 3]]))
# -> max(abs(tsr), axis=1) -> [1, 3]
assert_tensor_equal(self.be.norm(tsr, order=float('inf'), axis=1),
CPUTensor([1, 3]))
def test_neginfnorm(self):
tsr = self.be.array([[-1, 0], [1, 3]])
# -> min(abs(tsr), axis=0) -> [1, 0]
assert_tensor_equal(self.be.norm(tsr, order=float('-inf'), axis=0),
CPUTensor([[1, 0]]))
# -> min(abs(tsr), axis=1) -> [0, 1]
assert_tensor_equal(self.be.norm(tsr, order=float('-inf'), axis=1),
CPUTensor([0, 1]))
def test_lrgnorm(self):
tsr = self.be.array([[-1, 0], [1, 3]])
rpow = 1. / 5
# -> sum([[1, 0], [1, 243]], axis=0)**rpow -> rpow([2, 243])
assert_tensor_equal(self.be.norm(tsr, order=5, axis=0),
CPUTensor([[2**rpow, 243**rpow]]))
# -> sum([[1, 0], [1, 243]], axis=1)**rpow -> rpow([1, 244])
# 244**.2 == ~3.002465 hence the near_equal test
assert_tensor_near_equal(self.be.norm(tsr, order=5, axis=1),
CPUTensor([1**rpow, 244**rpow]), 1e-6)
def test_negnorm(self):
tsr = self.be.array([[-1, -2], [1, 3]])
rpow = -1. / 3
# -> sum([[1, .125], [1, .037037]], axis=0)**rpow -> rpow([2, .162037])
assert_tensor_equal(self.be.norm(tsr, order=-3, axis=0),
CPUTensor([[2**rpow, .162037037037**rpow]]))
# -> sum([[1, .125], [1, .037037]], axis=1)**rpow ->
# rpow([1.125, 1.037037])
assert_tensor_near_equal(self.be.norm(tsr, order=-3, axis=1),
CPUTensor([1.125**rpow, 1.037037**rpow]),
1e-6)
def test_argmax_axis1(self):
be = CPU()
tsr = be.array([[-1, 10], [11, 9]])
out = be.empty((2, ))
be.argmax(tsr, 1, out)
assert_tensor_equal(out, CPUTensor([1, 0]))
def test_argmax_noaxis(self):
be = CPU()
tsr = be.array([[-1, 0], [1, 92]])
out = be.empty([1, 1])
be.argmax(tsr, None, out)
assert_tensor_equal(out, CPUTensor(3))
def test_argmin_axis0(self):
be = CPU()
tsr = be.array([[-1, 0], [1, 92]])
out = be.empty((1, 2))
be.argmin(tsr, 0, out)
assert_tensor_equal(out, CPUTensor([[0, 0]]))