def test_correct_double_backward_unary():
chainerx.check_double_backward(
lambda xs: (xs[0] * xs[0],),
(chainerx.array([1, 2, 3], chainerx.float32).require_grad(),),
(chainerx.ones((3,), chainerx.float32).require_grad(),),
(chainerx.ones((3,), chainerx.float32),),
(chainerx.full((3,), 1e-3, chainerx.float32),
chainerx.full((3,), 1e-3, chainerx.float32)),
1e-4,
1e-3,
)
def test_array_grad_invalid_grad(invalid_shape, invalid_dtype, invalid_device):
shape = (3, 1)
dtype = chainerx.float64
device = 'native:0'
array = chainerx.ones(shape, dtype, device=device)
array.require_grad()
grad_shape = shape if invalid_shape is None else invalid_shape
grad_dtype = dtype if invalid_dtype is None else invalid_dtype
grad_device = device if invalid_device is None else invalid_device
invalid_grad = chainerx.ones(grad_shape, grad_dtype, device=grad_device)
with pytest.raises(chainerx.GradientError):
array.set_grad(invalid_grad)
with pytest.raises(chainerx.GradientError):
array.grad = invalid_grad
def test_cast_scalar_invalid(device, shape):
dtype = chainerx.float32
a = chainerx.ones(shape, dtype)
with pytest.raises(chainerx.DimensionError):
float(a)
a = chainerx.ones(shape, dtype)
with pytest.raises(chainerx.DimensionError):
int(a)
a = chainerx.ones(shape, dtype)
with pytest.raises(chainerx.DimensionError):
bool(a)
a = chainerx.ones(shape, dtype)
with pytest.raises(chainerx.DimensionError):
a.item()
def test_array_grad_invalid_grad(invalid_shape, invalid_dtype, invalid_device):
shape = (3, 1)
dtype = chainerx.float64
device = 'native:0'
array = chainerx.ones(shape, dtype, device=device)
array.require_grad()
grad_shape = shape if invalid_shape is None else invalid_shape
grad_dtype = dtype if invalid_dtype is None else invalid_dtype
grad_device = device if invalid_device is None else invalid_device
invalid_grad = chainerx.ones(
grad_shape, grad_dtype, device=grad_device)
with pytest.raises(chainerx.GradientError):
array.set_grad(invalid_grad)
with pytest.raises(chainerx.GradientError):
array.grad = invalid_grad
def test_cast_scalar_invalid(device, shape):
dtype = chainerx.float32
a = chainerx.ones(shape, dtype)
with pytest.raises(chainerx.DimensionError):
float(a)
a = chainerx.ones(shape, dtype)
with pytest.raises(chainerx.DimensionError):
int(a)
a = chainerx.ones(shape, dtype)
with pytest.raises(chainerx.DimensionError):
bool(a)
a = chainerx.ones(shape, dtype)
with pytest.raises(chainerx.DimensionError):
a.item()
def test_to_device():
a = chainerx.ones((2,), chainerx.float32, device='native:0')
dst_device = chainerx.get_device('native:1')
b0 = a.to_device(dst_device) # by device instance
assert b0.device is dst_device
chainerx.testing.assert_array_equal_ex(a, b0)
b1 = a.to_device('native:1') # by device name
assert b1.device is dst_device
chainerx.testing.assert_array_equal_ex(a, b1)
b2 = a.to_device('native', 1) # by backend name and index
assert b2.device is dst_device
chainerx.testing.assert_array_equal_ex(a, b2)
def test_to_device():
a = chainerx.ones((2,), chainerx.float32, device='native:0')
dst_device = chainerx.get_device('native:1')
b0 = a.to_device(dst_device) # by device instance
assert b0.device is dst_device
chainerx.testing.assert_array_equal_ex(a, b0)
b1 = a.to_device('native:1') # by device name
assert b1.device is dst_device
chainerx.testing.assert_array_equal_ex(a, b1)
b2 = a.to_device('native', 1) # by backend name and index
assert b2.device is dst_device
chainerx.testing.assert_array_equal_ex(a, b2)
def chx_ones(*args, **kwargs):
return chx.ones(*args, **kwargs, device='cuda:0')
def test_ones_with_device(device):
a = chainerx.ones((2,), 'float32', device)
b = chainerx.ones((2,), 'float32')
array_utils.check_device(a, device)
chainerx.testing.assert_array_equal_ex(a, b)
def orig_chainerx(self, device_name):
return chainerx.ones((2, 3), numpy.float32, device=device_name)
def test_ones_with_device(device):
a = chainerx.ones((2,), 'float32', device)
b = chainerx.ones((2,), 'float32')
array_utils.check_device(a, device)
chainerx.testing.assert_array_equal_ex(a, b)
def orig_chainerx(self, device_name):
return chainerx.ones((2, 3), numpy.float32, device=device_name)
def __init__(self, size, dtype=chx.float32):
shape = size,
self.avg_mean = chx.zeros(shape, dtype)
self.avg_var = chx.zeros(shape, dtype)
self.gamma = chx.ones(shape, dtype)
self.beta = chx.zeros(shape, dtype)
def __init__(self, size, dtype=chx.float32):
shape = size,
self.avg_mean = chx.zeros(shape, dtype)
self.avg_var = chx.zeros(shape, dtype)
self.gamma = chx.ones(shape, dtype)
self.beta = chx.zeros(shape, dtype)
