def test_sub_scalar(scalar, device, shape, dtype):
if dtype == 'bool_':
# Boolean subtract is deprecated.
return chainerx.testing.ignore()
x_np = array_utils.create_dummy_ndarray(numpy, shape, dtype)
# Implicit casting in NumPy's multiply depends on the 'casting' argument,
# which is not yet supported (ChainerX always casts).
# Therefore, we explicitly cast the scalar to the dtype of the ndarray
# before the multiplication for NumPy.
expected = x_np - numpy.dtype(dtype).type(scalar)
expected_rev = numpy.dtype(dtype).type(scalar) - x_np
x = chainerx.array(x_np)
scalar_chx = chainerx.Scalar(scalar, dtype)
chainerx.testing.assert_array_equal_ex(x - scalar, expected)
chainerx.testing.assert_array_equal_ex(x - scalar_chx, expected)
chainerx.testing.assert_array_equal_ex(scalar - x, expected_rev)
chainerx.testing.assert_array_equal_ex(scalar_chx - x, expected_rev)
chainerx.testing.assert_array_equal_ex(chainerx.subtract(x, scalar),
expected)
chainerx.testing.assert_array_equal_ex(chainerx.subtract(x, scalar_chx),
expected)
chainerx.testing.assert_array_equal_ex(chainerx.subtract(scalar, x),
expected_rev)
chainerx.testing.assert_array_equal_ex(chainerx.subtract(scalar_chx, x),
expected_rev)
def test_sub_scalar(scalar, device, shape, dtype):
if dtype == 'bool_':
# Boolean subtract is deprecated.
return chainerx.testing.ignore()
x_np = array_utils.create_dummy_ndarray(numpy, shape, dtype)
# Implicit casting in NumPy's multiply depends on the 'casting' argument,
# which is not yet supported (ChainerX always casts).
# Therefore, we explicitly cast the scalar to the dtype of the ndarray
# before the multiplication for NumPy.
expected = x_np - numpy.dtype(dtype).type(scalar)
expected_rev = numpy.dtype(dtype).type(scalar) - x_np
x = chainerx.array(x_np)
scalar_chx = chainerx.Scalar(scalar, dtype)
chainerx.testing.assert_array_equal_ex(x - scalar, expected)
chainerx.testing.assert_array_equal_ex(x - scalar_chx, expected)
chainerx.testing.assert_array_equal_ex(scalar - x, expected_rev)
chainerx.testing.assert_array_equal_ex(scalar_chx - x, expected_rev)
chainerx.testing.assert_array_equal_ex(
chainerx.subtract(x, scalar), expected)
chainerx.testing.assert_array_equal_ex(
chainerx.subtract(x, scalar_chx), expected)
chainerx.testing.assert_array_equal_ex(
chainerx.subtract(scalar, x), expected_rev)
chainerx.testing.assert_array_equal_ex(
chainerx.subtract(scalar_chx, x), expected_rev)
def test_sub_invalid_dtypes(device, dtypes, is_module):
(in_dtype1, in_dtype2), _ = dtypes
shape = (2, 3)
a = chainerx.array(array_utils.uniform(shape, in_dtype1))
b = chainerx.array(array_utils.uniform(shape, in_dtype2))
with pytest.raises(chainerx.DtypeError):
if is_module:
a - b
else:
chainerx.subtract(a, b)