def test_fft(self, backend):
x = torch.randn(2, 2, 2)
y = torch.empty_like(x)
y[0, 0, :] = x[0, 0, :] + x[0, 1, :] + x[1, 0, :] + x[1, 1, :]
y[0, 1, :] = x[0, 0, :] - x[0, 1, :] + x[1, 0, :] - x[1, 1, :]
y[1, 0, :] = x[0, 0, :] + x[0, 1, :] - x[1, 0, :] - x[1, 1, :]
y[1, 1, :] = x[0, 0, :] - x[0, 1, :] - x[1, 0, :] + x[1, 1, :]
z = backend.fft(x, direction='C2C')
assert torch.allclose(y, z)
z = backend.fft(x, direction='C2C', inverse=True)
z = z * 4.0
assert torch.allclose(y, z)
z = backend.fft(x, direction='C2R', inverse=True)
z = z * 4.0
assert z.shape == x.shape[:-1]
assert torch.allclose(y[..., 0], z)
def test_fft_exceptions(self, backend_device):
backend, device = backend_device
with pytest.raises(RuntimeError) as record:
backend.fft(torch.empty(2, 2), direction='C2R', inverse=False)
assert 'done with an inverse' in record.value.args[0]
x = torch.rand(4, 4, 1)
x = x.to(device)
with pytest.raises(TypeError) as record:
backend.fft(x)
assert 'complex' in record.value.args[0]
x = torch.randn(4, 4, 2)
x = x.to(device)
y = x[::2, ::2]
with pytest.raises(RuntimeError) as record:
backend.fft(y)
assert 'must be contiguous' in record.value.args[0]