def test_fftn_multiple_plan_error(self, dtype):
import cupy
import cupyx.scipy.fftpack as fftpack
x = testing.shaped_random(self.shape, cupy, dtype)
# hack: avoid testing the cases when getting a cuFFT plan is impossible
if _default_plan_type(x, s=self.s, axes=self.axes) != 'nd':
return
plan = fftpack.get_fft_plan(x, shape=self.s, axes=self.axes)
with pytest.raises(RuntimeError) as ex, plan:
fftpack.fftn(x, shape=self.s, axes=self.axes, plan=plan)
assert 'Use the cuFFT plan either as' in str(ex.value)
def test_default_plan_type(self, enable_nd):
# test cases where nd CUFFT plan is possible
ca = cupy.ones((16, 16, 16))
for axes in [(0, 1), (1, 2), None, (0, 1, 2)]:
plan_type = _default_plan_type(ca, axes=axes)
if enable_nd:
self.assertEqual(plan_type, 'nd')
else:
self.assertEqual(plan_type, '1d')
# only a single axis is transformed -> 1d plan preferred
for axes in [(0, ), (1, ), (2, )]:
self.assertEqual(_default_plan_type(ca, axes=axes), '1d')
# non-contiguous axes -> nd plan not possible
self.assertEqual(_default_plan_type(ca, axes=(0, 2)), '1d')
# >3 axes transformed -> nd plan not possible
ca = cupy.ones((2, 4, 6, 8))
self.assertEqual(_default_plan_type(ca), '1d')
# first or last axis not included -> nd plan not possible
self.assertEqual(_default_plan_type(ca, axes=(1, )), '1d')
def test_ifftn_plan(self, xp, scp, dtype):
x = testing.shaped_random(self.shape, xp, dtype)
# hack: avoid testing the cases when getting a cuFFT plan is impossible
if _default_plan_type(x, s=self.s, axes=self.axes) != 'nd':
return x
if scp is cupyx.scipy:
import cupy.fft.config as config
config.enable_nd_planning = False # use explicit plan
plan = scp.fftpack.get_fft_plan(x, shape=self.s, axes=self.axes)
out = scp.fftpack.ifftn(x, shape=self.s, axes=self.axes, plan=plan)
config.enable_nd_planning = True # default
else: # scipy
out = scp.fftpack.ifftn(x, shape=self.s, axes=self.axes)
return out
def test_fftn_orders(self, dtype, enable_nd):
for order in ['C', 'F']:
a = testing.shaped_random(self.shape, cupy, dtype)
if order == 'F':
a = cupy.asfortranarray(a)
out = cupy.fft.fftn(a, s=self.s, axes=self.axes)
plan_type = _default_plan_type(a, s=self.s, axes=self.axes)
if plan_type == 'nd':
# nd plans have output with contiguity matching the input
self.assertEqual(out.flags.c_contiguous, a.flags.c_contiguous)
self.assertEqual(out.flags.f_contiguous, a.flags.f_contiguous)
else:
# 1d planning case doesn't guarantee preserved contiguity
pass
def test_ifftn_plan_manager(self, xp, scp, dtype):
x = testing.shaped_random(self.shape, xp, dtype)
# hack: avoid testing the cases when getting a cuFFT plan is impossible
if _default_plan_type(x, s=self.s, axes=self.axes) != 'nd':
return x
if scp is cupyx.scipy:
from cupy.cuda.cufft import get_current_plan
plan = scp.fftpack.get_fft_plan(x, shape=self.s, axes=self.axes)
with plan:
assert id(plan) == id(get_current_plan())
out = scp.fftpack.ifftn(x, shape=self.s, axes=self.axes)
assert get_current_plan() is None
else: # scipy
out = scp.fftpack.ifftn(x, shape=self.s, axes=self.axes)
return out
