def test_irfft(self):
inputs_val = np.random.random((1, N, N)).astype('float32')
inputs = theano.shared(inputs_val)
fft = theano.gpuarray.fft.curfft(inputs)
f_fft = theano.function([], fft, mode=mode_with_gpu)
res_fft = f_fft()
m = fft.type()
ifft = theano.gpuarray.fft.cuirfft(m)
f_ifft = theano.function([m], ifft, mode=mode_with_gpu)
res_ifft = f_ifft(res_fft)
utt.assert_allclose(inputs_val, np.asarray(res_ifft))
inputs_val = numpy.random.random((1, N, N, 2)).astype('float32')
inputs = theano.shared(inputs_val)
irfft = theano.gpuarray.fft.cuirfft(inputs)
f_irfft = theano.function([], irfft)
res_irfft = f_irfft()
inputs_ref = inputs_val[..., 0] + inputs_val[..., 1] * 1j
irfft_ref = np.fft.irfftn(inputs_ref, axes=(1, 2))
utt.assert_allclose(irfft_ref, res_irfft, atol=1e-4, rtol=1e-4)
def test_irfft(self):
inputs_val = np.random.random((1, N, N)).astype("float32")
inputs = theano.shared(inputs_val)
fft = theano.gpuarray.fft.curfft(inputs)
f_fft = theano.function([], fft, mode=mode_with_gpu)
res_fft = f_fft()
m = fft.type()
ifft = theano.gpuarray.fft.cuirfft(m)
f_ifft = theano.function([m], ifft, mode=mode_with_gpu)
res_ifft = f_ifft(res_fft)
utt.assert_allclose(inputs_val, np.asarray(res_ifft))
inputs_val = np.random.random((1, N, N, 2)).astype("float32")
inputs = theano.shared(inputs_val)
irfft = theano.gpuarray.fft.cuirfft(inputs)
f_irfft = theano.function([], irfft, mode=mode_with_gpu)
res_irfft = f_irfft()
inputs_ref = inputs_val[..., 0] + inputs_val[..., 1] * 1j
irfft_ref = np.fft.irfftn(inputs_ref, axes=(1, 2))
utt.assert_allclose(irfft_ref, res_irfft, atol=1e-4, rtol=1e-4)