def observe_until_click(c):
"""
Generates a vector of observed documents (=1) and unobserved documents (=0)
under the assumption that the user observed all documents up to and
including the last clicked one.
:param c: The click vectors
:type c: chainer.Variable
:return: The observation vectors
:rtype: chainer.Variable
"""
return F.fliplr(F.clip(F.cumsum(F.fliplr(c), axis=1), 0.0, 1.0))
def chainer_fft_spectrogram(xr, xi, forward=True):
T, O = xr.shape
if (forward): # STFT
yr, yi = F.fft((xr, xi))
yr = F.transpose(yr[:, :int(O / 2) + 1])
yi = F.transpose(yi[:, :int(O / 2) + 1])
else: # iSTFT
xr_cnj = F.fliplr(xr[:, 1:O - 1])
xi_cnj = -F.fliplr(xi[:, 1:O - 1])
xr = F.concat((xr, xr_cnj), axis=1)
xi = F.concat((xi, xi_cnj), axis=1)
yr, yi = F.ifft((xr, xi))
yr = F.transpose(yr)
yi = F.transpose(yi)
return yr, yi
def check_forward(self, x_data):
x = chainer.Variable(x_data)
y = functions.fliplr(x)
testing.assert_allclose(y.data, numpy.fliplr(self.x))
def forward(self, inputs, device):
x, = inputs
return functions.fliplr(x),
def f(x):
y = functions.fliplr(x)
return y * y
def check_forward(self, x_data):
x = chainer.Variable(x_data)
y = functions.fliplr(x)
testing.assert_allclose(y.data, numpy.fliplr(self.x))
def f(x):
y = functions.fliplr(x)
return y * y
def forward(self, inputs, device):
x, = inputs
return functions.fliplr(x),