def get_forward_output(self):
X=self.get_input()
[h,c], _ = theano.scan(self._fstep,
sequences = X,
outputs_info = [alloc_zeros_matrix(self.n_hidden),
alloc_zeros_matrix(self.n_hidden)])
# outputs_info =T.unbroadcast(alloc_zeros_matrix(self.input.shape[0],
# self.n_hidden), 0) )
return h
def get_output(self):
X=self.get_input()
[h,c], _ = theano.scan(self._step,
sequences = X,
outputs_info = [alloc_zeros_matrix(self.input.shape[1],
self.n_hidden),
alloc_zeros_matrix(self.input.shape[1],
self.n_hidden)])
return h
def get_output(self):
X = self.get_input()
[h, c], _ = theano.scan(self._step,
sequences=X,
outputs_info=[
alloc_zeros_matrix(self.input.shape[1],
self.n_hidden),
alloc_zeros_matrix(self.input.shape[1],
self.n_hidden)
])
return h
def get_forward_output(self):
X=self.get_input()
mask_x=self.x_mask
h, _ = theano.scan(self._fstep,
sequences = [X,mask_x],
outputs_info = alloc_zeros_matrix(self.input.shape[1],
self.n_hidden))
return h
def get_forward_output(self):
X = self.get_input()
mask_x = self.x_mask
h, _ = theano.scan(self._fstep,
sequences=[X, mask_x],
outputs_info=alloc_zeros_matrix(
self.input.shape[1], self.n_hidden))
return h
def get_output(self):
X=self.get_input()
h, _ = theano.scan(self._step,
sequences = X,
outputs_info = alloc_zeros_matrix(self.n_hidden))
# outputs_info =T.unbroadcast(alloc_zeros_matrix(self.input.shape[0],
# self.n_hidden), 0) )
# outputs_info = [T.unbroadcast(T.alloc(self.h0_tm1,
#self.n_layers,self.n_hidden),0),])
return h