def step(self, x, states):
h, [h, c] = super(AttentionLSTM, self).step(x, states)
attention = states[4]
m = K.tanh(K.dot(h, self.U_a) + attention + self.b_a)
s = K.exp(K.dot(m, self.U_s) + self.b_s)
h = h * s
return h, [h, c]
def step(self, x, states):
h, [h, c] = super(AttentionLSTM, self).step(x, states)
attention = states[4]
m = K.tanh(K.dot(h, self.U_a) + attention + self.b_a)
s = K.exp(K.dot(m, self.U_s) + self.b_s)
h = h * s
return h, [h, c]
def get_constants(self, x):
constants = super(AttentionLSTM, self).get_constants(x)
constants.append(K.dot(self.attentionvec, self.U_m) + self.b_m)
return constants
def get_constants(self, x):
constants = super(AttentionLSTM, self).get_constants(x)
constants.append(K.dot(self.attentionvec, self.U_m) + self.b_m)
return constants