def connect(self, l_in):
self.l_in = l_in
self.n_in = l_in.size
self.h0 = shared0s((1, self.size))
self.w_z = self.init((self.n_in, self.size))
self.w_r = self.init((self.n_in, self.size))
self.u_z = self.init((self.size, self.size))
self.u_r = self.init((self.size, self.size))
self.b_z = shared0s((self.size))
self.b_r = shared0s((self.size))
if 'maxout' in self.activation_str:
self.w_h = self.init((self.n_in, self.size*2))
self.u_h = self.init((self.size, self.size*2))
self.b_h = shared0s((self.size*2))
else:
self.w_h = self.init((self.n_in, self.size))
self.u_h = self.init((self.size, self.size))
self.b_h = shared0s((self.size))
self.params = [self.h0, self.w_z, self.w_r, self.w_h, self.u_z, self.u_r, self.u_h, self.b_z, self.b_r, self.b_h]
if self.weights is not None:
for param, weight in zip(self.params, self.weights):
param.set_value(floatX(weight))
def connect(self, l_in):
self.l_in = l_in
self.n_in = l_in.size
self.w_i = self.init((self.n_in, self.size))
self.w_f = self.init((self.n_in, self.size))
self.w_o = self.init((self.n_in, self.size))
self.w_c = self.init((self.n_in, self.size))
self.b_i = shared0s((self.size))
self.b_f = shared0s((self.size))
self.b_o = shared0s((self.size))
self.b_c = shared0s((self.size))
self.u_i = self.init((self.size, self.size))
self.u_f = self.init((self.size, self.size))
self.u_o = self.init((self.size, self.size))
self.u_c = self.init((self.size, self.size))
self.params = [self.w_i, self.w_f, self.w_o, self.w_c,
self.u_i, self.u_f, self.u_o, self.u_c,
self.b_i, self.b_f, self.b_o, self.b_c]
if self.weights is not None:
for param, weight in zip(self.params, self.weights):
param.set_value(floatX(weight))
def connect(self, l_in):
self.l_in = l_in
self.n_in = l_in.size
self.h0 = shared0s((1, self.size))
self.w_z = self.init((self.n_in, self.size))
self.w_r = self.init((self.n_in, self.size))
self.u_z = self.init((self.size, self.size))
self.u_r = self.init((self.size, self.size))
self.b_z = shared0s((self.size))
self.b_r = shared0s((self.size))
if 'maxout' in self.activation_str:
self.w_h = self.init((self.n_in, self.size * 2))
self.u_h = self.init((self.size, self.size * 2))
self.b_h = shared0s((self.size * 2))
else:
self.w_h = self.init((self.n_in, self.size))
self.u_h = self.init((self.size, self.size))
self.b_h = shared0s((self.size))
self.params = [
self.h0, self.w_z, self.w_r, self.w_h, self.u_z, self.u_r,
self.u_h, self.b_z, self.b_r, self.b_h
]
if self.weights is not None:
for param, weight in zip(self.params, self.weights):
param.set_value(floatX(weight))
def connect(self, l_in):
self.l_in = l_in
self.n_in = l_in.size
self.w_i = self.init((self.n_in, self.size))
self.w_f = self.init((self.n_in, self.size))
self.w_o = self.init((self.n_in, self.size))
self.w_c = self.init((self.n_in, self.size))
self.b_i = shared0s((self.size))
self.b_f = shared0s((self.size))
self.b_o = shared0s((self.size))
self.b_c = shared0s((self.size))
self.u_i = self.init((self.size, self.size))
self.u_f = self.init((self.size, self.size))
self.u_o = self.init((self.size, self.size))
self.u_c = self.init((self.size, self.size))
self.params = [
self.w_i, self.w_f, self.w_o, self.w_c, self.u_i, self.u_f,
self.u_o, self.u_c, self.b_i, self.b_f, self.b_o, self.b_c
]
if self.weights is not None:
for param, weight in zip(self.params, self.weights):
param.set_value(floatX(weight))
def connect(self, l_in):
self.l_in = l_in
self.n_in = l_in.size
if 'maxout' in self.activation_str:
self.w = self.init((self.n_in, self.size*2))
self.b = shared0s((self.size*2))
else:
self.w = self.init((self.n_in, self.size))
self.b = shared0s((self.size))
self.params = [self.w, self.b]
if self.weights is not None:
for param, weight in zip(self.params, self.weights):
param.set_value(floatX(weight))
def connect(self, l_in):
self.l_in = l_in
self.n_in = l_in.size
if 'maxout' in self.activation_str:
self.w = self.init((self.n_in, self.size * 2))
self.b = shared0s((self.size * 2))
else:
self.w = self.init((self.n_in, self.size))
self.b = shared0s((self.size))
self.params = [self.w, self.b]
if self.weights is not None:
for param, weight in zip(self.params, self.weights):
param.set_value(floatX(weight))
