def sampleCatBNN(weights, n_hid):
""" return a sample from weights of a categorical BNN """
wTilde = sampleBNN(weights, n_hid)
meanW, meanB = weights['Wout_mean'], weights['bout_mean']
logvarW, logvarB = weights['Wout_logvar'], weights['bout_logvar']
wTilde['Wout'], wTilde['bout'] = tf.squeeze(
dgm.sampleNormal(meanW, logvarW, 1),
0), tf.squeeze(dgm.sampleNormal(meanB, logvarB, 1), 0)
return wTilde
def sampleBNN(weights, n_hid):
""" sample weights from a variational approximation """
wTilde = {}
for layer in range(len(n_hid)):
wName, bName = 'W' + str(layer), 'b' + str(layer)
meanW, meanB = weights['W' + str(layer) +
'_mean'], weights['b' + str(layer) + '_mean']
logvarW, logvarB = weights['W' + str(layer) +
'_logvar'], weights['b' + str(layer) +
'_logvar']
wTilde[wName], wTilde[bName] = tf.squeeze(
dgm.sampleNormal(meanW, logvarW, 1),
0), tf.squeeze(dgm.sampleNormal(meanB, logvarB, 1), 0)
return wTilde
def sample_z(self, x, y, n_samples=None):
if n_samples == None:
n_samples = self.mc_samples
l_qz_in = tf.concat([x, y], axis=-1)
z_mean = dgm.forwardPass(self.q_z_xy_mean, l_qz_in)
z_log_var = dgm.forwardPass(self.q_z_xy_log_var, l_qz_in)
return z_mean, z_log_var, dgm.sampleNormal(z_mean, z_log_var,
n_samples)
def sample_a(self, x, n_samples=None):
if n_samples == None:
n_samples = self.mc_samples
l_qa_in = x
a_mean = dgm.forwardPass(self.q_a_x_mean, l_qa_in)
a_log_var = dgm.forwardPass(self.q_a_x_log_var, l_qa_in)
return a_mean, a_log_var, dgm.sampleNormal(a_mean, a_log_var,
n_samples)
def sample_z(self, x, y, a, n_samples=None):
if n_samples == None:
n_samples = 1
l_qz_in = tf.reshape(tf.concat([x, y, a], axis=-1),
[-1, self.n_x + self.n_y + self.n_a])
z_mean = dgm.forwardPass(self.q_z_axy_mean, l_qz_in)
z_log_var = dgm.forwardPass(self.q_z_axy_log_var, l_qz_in)
z = dgm.sampleNormal(z_mean, z_log_var, mc_samps=n_samples)
z_mean, z_log_var = tf.reshape(
z_mean, [self.mc_samples, -1, self.n_z]), tf.reshape(
z_log_var, [self.mc_samples, -1, self.n_z])
z = tf.reshape(z, [self.mc_samples, -1, self.n_z])
return z_mean, z_log_var, z