def _get_b(self):
common.print_func_name(self._get_b)
layer = self.weighted_layers[0]
print(self.sess.run(layer.b))
def _init_weight_values(n_inputs, n_outputs, shape):
common.print_func_name(Relu._init_weight_values)
print(shape)
w_values = tf.truncated_normal(shape=shape, stddev=1. / math.sqrt(float(shape[0])))
return w_values
def _get_b(self):
common.print_func_name(self._get_b)
layer = self.weighted_layers[0]
print(self.sess.run(layer.b))
