Cost function always returning zero for a binary classification in tensorflow

I have written the following binary classification program in tensorflow that is buggy. The cost is returning to be zero all the time no matter what the input is. I am trying to debug a larger program which is not learning anything from the data. I have narrowed down at least one bug to the cost function always returning zero. The given program is using some random inputs and is having the same problem. self.X_train and self.y_train is originally supposed to read from files and the function self.predict() has more layers forming a feedforward neural network.

import numpy as np
import tensorflow as tf

class annClassifier():

    def __init__(self):

        with tf.variable_scope("Input"):
             self.X = tf.placeholder(tf.float32, shape=(100, 11))

        with tf.variable_scope("Output"):
            self.y = tf.placeholder(tf.float32, shape=(100, 1))

        self.X_train = np.random.rand(100, 11)
        self.y_train = np.random.randint(0,2, size=(100, 1))

    def predict(self):

        with tf.variable_scope('OutputLayer'):
            weights = tf.get_variable(name='weights',
                                      shape=[11, 1],
                                      initializer=tf.contrib.layers.xavier_initializer())
            bases = tf.get_variable(name='bases',
                                    shape=[1],
                                    initializer=tf.zeros_initializer())
            final_output = tf.matmul(self.X, weights) + bases

        return final_output

    def train(self):

        prediction = self.predict()
        cost = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(logits=prediction, labels=self.y))

        with tf.Session() as sess:
            sess.run(tf.global_variables_initializer())         
            print(sess.run(cost, feed_dict={self.X:self.X_train, self.y:self.y_train}))


with tf.Graph().as_default():
    classifier = annClassifier()
    classifier.train()

If someone could please figure out what I am doing wrong in this, I can try making the same change in my original program. Thanks a lot!