How to input integer vector with Tensorflow

Question

I am implementing a kind of Neural Network, in particular a Multilayer Perceptron to detect the language of the several sentences. In particular, I am using Tensorflow in Python 3.X.

Previously, I have built a 2-gram file from several sentences in 10 languages. 2-gram file is using as input of my Neural Network. For example, a sentences like "I like footbal" could be ['1','15','3',...,'30'].

As tutorial, I am following the next.

That example is using MINST as you can see at import section:

from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets("MNIST_data/", one_hot=True)

My question is, how can I pass this vector to my Neural Network?

In the example, I can see the following statement:

batch_x, batch_y = mnist.train.next_batch(batch_size)

And, this other one:

_, c = sess.run([optimizer, cost], feed_dict={x: batch_x, y: batch_y})

There, it is difficult to understand because I can not know which is the type of batch_x and batch_y.

Ali · Accepted Answer · 2017-04-19 19:29:32Z

1

They can be in numpy or list format, but when you feed it with feed_dict, it turns to tensor object,

You can pass it by feed_dict, as sess.run([optimizer, cost], feed_dict={x: batch_x, y: batch_y})

Generally, you have data x and labels y and you want to train your network with x and calculate loss(or cost) based on y, now for training, you no need to feed whole x to network, but instead, we divide x to parts which called batch then, pick each batch and train the network (so each batch has batch_x for data and batch_y for labels), then go to next batch.

answered Apr 19, 2017 at 19:29

Ali

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1 Comment

Sergio Rodríguez Calvo Over a year ago

Thanks for your help. I understood that I have to get each sentences like integer vector (batch), and batch_x has all sentences like integer vector. I am going to use python list type of integers.

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