Change number of classes of MNIST Tensorflow - tensorflow

Question

Hi, Im trying to adapt the beginners tutorial of Tensorflow with MNIST and softmax. In the tutorial you have 10 clases (for digits 0-9).
Now, with a different dataset (EMNIST) I have 62 classes for digits and letters.
What I have in the model of the orginal example is:
x = tf.placeholder(tf.float32, [None, 784])
W = tf.Variable(tf.zeros([784, 10]))
b = tf.Variable(tf.zeros([10]))
y = tf.matmul(x, W) + b`
Where 784 stands for the total pixels of a 28x28 image and 10 is the number of classes. What I want is:
x = tf.placeholder(tf.float32, [None, 784])
W = tf.Variable(tf.zeros([784, 62]))
b = tf.Variable(tf.zeros([62]))
y = tf.matmul(x, W) + b`
For 62 classes.
But when I reach this part of the code, where the next batch is called for execution:
for _ in range(1000):
batch_xs, batch_ys = mnist.train.next_batch(100)
sess.run(train_step, feed_dict={x: batch_xs, y_: batch_ys})
I get this error...
Traceback (most recent call last):
File "calligraphy.py", line 77, in <module>
tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)
File "C:\Users\Willy Barales\Anaconda3\lib\site-packages\tensorflow\python\platform\app.py", line 48, in run
_sys.exit(main(_sys.argv[:1] + flags_passthrough))
File "calligraphy.py", line 64, in main
sess.run(train_step, feed_dict={x: batch_xs, y_: batch_ys})
File "C:\Users\Willy Barales\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 789, in run
run_metadata_ptr)
File "C:\Users\Willy Barales\Anaconda3\lib\site-packages\tensorflow\python\client\session.py", line 975, in _run
% (np_val.shape, subfeed_t.name, str(subfeed_t.get_shape())))
ValueError: Cannot feed value of shape (100, 10) for Tensor 'Placeholder_1:0', which has shape '(?, 62)'
Any ideas on how to change the dataset for this example?
Do I have to change something in the mnist.py file where .next_batch() is implemented?
As far as I know, EMNIST has the exact same format as MNIST.
Thanks in advance.
Info on the new dataset:
http://biometrics.nist.gov/cs_links/EMNIST/Readme.txt

Answer 1

All I have to do was to edit in the mnist.py file the part where the one hot vectors were created from labels, since those are the ones corresponding to batch_ys, thanks to the enlightment of Neijla.
def extract_labels(f, one_hot=False, num_classes=62)
Besides of course, changing the number of the classes in the model as I stated first in my question.