Tensorflow Calculate error for a single neuron I'm required to be able to calculate the error on a given neuron in a neural network using Tensorflow.

Using this :

mse = tf.reduce_mean(tf.squared_difference(out, Y))
opt = tf.train.GradientDescentOptimizer(0.1).minimize(mse)


i just get the updated weight, how i can get or calculate the error for each neuron in my network.

Thanks for the replies.
Easy, you have already done it.

mse = tf.reduce_mean(tf.squared_difference(out, Y))

This command means you are taking the mean of all the neurons over all the examples.

error = tf.squared_difference(out, Y)

This command will give you the error over all neurons over all examples. But make sure you calculate against the correct axes.