Hi,

I had to initialise random tensor of specific shapes for X, W, b and compute Y. I did not change the order of initialisation which was given as X, W, b, Y. I initialised X, W,b as constant. Computed Y by adding b and product of W,X. The results are not matching. Please help.

Also, @RohanD, note the difference between `tf.constant`

and `tf.Variable`

.

As the hint in the assignment points out:

`Note that the difference between tf.constant and tf.Variable is that you can modify the state of a tf.Variable but cannot change the state of a tf.constant.`

Think about which of X,W,b,Y change, and which ones do not, throughout the training process.

Oh my god!!! Thank you so much. I do have a question now though, why don’t we use rand for initialising our W matrix? Since it initialises over 0 to 1, it should be valid right? I say this because in previous assignments we multiplied each element in the W matrix with 0.01 to keep it small.

Yes got it, I changed my W and b ‘constant’ initialization after I corrected the mistake in my code. Thank you so much for quick help!

Glad it worked!

Assuming the effect of weight initialization in neural networks is clear, the only reason `rand`

fails here is because it generates values different from those expected by the grader (the assignment specifically asks you to use `randn`

)

Good luck with the rest of the assignments!

Thank you. Randn and rand is a source of errors. Not the first time.