# Course 5, week 1, assignment 1, exercise 6 rnn_backward

Hello dear Deeplearning.ai community.
I can’t seem to be able to get the correct results for RNN back prop. I have correct shapes of the tensors, but the values are different.
It’s written that I have to choose `da_next` and `cache` wisely.
Something tells me that I didn’t exhibit the necessary wisdom choosing them. Otherwise, I don’t see any other places where I could make a mistake.
I’m wondering if anybody can hint me at how to pick `da_next` and `cache` please.
Ivan

If anybody is interested, I found a solution.
The problem is with choosing `da_next`. Read the third bullet of the instructions provided before the exercise: " You must combine this with the loss from the previous stages when calling `rnn_cell_backward` (see figure 7 above)."
Honestly speaking, when reading the instructions I didn’t understand at all what that meant and just forgot about that.
Here are my comments that can help one to understand what that means and choose `da_next` “wisely”.
First, it refers to figure 7. But if you, actually, use figure 7 you will “combine this” with `a^<t>` instead of the “loss from the previous stages” as mentioned in the instruction (see figure 7 `da[:,;,t]` in the blue box being added to `a^<t>` coming from the right and resulting in da_next).
Second, the word “loss” in the instruction actually means derivative of the loss function with respect to `a` at the previous time step - not the loss function itself as one might think.

4 Likes

I tried this and worked!:

you can see da_next like this: da[:,:,t] + da_prevt
where da_prevt is initialized with zeros for the last rnn cell.
please consider that da_prevt is updated in each reversal iteration of “t”