# week2\_Exercise 5 - propagate **URL:** \ **Category:** Neural Networks and Deep Learning\ **Tags:** coursera-platform\ **Created:** [September 29, 2023, 7:38am UTC](https://community.deeplearning.ai/t/week2-exercise-5-propagate/458080 "2023-09-29T07:38:19Z")\ **Posts on this page:** 7\ **Page:** 1
**Author:** ![vemula\_suman](https://avatars.discourse-cdn.com/v4/letter/v/da6949/32.png) [@vemula\_suman](https://community.deeplearning.ai/u/vemula_suman)\ **Post date:** [September 29, 2023, 7:38am UTC](https://community.deeplearning.ai/t/week2-exercise-5-propagate/458080/1 "2023-09-29T07:38:19Z")
code: A=1/1+np.exp(-(np.matmul(w.T,X))+b) cost=-((np.dot(Y,np.log(A)))+(np.dot((1-Y),np.log(1-A))))/m dw=np.matmul(X,((A-Y).T)) db=np.sum(A-Y ) output: ValueError Traceback (most recent call last) in 3 X = np.array([[1., -2., -1.], [3., 0.5, -3.2]]) 4 Y = np.array([[1, 1, 0]]) ----\> 5 grads, cost = propagate(w, b, X, Y) 6 7 assert type(grads[“dw”]) == np.ndarray in propagate(w, b, X, Y) 32 # YOUR CODE STARTS HERE 33 A=1/1+np.exp(-(np.matmul(w.T,X))+b) —\> 34 cost=-((np.dot(Y,np.log(A)))+(np.dot((1-Y),np.log(1-A))))/m 35 36 # YOUR CODE ENDS HERE \< **array\_function** internals\> in dot(\*args, \*\*kwargs) ValueError: shapes (1,3) and (1,3) not aligned: 3 (dim 1) != 1 (dim 0) please help to write code and any sujjestions ---
**Author:** ![saifkhanengr](https://sea1.discourse-cdn.com/dlai/user_avatar/community.deeplearning.ai/saifkhanengr/32/152858_2.png) [@saifkhanengr](https://community.deeplearning.ai/u/saifkhanengr)\ **Post date:** [September 29, 2023, 7:44am UTC](https://community.deeplearning.ai/t/week2-exercise-5-propagate/458080/2 "2023-09-29T07:44:26Z")
In your `cost` calculation, you have to use transpose for one term, `Y` or `A`. ---
**Author:** ![vemula\_suman](https://avatars.discourse-cdn.com/v4/letter/v/da6949/32.png) [@vemula\_suman](https://community.deeplearning.ai/u/vemula_suman)\ **Post date:** [September 29, 2023, 9:51am UTC](https://community.deeplearning.ai/t/week2-exercise-5-propagate/458080/3 "2023-09-29T09:51:11Z")
![image](https://global.discourse-cdn.com/dlai/original/3X/a/c/ac8e9f0c4ed2043599b58b5c8d554af1089f461e.png) but in the given formula it is not there,please see my image ---
**Author:** ![vemula\_suman](https://avatars.discourse-cdn.com/v4/letter/v/da6949/32.png) [@vemula\_suman](https://community.deeplearning.ai/u/vemula_suman)\ **Post date:** [September 29, 2023, 10:36am UTC](https://community.deeplearning.ai/t/week2-exercise-5-propagate/458080/4 "2023-09-29T10:36:07Z")
hi Saif , but in the cost equation ,there is not matrix transpose term. ![image.png](https://global.discourse-cdn.com/dlai/original/3X/a/c/ac8e9f0c4ed2043599b58b5c8d554af1089f461e.png) Thank you very much for responding ---
**Author:** ![saifkhanengr](https://sea1.discourse-cdn.com/dlai/user_avatar/community.deeplearning.ai/saifkhanengr/32/152858_2.png) [@saifkhanengr](https://community.deeplearning.ai/u/saifkhanengr)\ **Post date:** [September 29, 2023, 2:27pm UTC](https://community.deeplearning.ai/t/week2-exercise-5-propagate/458080/5 "2023-09-29T14:27:44Z")
If you choose to use dot product, then you have to transpose one term. There are other ways too for which you don’t need transpose, like using multiply and then sum… ---
**Author:** ![vemula\_suman](https://avatars.discourse-cdn.com/v4/letter/v/da6949/32.png) [@vemula\_suman](https://community.deeplearning.ai/u/vemula_suman)\ **Post date:** [September 29, 2023, 3:25pm UTC](https://community.deeplearning.ai/t/week2-exercise-5-propagate/458080/6 "2023-09-29T15:25:33Z")
what should be the output of cost function ,wheather it is nd.array or float value. please confirm thank you ---
**Author:** ![saifkhanengr](https://sea1.discourse-cdn.com/dlai/user_avatar/community.deeplearning.ai/saifkhanengr/32/152858_2.png) [@saifkhanengr](https://community.deeplearning.ai/u/saifkhanengr)\ **Post date:** [September 30, 2023, 5:47am UTC](https://community.deeplearning.ai/t/week2-exercise-5-propagate/458080/7 "2023-09-30T05:47:39Z")
What do you think it should be? Can you see the expected output below the test cell?