I am confused about the first exercise. I ended up getting the answer correct but I do not understand conceptually why it is correct.
So the test case is initialized as. x.shape = (4, 3, 3, 2)
x ends up looking like
array([[[[ 1.62434536, -0.61175641],
[-0.52817175, -1.07296862],
[ 0.86540763, -2.3015387 ]],
[[ 1.74481176, -0.7612069 ],
[ 0.3190391 , -0.24937038],
[ 1.46210794, -2.06014071]],
[[-0.3224172 , -0.38405435],
[ 1.13376944, -1.09989127],
[-0.17242821, -0.87785842]]],
[[[ 0.04221375, 0.58281521],
[-1.10061918, 1.14472371],
[ 0.90159072, 0.50249434]],
[[ 0.90085595, -0.68372786],
[-0.12289023, -0.93576943],
[-0.26788808, 0.53035547]],
[[-0.69166075, -0.39675353],
[-0.6871727 , -0.84520564],
[-0.67124613, -0.0126646 ]]],
[[[-1.11731035, 0.2344157 ],
[ 1.65980218, 0.74204416],
[-0.19183555, -0.88762896]],
[[-0.74715829, 1.6924546 ],
[ 0.05080775, -0.63699565],
[ 0.19091548, 2.10025514]],
[[ 0.12015895, 0.61720311],
[ 0.30017032, -0.35224985],
[-1.1425182 , -0.34934272]]],
[[[-0.20889423, 0.58662319],
[ 0.83898341, 0.93110208],
[ 0.28558733, 0.88514116]],
[[-0.75439794, 1.25286816],
[ 0.51292982, -0.29809284],
[ 0.48851815, -0.07557171]],
[[ 1.13162939, 1.51981682],
[ 2.18557541, -1.39649634],
[-1.44411381, -0.50446586]]]])
I understand how 4 here would technically represent the number of training examples here, both of the 3’s represent that each of the 2 channels are 3x3. But these desired properties of the answer do not seem to be reflected in x.shape. Maybe I am misinterpreting.
Any guidance to understanding this would be amazing.