In your case that the sizes are only 1, 2 or 4, the answer is quite easy:
If the knapsack has an odd size, then you pick the most valuable item of size 1 and add it to the last slot.
If the remaining knapsack has a size that is an odd multiple of two, then you pick the most valuable item of size 2, or the two most valuable items of size 1, whichever is more valuable, and put them to the last slot of size 2.
Now the remaining knapsack has a size that is a multiple of 4. You pick the most valuable item of size 4, or the two most valuable items of size 2, or the four most valuable items of size 1, or the most valuable item of size 2 plus the two most valuable items of size 1.
With other sizes, say sizes 2, 3 and 5, things will be more difficult. However, you can sort the items of each size in descending order, and can solve this using dynamic programming.
I suppose the time will be polynomial for every fixed size of weights, with the polynomial depending on the weights. But you can sort the items of each weight in descending order in O (n log n), and if there are m different weights and the size of the knapsack is K, you find the best solution easily in mW steps.
If the weights and K are large, the number of possible sums of weights may be a lot smaller than K. For example if K = 1 billion and three weights >= 100 million, there will be less than 167 possible sums of weights < K.