Implement a python functionbuild_unigram_probs(unigrams, unigram_counts, total_count)which takes a list of all of the unique words in the book, a dictionary mapping unique unigrams to counts, and the total count of words in the book, and returns a new list of the probabilities of each word.

In order to do this, you should iterate through the indexes of the unigram list. Look up the count of the indexs corresponding unigram in unigram_counts, then divide the unigram count by the total_count to get the probability that the word at the same index in unigrams would be chosen at random from the book. Return the list of probabilities

def test_build_unigram_probs():

assert(build_unigram_probs(\

[ "hello", "world", "again"],

{ "hello" : 2, "world" : 2, "again" : 1 }, 5 ) == \

[ 2/5, 2/5, 1/5 ])

assert(build_unigram_probs(\

[ "hello", "and", "welcome", "to", "the", "program", ".", "we're", "happy", "have", "you"],

{ "hello" : 1, "and" : 1, "welcome" : 1, "to" : 2, "the" : 1, "program" : 1, "." : 2,

"we're" : 1, "happy" : 1, "have" : 1, "you" : 1 }, 13) == \

[ 1/13, 1/13, 1/13, 2/13, 1/13, 1/13, 2/13, 1/13, 1/13, 1/13, 1/13 ])

assert(build_unigram_probs(\

[ "this", "is", "the", "song", "that", "never", "ends", "yes", "it",

"goes", "on", "and", "my", "friends", "!", "some", "people", "started",

"singing", ",", "not", "knowing", "what", "was", "now", "they", "keep",

"forever", "just", "because", "." ],

{ "this" : 1, "is" : 1, "the" : 1, "song" : 1, "that" : 1, "never" : 1,

"ends" : 1, "yes" : 1, "it" : 4, "goes" : 1, "on" : 3, "and" : 2,

"my" : 1, "friends" : 1, "!" : 1, "some" : 1, "people" : 1,

"started" : 1, "singing" : 2, "," : 2, "not" : 1, "knowing" : 1,

"what" : 1, "was" : 1, "now" : 1, "they" : 1, "keep" : 1,

"forever" : 1, "just" : 1, "because" : 1, "." : 3 }, 41) == \

[ 1/41, 1/41, 1/41, 1/41, 1/41, 1/41, 1/41, 1/41, 4/41, 1/41, 3/41, 2/41,

1/41, 1/41, 1/41, 1/41, 1/41, 1/41, 2/41, 2/41, 1/41, 1/41, 1/41, 1/41,

1/41, 1/41, 1/41, 1/41, 1/41, 1/41, 3/41 ])

print("... done!")