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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def load(pathtovector, wordlist=(), num_to_load=None, truncate_embeddings=None, unk_word=None, sep=" "):
 r""" Read a file in word2vec .txt format. The load function will raise a ValueError when trying to load items which do not conform to line lengths. Parameters pathtovector : string The path to the vector file. header : bool Whether the vector file has a header of the type (NUMBER OF ITEMS, SIZE OF VECTOR). wordlist : iterable, optional, default () A list of words you want loaded from the vector file. If this is None (default), all words will be loaded. num_to_load : int, optional, default None The number of items to load from the file. Because loading can take some time, it is sometimes useful to onlyl load the first n items from a vector file for quick inspection. truncate_embeddings : int, optional, default None If this value is not None, the vectors in the vector space will be truncated to the number of dimensions indicated by this value. unk_word : object The object to treat as UNK in your vector space. If this is not in your items dictionary after loading, we add it with a zero vector. Returns ------- r : Reach An initialized Reach instance. """

        vectors, items = Reach._load(pathtovector,
                                     wordlist,
                                     num_to_load,
                                     truncate_embeddings,
                                     sep)
        if unk_word is not None:
            if unk_word not in set(items):
                unk_vec = np.zeros((1, vectors.shape[1]))
                vectors = np.concatenate([unk_vec, vectors], 0)
                items = [unk_word] + items
                unk_index = 0
            else:
                unk_index = items.index(unk_word)
        else:
            unk_index = None

        return Reach(vectors,
                     items,
                     name=os.path.split(pathtovector)[-1],
                     unk_index=unk_index)