The size of the embedding weight tensor is (Vocab size,Embedding Size), but according to the docs 8 the embedding layer takes input of shape (batch_size, words) where each element is the index of a word, and produces output of shape (batch_size, words, embedding_size) where each word index has been replaced by the corresponding embedding vector.
Basically, the embedding is applied individually to each word of the input.