Transformer architecture question
The input dimensionality is the embedding size, which is the same as the model dimensionality, as explained in section 3.4 of the article:

3.4 Embeddings and Softmax
Similarly to other sequence transduction models, we use learned embeddings to convert the input tokens and output tokens to vectors of dimension $d_{model}$.

Therefore, the input dimensionality and the model dimensionality are the same, which makes them suitable for the residual connection.