nn.Embedding will output a tensor in the shape [*, H], where * is the input shape and H the embedding_dim.
Given your input shape, you’ll end up with a 4-dimensional tensor.
Could you explain a bit, in which dimension the conv layer should operate?
I.e. should the filters convole the “sentence dimension” or the “word dimension”?