[🐛BUG] Context-aware recommenders not properly embedding float sequences.

[mmosc]

Hello! Thank you for this library.

Describe the bug I am running several context-aware models using several float-sequence item features. However, the results that I get are for each model always the same, irrespective of the feature loaded.

While inspecting the code of Context Aware recommenders, I noticed that float sequences are always embedded with a number of embeddings of float_seq_field_dim. However, float_seq_field_dim is always 1 for float sequences, as can be seen here and here. This means that every item is assigned the same embedding. This would explain why I get the same result, no matter which item feature I am loading.

Expected behavior The model performance should vary depending on the float seq feature used.

My guess on the origin of the problem float sequences are always embedded with a number of embeddings of 1, which means that every item is assigned the same embedding. This would explain why I get the same result, no matter which item feature I am loading.

Are my hypotheses correct? If so, I think I found a bug :)

Best, Marta