Sequence feature in demo "DeepFM_with_sequence_feature.py".

[cjfcsjt]

Should field "sequence" share embeddings with the field "adgroup_id"? I found that the method "encoder.fit()" assigns the encoder such as tokenizer for each field. Since the given tiny datasets record the user historical behavior (ad sequence), then in my understanding that the id that appeared in the field "sequence" may also appear in the field "adgroup_id". As a result, it seems that the field "sequence" should share the same encoder (i.e., tokenizer) with the field "adgroup_id", but the demo "DeepFM_with_sequence_feature.py" gives separate encoders for these two fields.

[zhujiem]

Thanks for your suggestion. I have make a revision on the config to add share_embedding: "adgroup_id"

taobao_tiny_sequence:
data_root: ../data/
data_format: csv
train_data: ../data/tiny_data/train_sample.csv
valid_data: ../data/tiny_data/valid_sample.csv
test_data: ../data/tiny_data/test_sample.csv
min_categr_count: 1
feature_cols:
[{name: ["userid","adgroup_id","pid","cate_id","campaign_id","customer","brand","cms_segid",
"cms_group_id","final_gender_code","age_level","pvalue_level","shopping_level","occupation"],
active: True, dtype: str, type: categorical},
{name: "click_sequence", active: True, dtype: str, type: sequence, splitter: "^", max_len: 5,
encoder: "MaskedAveragePooling", share_embedding: "adgroup_id"}]
label_col: {name: clk, dtype: float}