be65ce986a45bf2f35b5494db3fa6e993b905aeb,examples/run_multivalue_movielens_hash.py,,,#,8

Before Change

              sequence_input  // make sure the order is right

// 4.Define Model,compile and train
model = DeepFM({"sparse": sparse_feat_list,
                "sequence": sequence_feature}, task="regression")

model.compile("adam", "mse", metrics=["mse"], )
history = model.fit(model_input, data[target].values,

After Change

varlen_feature_columns = [VarLenSparseFeat("genres", 100, max_len, "mean", use_hash=True,
                                           dtype="string")]  // Notice : value 0 is for padding for sequence input feature
linear_feature_columns = fixlen_feature_columns + varlen_feature_columns
dnn_feature_columns = fixlen_feature_columns + varlen_feature_columns
feature_names = get_fixlen_feature_names(linear_feature_columns + dnn_feature_columns)

// 3.generate input data for model
fixlen_input = [data[name].values for name in feature_names]
varlen_input = [genres_list]

Instances