(X, features, feature_columns)
| 228 | |
| 229 | |
| 230 | def get_dense_input(X, features, feature_columns): |
| 231 | dense_feature_columns = list(filter(lambda x: isinstance( |
| 232 | x, DenseFeat), feature_columns)) if feature_columns else [] |
| 233 | dense_input_list = [] |
| 234 | for fc in dense_feature_columns: |
| 235 | lookup_idx = np.array(features[fc.name]) |
| 236 | input_tensor = X[:, lookup_idx[0]:lookup_idx[1]].float() |
| 237 | dense_input_list.append(input_tensor) |
| 238 | return dense_input_list |
| 239 | |
| 240 | |
| 241 | def maxlen_lookup(X, sparse_input_dict, maxlen_column): |