(att_layer_num, dnn_hidden_units, sparse_feature_num)
| 10 | [(1, (4,), 2), (0, (4,), 2), (2, (4, 4,), 2), (1, (), 1), (1, (4,), 1)] |
| 11 | ) |
| 12 | def test_AutoInt(att_layer_num, dnn_hidden_units, sparse_feature_num): |
| 13 | # if version.parse(torch.__version__) >= version.parse("1.1.0") and len(dnn_hidden_units)==0:#todo check version |
| 14 | # return |
| 15 | model_name = "AutoInt" |
| 16 | sample_size = SAMPLE_SIZE |
| 17 | x, y, feature_columns = get_test_data( |
| 18 | sample_size, sparse_feature_num=sparse_feature_num, dense_feature_num=sparse_feature_num) |
| 19 | |
| 20 | model = AutoInt(linear_feature_columns=feature_columns, dnn_feature_columns=feature_columns, |
| 21 | att_layer_num=att_layer_num, |
| 22 | dnn_hidden_units=dnn_hidden_units, dnn_dropout=0.5, device=get_device()) |
| 23 | check_model(model, model_name, x, y) |
| 24 | |
| 25 | |
| 26 | if __name__ == "__main__": |
nothing calls this directly
no test coverage detected