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Stanislaw Adaszewski
4 years ago
1 changed files with 6 additions and 6 deletions
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+ 6
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tests/icosagon/test_declayer.py
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| @@ -102,17 +102,17 @@ def test_decode_layer_03(): | |||||
| def test_decode_layer_04(): | def test_decode_layer_04(): | ||||
| d = Data() | d = Data() | ||||
| d.add_node_type('Dummy', 100) | d.add_node_type('Dummy', 100) | ||||
| assert len(d.relation_types[0, 0]) == 0 | |||||
| assert len(d.relation_families) == 0 | |||||
| prep_d = prepare_training(d, TrainValTest(.8, .1, .1)) | prep_d = prepare_training(d, TrainValTest(.8, .1, .1)) | ||||
| in_layer = OneHotInputLayer(d) | in_layer = OneHotInputLayer(d) | ||||
| d_layer = DecagonLayer(in_layer.output_dim, 32, d) | d_layer = DecagonLayer(in_layer.output_dim, 32, d) | ||||
| dec_layer = DecodeLayer(input_dim=d_layer.output_dim, data=prep_d, keep_prob=1., | |||||
| decoder_class=DEDICOMDecoder, activation=lambda x: x) | |||||
| dec_layer = DecodeLayer(input_dim=d_layer.output_dim, data=prep_d, | |||||
| keep_prob=1., activation=lambda x: x) | |||||
| seq = torch.nn.Sequential(in_layer, d_layer, dec_layer) | seq = torch.nn.Sequential(in_layer, d_layer, dec_layer) | ||||
| pred_adj_matrices = seq(None) | |||||
| pred = seq(None) | |||||
| assert isinstance(pred_adj_matrices, dict) | |||||
| assert len(pred_adj_matrices) == 0 | |||||
| assert isinstance(pred, Predictions) | |||||
| assert len(pred.relation_families) == 0 | |||||