def create_model(self, shared_rep):
# shared_rep: do query and response share representation layer?
metadata = self.data_handler.metadata
model_config = QueryDocumentPairwiseRankingModel_Deprecated.Config()
model_config.representation = QueryDocumentPairwiseRankingRep.Config()
model_config.representation.shared_representations = shared_rep
model_config.decoder = MLPDecoderQueryResponse.Config()
model_config.decoder.hidden_dims = [64]
model_config.output_layer = PairwiseRankingOutputLayer.Config()
feat_config = ModelInputConfig()
feat_config.pos_response = WordFeatConfig()
feat_config.pos_response.embed_dim = 64
feat_config.neg_response = WordFeatConfig()
feat_config.query = WordFeatConfig()
return QueryDocumentPairwiseRankingModel_Deprecated.from_config(
model_config, feat_config, metadata)
def setUp(self):
simple_featurizer_config = SimpleFeaturizer.Config()
simple_featurizer_config.split_regex = r""
simple_featurizer_config.convert_to_bytes = True
self.data_handler = QueryDocumentPairwiseRankingDataHandler.from_config(
QueryDocumentPairwiseRankingDataHandler.Config(),
ModelInputConfig(),
[],
featurizer=SimpleFeaturizer.from_config(simple_featurizer_config,
FeatureConfig()),
)
def setup_data(self):
simple_featurizer_config = SimpleFeaturizer.Config()
simple_featurizer_config.split_regex = r""
simple_featurizer_config.convert_to_bytes = True
self.data_handler = QueryDocumentPairwiseRankingDataHandler.from_config(
QueryDocumentPairwiseRankingDataHandler.Config(),
ModelInputConfig(),
[],
featurizer=SimpleFeaturizer.from_config(simple_featurizer_config,
FeatureConfig()),
)
self.file_name = tests_module.test_file(
"query_document_pairwise_ranking_tiny.tsv")
self.data_handler.shuffle = False
self.data_handler.init_metadata_from_path(self.file_name,
self.file_name,
self.file_name)