def create_model(self, config):
sparse_feature_number = config.get(
"hyper_parameters.sparse_feature_number")
sparse_feature_dim = config.get("hyper_parameters.sparse_feature_dim")
fc_sizes = config.get("hyper_parameters.fc_sizes")
rank_model = net.DNNLayer(sparse_feature_number, sparse_feature_dim,
fc_sizes)
return rank_model
def create_model(self, config):
sparse_feature_number = config.get(
"hyper_parameters.sparse_feature_number")
sparse_feature_dim = config.get("hyper_parameters.sparse_feature_dim")
fc_sizes = config.get("hyper_parameters.fc_sizes")
sparse_fea_num = config.get('hyper_parameters.sparse_fea_num')
dense_feature_dim = config.get('hyper_parameters.dense_input_dim')
sparse_input_slot = config.get('hyper_parameters.sparse_inputs_slots')
dnn_model = net.DNNLayer(sparse_feature_number, sparse_feature_dim,
dense_feature_dim, sparse_input_slot - 1,
fc_sizes)
return dnn_model