def __init__(self, config):
super().__init__()
self.lstm_pooling = config['lstm_pooling']
self.lstm_encoder = define_lstm_encoder()(config)
self.gnn_name = config['gnn_name']
self.gnn_encoder = define_ns_gnn_encoder(config['gnn_name'])(config)
self.last_act = get_act_fn(config['final_act_fn'])
self.lstm_out = nn.Linear(config['lstm_last_ts_dim'],
config['out_dim'])
self._initialize_weights()
def __init__(self, config):
super().__init__()
self.lstm_encoder = DynamicLSTM(config)
self.flat_after = config['flat_after']
fc_in_dim = config['lstm_outdim']
if self.flat_after:
flat_dim = config['flat_nhid'] if config[
'flat_nhid'] is not None else config['num_flat_feats']
self.flat_fc = nn.Linear(config['num_flat_feats'], flat_dim)
fc_in_dim += flat_dim
self.out_layer = nn.Linear(fc_in_dim, config['out_dim'])
self.drop = nn.Dropout(config['main_dropout'])
self.last_act = get_act_fn(config['final_act_fn'])
self._initialize_weights()
def __init__(self, config):
super().__init__()
self.gnn_encoder = define_gnn_encoder(config['gnn_name'])(config)
self.last_act = get_act_fn(config['final_act_fn'])
# where to put the flat features
# self.flat_before = config['add_flat'] and config['flat_first'] (done in GraphDataset)
self.flat_after = config['flat_after']
if self.flat_after:
flat_dim = config['flat_nhid'] if config[
'flat_nhid'] is not None else config['num_flat_feats']
self.flat_fc = nn.Linear(config['num_flat_feats'], flat_dim)
fc_in_dim = config['gnn_outdim'] + flat_dim
self.out_layer = nn.Linear(fc_in_dim, config['out_dim'])
self.drop = nn.Dropout(config['main_dropout'])
self._initialize_weights()
def __init__(self, config):
super().__init__()
self.lstm_encoder = define_lstm_encoder()(config)
self.gnn_encoder = define_gnn_encoder(config['gnn_name'])(config)
self.k = config['dg_k']
self.flat_after, self.add_lstm, fc_in_dim, flat_dim = determine_fc_in_dim(
config)
if self.flat_after:
self.flat_fc = nn.Linear(config['num_flat_feats'], flat_dim)
if self.flat_after or self.add_lstm:
self.out_layer = nn.Linear(fc_in_dim, config['num_cls'])
self.last_act = get_act_fn(config['final_act_fn'])
self.drop = nn.Dropout(config['main_dropout'])
self.lstm_out = nn.Linear(config['lstm_last_ts_dim'],
config['out_dim'])
self._initialize_weights()
def __init__(self, config):
super().__init__()
self.gnn_encoder = define_ns_gnn_encoder(config['gnn_name'])(config)
self.last_act = get_act_fn(config['final_act_fn'])
self._initialize_weights()