def __init__(self, model_type, layers_setting, embed_layers_setting, input_dim, cls_dim, max_length, max_size, type_size, conditional, position_type, segment_type, sketch_embed_type, embed_pool_type, attention_norm_type, inter_activation, attention_dropout_prob, hidden_dropout_prob, output_dropout_prob):
    super(SketchVAEEncoder, self).__init__(model_type, layers_setting, embed_layers_setting, input_dim, max_length, max_size, type_size, position_type, segment_type, sketch_embed_type, embed_pool_type, attention_norm_type, inter_activation, attention_dropout_prob, hidden_dropout_prob, output_dropout_prob)
    self.conditional = conditional
    if self.conditional:
        self.cls_embedding = nn.Embedding(cls_dim, embed_layers_setting[0])
    else:
        self.cls_embedding = None
def __init__(self, model_type, layers_setting, embed_layers_setting, input_dim, cls_dim, max_length, max_size, type_size, conditional, position_type, segment_type, sketch_embed_type, embed_pool_type, attention_norm_type, inter_activation, attention_dropout_prob, hidden_dropout_prob, output_dropout_prob):
    super(SketchVAEEncoder, self).__init__(model_type, layers_setting, embed_layers_setting, input_dim, max_length, max_size, type_size, position_type, segment_type, sketch_embed_type, embed_pool_type, attention_norm_type, inter_activation, attention_dropout_prob, hidden_dropout_prob, output_dropout_prob)
    self.conditional = conditional
    if self.conditional:
        self.cls_embedding = nn.Embedding(cls_dim, embed_layers_setting[0])
    else:
        self.cls_embedding = None