paddlets.models.anomaly.dl._mtad_gat.attention
- class FeatOrTempAttention(feature_dim: int, in_chunk_len: int, dropout: float, alpha: int, embed_dim: Union[None, int] = None, use_gatv2: bool = True, use_bias: bool = True, name: str = 'feature')[source]
Bases:
LayerFeature/Temporal Graph Attention Layer.
- Parameters
feature_dim (int) – The number of features.
in_chunk_len (int) – The size of the loopback window, i.e. the number of time steps feed to the model.
dropout (float) – The percentage of nodes to dropout.
alpha (float) – The negative slope used in the LeakyReLU activation function.
embed_dim (None|int) – The embedding dimension (output dimension of linear transformation).
use_gatv2 (bool) – Whether to use the modified attention mechanism of GATv2 instead of standard GAT.
use_bias (bool) – whether to include a bias term in the attention layer.
name (str) – Feature or Temporal Graph.
- _feature_dim
The number of features/nodes.
- Type
int
- _in_chunk_len
The size of the loopback window, i.e. the number of time steps feed to the model.
- Type
int
- _dropout
The percentage of nodes to dropout.
- Type
float
- _alpha
The negative slope used in the LeakyReLU activation function.
- Type
float
- _embed_dim
The embedding dimension (output dimension of linear transformation).
- Type
None|int
- _use_gatv2
Whether to use the modified attention mechanism of GATv2 instead of standard GAT.
- Type
bool
- _use_bias
whether to include a bias term in the attention layer.
- Type
bool
- _name
Feature or Temporal Graph.
- Type
str
- _nodes_num
Number of nodes in a graph.
- Type
int
- _lin
The linear transformation layer.
- Type
paddle.nn.Layer
- _att
The attention parameter.
- Type
paddle.Parameter
- _bias
The bias parameter.
- Type
paddle.Parameter
- _leakyrelu
The LeakyReLU activation layer.
- Type
paddle.nn.Layer
- _sigmoid
The Sigmoid layer.
- Type
paddle.nn.Layer