paddlets.models.anomaly.dl._mtad_gat.model
- class Reconstruction(in_chunk_len: int, feature_dim: int, hidden_size: int, out_dim: int, num_layers: int, dropout: float)[source]
Bases:
LayerReconstruction based Model.
- Parameters
in_chunk_len (int) – The size of the loopback window, i.e. the number of time steps feed to the model.
feature_dim (int) – The number of features.
hidden_size (int) – The hidden size.
out_dim (int) – The number of output features.
num_layers (int) – The number of layer.
dropout (float) – Dropout regularization parameter.
- _in_chunk_len
The size of the loopback window, i.e. the number of time steps feed to the model.
- Type
int
- _decoder
The gru decoder layer.
- Type
paddle.nn.Layer
- _fc
The fc layer.
- Type
paddle.nn.Layer
- class Forecasting(feature_dim: int, hidden_size: int, out_dim: int, num_layers: int, dropout: float)[source]
Bases:
LayerForecasting based Model.
- Parameters
feature_dim (int) – The number of features.
hidden_size (int) – The hidden size.
out_dim (int) – The number of output features.
num_layers (int) – The number of layer.
dropout (float) – Dropout regularization parameter.
- _layers
Dynamic graph LayerList.
- Type
paddle.nn.Sequential
- _dropout
The dropout layer.
- Type
paddle.nn.Dropout
- _relu
The relu layer.
- Type
paddle.nn.RelU