Encoder

class Encoder(*args, **kwargs)

Bases: Module, ABC

Return type:

Any

Implementations

class IdentityEncoder(*args, **kwargs)

Bases: Encoder

Identity encoder that returns the input graph unchanged.

\[\tilde{x} = x\]

Return type:

Any

class MLPEncoder(*args, **kwargs)

Bases: Encoder

Encoder that applies class-specific Multi Layer Perceptrons.

\[\begin{align} &\forall c \in \mathcal{C}, \forall e \in \mathcal{E}^c_x, & \tilde{x}_e = \phi_\theta^c(x_e), \end{align}\]

where \(({\phi}_{\theta}^c)_{c\in C}\) is a set of class-specific MLPs.

Parameters:

• input_structure – Input graph structure.

• hidden_sizes – Hidden sizes of MLPs \(({\phi}_{\theta}^c)_{c\in C}\).

• activation – Activation functions of MLPs \(({\phi}_{\theta}^c)_{c\in C}\).

• out_size – Output size of MLPs \(({\phi}_{\theta}^c)_{c\in C}\).

• use_bias – Whether to use bias in MLPs \(({\phi}_{\theta}^c)_{c\in C}\).

• kernel_init – Kernel initializer for MLPs \(({\phi}_{\theta}^c)_{c\in C}\).

• bias_init – Bias initializer for MLPs \(({\phi}_{\theta}^c)_{c\in C}\).

• final_activation – Final activation function for MLPs \(({\phi}_{\theta}^c)_{c\in C}\).

• seed – Seed for RNG streams for weight initialization.

Return type:

Any