ConvEInteraction
- class ConvEInteraction(input_channels=None, output_channels=32, embedding_height=None, embedding_width=None, kernel_height=3, kernel_width=3, input_dropout=0.2, output_dropout=0.3, feature_map_dropout=0.2, embedding_dim=200, apply_batch_normalization=True)[source]
Bases:
pykeen.nn.modules.FunctionalInteraction
[torch.FloatTensor
,torch.FloatTensor
,Tuple
[torch.FloatTensor
,torch.FloatTensor
]]A stateful module for the ConvE interaction function.
Initializes internal Module state, shared by both nn.Module and ScriptModule.
Attributes Summary
Methods Summary
func
(r, t, t_bias, input_channels, ...)Evaluate the ConvE interaction function.
Attributes Documentation
- tail_entity_shape = ('d', '')
Methods Documentation
- func(r, t, t_bias, input_channels, embedding_height, embedding_width, hr2d, hr1d)
Evaluate the ConvE interaction function.
- Parameters
h (
FloatTensor
) – shape: (*batch_dims, dim) The head representations.r (
FloatTensor
) – shape: (*batch_dims, dim) The relation representations.t (
FloatTensor
) – shape: (*batch_dims, dim) The tail representations.t_bias (
FloatTensor
) – shape: (*batch_dims) The tail entity bias.input_channels (
int
) – The number of input channels.embedding_height (
int
) – The height of the reshaped embedding.embedding_width (
int
) – The width of the reshaped embedding.hr2d (
Module
) – The first module, transforming the 2D stacked head-relation “image”.hr1d (
Module
) – The second module, transforming the 1D flattened output of the 2D module.
- Return type
FloatTensor
- Returns
shape: batch_dims The scores.