libcity.model.road_representation.LINE

class libcity.model.road_representation.LINE.LINE(config, data_feature)

Bases: libcity.model.abstract_traffic_state_model.AbstractTrafficStateModel

calculate_loss(batch)

输入一个batch的数据，返回训练过程的loss，也就是需要定义一个loss函数

Parameters

batch (Batch) – a batch of input

Returns

return training loss

Return type

torch.tensor

forward(I, J)

Parameters

• I – origin indices of node i ; (B,)

• J – origin indices of node j ; (B,)

Returns

[u_j^T * u_i for (i,j) in zip(I, J)]; (B,) elif order == ‘second’:

[u’_j^T * v_i for (i,j) in zip(I, J)]; (B,)

Return type

if order == ‘first’

training: bool

class libcity.model.road_representation.LINE.LINE_FIRST(num_nodes, output_dim)

Bases: torch.nn.modules.module.Module

forward(i, j)

Parameters

• i – indices of i; (B,)

• j – indices of j; (B,)

Returns

v_i^T * v_j; (B,)

get_embeddings()

training: bool

class libcity.model.road_representation.LINE.LINE_SECOND(num_nodes, output_dim)

Bases: torch.nn.modules.module.Module

forward(I, J)

Parameters

• I – indices of i; (B,)

• J – indices of j; (B,)

Returns

[v_i^T * u_j for (i,j) in zip(I,J)]; (B,)

get_embeddings()

training: bool