trajdl.common.samples module

trajdl.common.samples module#

class trajdl.common.samples.GMVSAESample(encoder_seq: LongTensor, encoder_lengths: List[int], decoder_seq: LongTensor | None = None, decoder_lengths: List[int] | None = None, decoder_labels: LongTensor | None = None, mask: Tensor | None = None)[source]#

Bases: object

GMVSAE的输入样本

Parameters:

  • encoder_seq (torch.LongTensor) – shape is (B, T)

  • encoder_lengths (List[int]) – length of each sequence

  • decoder_seq (Optional[torch.LongTensor], optional) – shape is (B, T + 1), each of seq added BOS, default is None

  • decoder_lengths (Optional[List[int]], optional) – encoder_lengths + 1, default is None

  • decoder_labels (Optional[torch.LongTensor], optional) – shape is (B, T + 1), each of seq added EOS, default is None

  • mask (Optional[torch.Tensor], optional) – shape is (B, T + 1), default is None

property batch_size: int#
decoder_labels: LongTensor | None = None#
decoder_lengths: List[int] | None = None#
decoder_seq: LongTensor | None = None#
encoder_lengths: List[int]#
encoder_seq: LongTensor#
mask: Tensor | None = None#
class trajdl.common.samples.STLSTMSample(loc_seq: LongTensor, td_upper_seq: LongTensor, td_lower_seq: LongTensor, sd_upper_seq: LongTensor, sd_lower_seq: LongTensor, valid_lengths: List[int], labels: LongTensor | None = None, mask: LongTensor | None = None)[source]#

Bases: object

ST-LSTM的输入样本

Parameters:

  • loc_seq (torch.LongTensor) – shape is (B, T), 位置序列

  • td_upper_seq (torch.LongTensor) – shape is (B, T), 这个是两个时间步之间的时间差被上界减去的batch

  • td_lower_seq (torch.LongTensor) – shape is (B, T), 这个是两个时间步之间的时间差减去下界的batch

  • sd_upper_seq (torch.LongTensor) – shape is (B, T), 这个是两个时间步之间的空间位移被上界减去的batch

  • sd_lower_seq (torch.LongTensor) – shape is (B, T), 这个是两个时间步之间的空间位移减去下界的batch

  • valid_lengths (List[int]) – 每条序列的实际长度

  • labels (torch.LongTensor, optional) – shape is (B, T), 训练时传入, LSTM的输出对应的标签

  • mask (torch.LongTensor, optional) – shape is (B, T), 训练时传入, LSTM的输出对应的mask, 为1表示该位置应该计算损失, 为0不计算

property batch_size: int#
labels: LongTensor | None = None#
loc_seq: LongTensor#
mask: LongTensor | None = None#
sd_lower_seq: LongTensor#
sd_upper_seq: LongTensor#
td_lower_seq: LongTensor#
td_upper_seq: LongTensor#
valid_lengths: List[int]#
class trajdl.common.samples.T2VECSample(src: LongTensor, lengths: List[int], target: LongTensor | None = None)[source]#

Bases: object

T2VEC的输入样本

Parameters:

  • src (torch.LongTensor) – shape is (batch_size, seq_length)

  • lengths (List[int]) – length of each src sequence

  • target (torch.LongTensor, optional) – shape is (batch_size, seq_length’), default is None

property batch_size: int#
lengths: List[int]#
src: LongTensor#
target: LongTensor | None = None#
class trajdl.common.samples.TULERSample(src: LongTensor, seq_len: List[int], labels: LongTensor | None = None)[source]#

Bases: object

TULER的输入样本

Parameters:

  • src (torch.LongTensor) – shape is (B, T)

  • seq_len (List[int]) – length of each sequence

  • labels (torch.LongTensor, optional) – shape is (B,), label of each sequence, default is None

property batch_size: int#
labels: LongTensor | None = None#
seq_len: List[int]#
src: LongTensor#