ptls.nn.pb

All classes from ptls.nn.pb also available in ptls.nn

All classes in this module support PaddedBatch as input and output. Many modules extend torch.nn classes.

Inherited layers

Some layers are inherited from the original classes with forward reimplement. Original forward process x.payload. Result are packed to PaddedBatch. x.seq_lens passed to output PaddedBatch.

PB-layers keep original class behavioral.

Example:

x = PaddedBatch(torch.randn(4, 12, 8), torch.LongTensor([3, 12, 8]))
model = PBLinear(8, 5)
y = model(x)
assert y.payload.size() == (4, 12, 5)
help(PBLinear)

PB-layers can be used with other layers in torch.nn.Sequential

x = PaddedBatch(torch.randn(4, 12, 8), torch.LongTensor([3, 12, 8]))
model = torch.nn.Sequential(
    PBLinear(8, 5),
    PBReLU(),
    PBLinear(5, 10),
)
y = model(x)
assert y.payload.size() == (4, 12, 10)

Class mapping

Pb layer	Parent Layer
PBLinear	torch.nn.Linear
PBLayerNorm	torch.nn.LayerNorm
PBReLU	torch.nn.ReLU
PBL2Norm	ptls.nn.L2NormEncoder

Classes

See docstrings for classes.

• ptls.nn.PBLinear
• ptls.nn.PBLayerNorm
• ptls.nn.PBL2Norm
• ptls.nn.PBReLU
• ptls.nn.PBL2Norm