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Use LambdaLayer from ProtoTorch

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This commit is contained in:
Jensun Ravichandran 2021-05-31 16:53:04 +02:00
parent 8f4d66edf1
commit 27eccf44d4
2 changed files with 18 additions and 22 deletions
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20
examples/dynamic_components.py
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@ -47,17 +47,25 @@ if __name__ == "__main__":
prototype_initializer=pt.components.SMI(train_ds), prototype_initializer=pt.components.SMI(train_ds),
) )
# Summary
print(model)
# Callbacks # Callbacks
vis = pt.models.VisGLVQ2D(train_ds) vis = pt.models.VisGLVQ2D(train_ds)
proto_scheduler = PrototypeScheduler(train_ds, 10) proto_scheduler = PrototypeScheduler(train_ds, 10)
# Setup trainer # Setup trainer
trainer = pl.Trainer.from_argparse_args(args, trainer = pl.Trainer.from_argparse_args(
max_epochs=100, args,
callbacks=[vis, proto_scheduler], max_epochs=100,
terminate_on_nan=True, callbacks=[
weights_summary=None, vis,
accelerator='ddp') proto_scheduler,
],
terminate_on_nan=True,
weights_summary=None,
accelerator="ddp",
)
# Training loop # Training loop
trainer.fit(model, train_loader) trainer.fit(model, train_loader)

20
prototorch/models/glvq.py
View File

@ -9,23 +9,11 @@ from prototorch.functions.distances import (euclidean_distance, omega_distance,
sed) sed)
from prototorch.functions.helper import get_flat from prototorch.functions.helper import get_flat
from prototorch.functions.losses import glvq_loss, lvq1_loss, lvq21_loss from prototorch.functions.losses import glvq_loss, lvq1_loss, lvq21_loss
from prototorch.modules import LambdaLayer
from .abstract import AbstractPrototypeModel, PrototypeImageModel from .abstract import AbstractPrototypeModel, PrototypeImageModel
class FunctionLayer(torch.nn.Module):
def __init__(self, distance_fn):
super().__init__()
self.fn = distance_fn
self.name = distance_fn.__name__
def forward(self, *args, **kwargs):
return self.fn(*args, **kwargs)
def extra_repr(self):
return self.name
class GLVQ(AbstractPrototypeModel): class GLVQ(AbstractPrototypeModel):
"""Generalized Learning Vector Quantization.""" """Generalized Learning Vector Quantization."""
def __init__(self, hparams, **kwargs): def __init__(self, hparams, **kwargs):
@ -46,9 +34,9 @@ class GLVQ(AbstractPrototypeModel):
distribution=self.hparams.distribution, distribution=self.hparams.distribution,
initializer=self.prototype_initializer(**kwargs)) initializer=self.prototype_initializer(**kwargs))
self.distance_layer = FunctionLayer(distance_fn) self.distance_layer = LambdaLayer(distance_fn)
self.transfer_layer = FunctionLayer(tranfer_fn) self.transfer_layer = LambdaLayer(tranfer_fn)
self.loss = FunctionLayer(glvq_loss) self.loss = LambdaLayer(glvq_loss)
self.optimizer = kwargs.get("optimizer", torch.optim.Adam) self.optimizer = kwargs.get("optimizer", torch.optim.Adam)