julius/prototorch_models
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[BUG] NaN when training with selection initializer

Browse Source 
How to reproduce:
Run the `glvq_spiral.py` file under `examples/`.

The error seems to occur when using a lot of prototypes in combination with the
`StratifiedSelectionInitializer`. Using only a prototype per class, or using
another initializer like the `StratifiedMeanInitializer` seems to make the
problem go away.
This commit is contained in:
Jensun Ravichandran
2021-04-29 19:09:10 +02:00
parent 8bad54fc2d
commit fef73e2fbf
2 changed files with 82 additions and 31 deletions
Download Patch File Download Diff File Expand all files Collapse all files

57
prototorch/models/callbacks/visualization.py
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@@ -261,20 +261,29 @@ class VisPointProtos(VisWeights):
self._show_and_save(epoch)
class VisGLVQ2D(pl.Callback):
class Vis2DAbstract(pl.Callback):
def __init__(self,
x_train,
y_train,
title="Prototype Visualization",
cmap="viridis"):
cmap="viridis",
show_last_only=False,
block=False):
super().__init__()
self.x_train = x_train
self.y_train = y_train
self.title = title
self.fig = plt.figure(self.title)
self.cmap = cmap
self.show_last_only = show_last_only
self.block = block
class VisGLVQ2D(Vis2DAbstract):
def on_epoch_end(self, trainer, pl_module):
if self.show_last_only:
if trainer.current_epoch != trainer.max_epochs - 1:
return
protos = pl_module.prototypes
plabels = pl_module.prototype_labels
x_train, y_train = self.x_train, self.y_train
@@ -306,22 +315,13 @@ class VisGLVQ2D(pl.Callback):
ax.contourf(xx, yy, y_pred, cmap=self.cmap, alpha=0.35)
ax.set_xlim(left=x_min + 0, right=x_max - 0)
ax.set_ylim(bottom=y_min + 0, top=y_max - 0)
plt.pause(0.1)
if not self.block:
plt.pause(0.01)
else:
plt.show(block=True)
class VisSiameseGLVQ2D(pl.Callback):
def __init__(self,
x_train,
y_train,
title="Prototype Visualization",
cmap="viridis"):
super().__init__()
self.x_train = x_train
self.y_train = y_train
self.title = title
self.fig = plt.figure(self.title)
self.cmap = cmap
class VisSiameseGLVQ2D(Vis2DAbstract):
def on_epoch_end(self, trainer, pl_module):
protos = pl_module.prototypes
plabels = pl_module.prototype_labels
@@ -361,22 +361,14 @@ class VisSiameseGLVQ2D(pl.Callback):
global_step=trainer.current_epoch,
close=False,
)
plt.pause(0.1)
if not self.block:
plt.pause(0.01)
else:
plt.show(block=True)
class VisNG2D(pl.Callback):
def __init__(self,
x_train,
y_train,
title="Neural Gas Visualization",
cmap="viridis"):
super().__init__()
self.x_train = x_train
self.y_train = y_train
self.title = title
self.fig = plt.figure(self.title)
self.cmap = cmap
class VisNG2D(Vis2DAbstract):
def on_epoch_end(self, trainer, pl_module):
protos = pl_module.prototypes
cmat = pl_module.topology_layer.cmat.cpu().numpy()
@@ -410,4 +402,7 @@ class VisNG2D(pl.Callback):
"k-",
)
plt.pause(0.01)
if not self.block:
plt.pause(0.01)
else:
plt.show(block=True)