You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Describe the bug
Models cannot be saved like sklearn.
if we use sklearn, it works:
import torch
from sklearn import random_projection
model = random_projection.SparseRandomProjection(eps=0.1)
torch.save(model, 'model.pkl')
in cuml it not work and give following error:
import cuml
model = cuml.random_projection.SparseRandomProjection(eps=0.1)
torch.save(model, 'model.pkl')
TypeError: self.rand_matD,self.rand_matS cannot be converted to a Python object for pickling
The text was updated successfully, but these errors were encountered:
Thanks for the issue @skyqwe123, I haven't used torch.save before with sklearn estimators, seems like it relies in pickle so this must be exposing a bug in our pickling of Spars Random Projection, so this is something we will work in but don't have an ETA currently.
@msarahan @seberg @benfred @mattf Thanks for your good job! When i use cuml, the model can not be saved like sklearn.
Describe the bug
Models cannot be saved like sklearn.
if we use sklearn, it works:
import torch
from sklearn import random_projection
model = random_projection.SparseRandomProjection(eps=0.1)
torch.save(model, 'model.pkl')
in cuml it not work and give following error:
import cuml
model = cuml.random_projection.SparseRandomProjection(eps=0.1)
torch.save(model, 'model.pkl')
TypeError: self.rand_matD,self.rand_matS cannot be converted to a Python object for pickling
The text was updated successfully, but these errors were encountered: