import numpy as np
C = np.random.normal(0, 1, (100, 2))
X = np.random.normal(0, 1, (100, 2))
Y = np.random.normal(0, 1, 100)
from contextualized.easy import ContextualizedRegressor
model = ContextualizedRegressor(encoder_type='linear')
model.fit(C, X, Y)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/calebellington/Workbench/Contextualized/contextualized/easy/wrappers/SKLearnWrapper.py", line 514, in fit
model = self.base_constructor(**organized_kwargs["model"])
File "/Users/calebellington/Workbench/Contextualized/contextualized/regression/lightning_modules.py", line 69, in __init__
self._build_metamodel(*args, **kwargs)
File "/Users/calebellington/Workbench/Contextualized/contextualized/regression/lightning_modules.py", line 243, in _build_metamodel
self.metamodel = NaiveMetamodel(*args, **kwargs)
File "/Users/calebellington/Workbench/Contextualized/contextualized/regression/metamodels.py", line 50, in __init__
self.context_encoder = encoder(context_dim, out_dim, **encoder_kwargs)
TypeError: Linear.__init__() got an unexpected keyword argument 'width'
To reproduce