Building a simple nowcasting model Error - return (loss_gradient * utils.VectorDict(x), loss_gradient)

[oscarstv]

river version: 0.13.0
Python version: 3.10
Operating system: macOS - mambaforge
Using Jupyter Lab

Trying to reproduce this tutorial:
https://riverml.xyz/0.13.0/examples/building-a-simple-nowcasting-model/

Error when Jupiter executes:
evaluate_model(model)

What I get:

---

TypeError Traceback (most recent call last)
Cell In[6], line 12
4 model = compose.Pipeline(
5 ('ordinal_date', compose.FuncTransformer(get_ordinal_date)),
6 ('scale', preprocessing.StandardScaler()),
7 ('lin_reg', linear_model.LinearRegression(intercept_lr=0)),
8 )
10 model = preprocessing.TargetStandardScaler(regressor=model)
---> 12 evaluate_model(model)

Cell In[4], line 23, in evaluate_model(model)
19 for x, y in datasets.AirlinePassengers():
20
21 # Obtain the prior prediction and update the model in one go
22 y_pred = model.predict_one(x)
---> 23 model.learn_one(x, y)
25 # Update the error metric
26 metric.update(y, y_pred)

File ~/mambaforge/envs/my_jordi_env/lib/python3.10/site-packages/river/preprocessing/scale.py:590, in TargetStandardScaler.learn_one(self, x, y)
588 def learn_one(self, x, y):
589 self.var.update(y)
--> 590 return super().learn_one(x, y)

File ~/mambaforge/envs/my_jordi_env/lib/python3.10/site-packages/river/compose/target_transform.py:62, in TargetTransformRegressor.learn_one(self, x, y)
61 def learn_one(self, x, y):
---> 62 self.regressor.learn_one(x, self.func(y))
63 return self

File ~/mambaforge/envs/my_jordi_env/lib/python3.10/site-packages/river/compose/pipeline.py:533, in Pipeline.learn_one(self, x, y, **params)
531 last_step = next(steps)
532 if last_step._supervised:
--> 533 last_step.learn_one(x=x, y=y, **params)
534 else:
535 last_step.learn_one(x, **params)

File ~/mambaforge/envs/my_jordi_env/lib/python3.10/site-packages/river/linear_model/base.py:166, in GLM.learn_one(self, x, y, w)
164 def learn_one(self, x, y, w=1.0):
165 with self._learn_mode(x):
--> 166 self._fit(x, y, w, get_grad=self._eval_gradient_one)

File ~/mambaforge/envs/my_jordi_env/lib/python3.10/site-packages/river/linear_model/base.py:110, in GLM._fit(self, x, y, w, get_grad)
107 self.optimizer.look_ahead(w=self._weights)
109 # Calculate the gradient
--> 110 gradient, loss_gradient = get_grad(x, y, w)
112 # Update the intercept
113 self.intercept -= self._get_intercept_update(loss_gradient)

File ~/mambaforge/envs/my_jordi_env/lib/python3.10/site-packages/river/linear_model/base.py:162, in GLM._eval_gradient_one(self, x, y, w)
156 if self.l2:
157 return (
158 loss_gradient * utils.VectorDict(x) + self.l2 * self._weights,
159 loss_gradient,
160 )
--> 162 return (loss_gradient * utils.VectorDict(x), loss_gradient)

TypeError: unsupported operand type(s) for *: 'float' and 'river.utils.vectordict.VectorDict'

Thank you!

[oscarstv]

Solved installing from terminal River 0.21.0

[oscarstv]

Thank you