TypeError: got an unexpected keyword argument 'fit_params'

[ShaLiuYSU]

Dear developers,

I am now using CASM for fitting. No matter which exLasso or exGeneticAlgorithm method, I always got the following error:
TypeError: got an unexpected keyword argument 'fit_params'

I copy the full fit.json and output below, and please give me some advice on what happened?

{
"problem_specs": {
"data": {
"filename": "train",
"filetype": "selection",
"X": "corr",
"y": "formation_energy",
"kwargs": null
},
"weight": {
"method": "wHullDist",
"kwargs": {
"A": 0.0,
"B": 1.0,
"kT": 0.01
}
},
"cv": {
"method": "KFold",
"kwargs": {
"n_splits": 10,
"shuffle": true
},
"penalty": 0.0
}
},
"estimator": {
"method": "Lasso",
"kwargs": {
"alpha": 0.0001,
"max_iter": 1
}
},
"feature_selection": {
"method": "SelectFromModel",
"kwargs": null
},
"n_halloffame": 25
}

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!OUTPUT:
(casm) [LS@mgt fit_2]$ casm-learn -s fit_2_ga.json
Loading fit_2_ga.json

Hall of Fame size: 25

Get problem data...

Reading existing problem specs from: fit_2_ga_specs.pkl

DONE

Estimator:

{
"method": "Lasso",
"kwargs": {
"alpha": 0.0001,
"max_iter": 1,
"fit_intercept": false
}
}

Feature Selection:

{
"method": "SelectFromModel",
"kwargs": {}
}

Fit and select...

/data/home/LS/miniconda3/envs/casm/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:695: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.873e+00, tolerance: 6.002e-03
model = cd_fast.enet_coordinate_descent(

Iterations: 1

Feature selection threshold: None

DONE Runtime: 0.004479796160012484 (s)

Adding statistics...
Traceback (most recent call last):
File "/data/home/LS/miniconda3/envs/casm/bin/casm-learn", line 7, in
sys.exit(main())
File "/data/home/LS/miniconda3/envs/casm/lib/python3.9/site-packages/casm/scripts/casm_learn.py", line 212, in main
casm.learn.fit_and_select(input,
File "/data/home/LS/miniconda3/envs/casm/lib/python3.9/site-packages/casm/learn/feature_selection.py", line 123, in fit_and_select
indiv.fitness.values = casm.learn.model_selection.cross_val_score(
File "/data/home/LS/miniconda3/envs/casm/lib/python3.9/site-packages/casm/learn/model_selection.py", line 107, in cross_val_score
scores = sklearn.model_selection.cross_val_score(estimator,
File "/data/home/LS/miniconda3/envs/casm/lib/python3.9/site-packages/sklearn/utils/_param_validation.py", line 194, in wrapper
params = func_sig.bind(*args, **kwargs)
File "/data/home/LS/miniconda3/envs/casm/lib/python3.9/inspect.py", line 3045, in bind
return self._bind(args, kwargs)
File "/data/home/LS/miniconda3/envs/casm/lib/python3.9/inspect.py", line 3034, in _bind
raise TypeError(
TypeError: got an unexpected keyword argument 'fit_params'