shap_values should be 2d, instead shape=(200, 21, 2)!

[harshil17]

I am running the sample code same as it's given here https://github.com/oegedijk/explainerdashboard, using titanic datasource.

And running into the error saying "shap_values should be 2d, instead shape=(200, 21, 2)!"

Attached is the full error trace. can pleas anyone help me understand why i am getting this error and how can i resolve it ?

`AssertionError Traceback (most recent call last)
Cell In[7], line 12
1 explainer = ClassifierExplainer(model, X_test, y_test,
2 cats=['Deck', 'Embarked',
3 {'Gender': ['Sex_male', 'Sex_female', 'Sex_nan']}],
(...)
9 target = "Survival", # defaults to y.name
10 )
---> 12 db = ExplainerDashboard(explainer,
13 title="Titanic Explainer", # defaults to "Model Explainer"
14 shap_interaction=False, # you can switch off tabs with bools
15 )
16 db.run(port=8050)

File I:\Explainer Dashboard\explainer-dashboard\lib\site-packages\explainerdashboard\dashboards.py:803, in ExplainerDashboard.init(self, explainer, tabs, title, name, description, simple, hide_header, header_hide_title, header_hide_selector, header_hide_download, hide_poweredby, block_selector_callbacks, pos_label, fluid, mode, width, height, bootstrap, external_stylesheets, server, url_base_pathname, routes_pathname_prefix, requests_pathname_prefix, responsive, logins, port, importances, model_summary, contributions, whatif, shap_dependence, shap_interaction, decision_trees, **kwargs)
801 if isinstance(tabs, list):
802 tabs = [self._convert_str_tabs(tab) for tab in tabs]
--> 803 self.explainer_layout = ExplainerTabsLayout(
804 explainer,
805 tabs,
806 title,
807 description=self.description,
808 **update_kwargs(
809 kwargs,
810 header_hide_title=self.header_hide_title,
811 header_hide_selector=self.header_hide_selector,
812 header_hide_download=self.header_hide_download,
813 hide_poweredby=self.hide_poweredby,
814 block_selector_callbacks=self.block_selector_callbacks,
815 pos_label=self.pos_label,
816 fluid=fluid,
817 ),
818 )
819 else:
820 tabs = self._convert_str_tabs(tabs)

File I:\Explainer Dashboard\explainer-dashboard\lib\site-packages\explainerdashboard\dashboards.py:119, in ExplainerTabsLayout.init(self, explainer, tabs, title, name, description, header_hide_title, header_hide_selector, header_hide_download, hide_poweredby, block_selector_callbacks, pos_label, fluid, **kwargs)
116 self.fluid = fluid
118 self.selector = PosLabelSelector(explainer, name="0", pos_label=pos_label)
--> 119 self.tabs = [
120 instantiate_component(tab, explainer, name=str(i + 1), **kwargs)
121 for i, tab in enumerate(tabs)
122 ]
123 assert (
124 len(self.tabs) > 0
125 ), "When passing a list to tabs, need to pass at least one valid tab!"
127 self.register_components(*self.tabs)

File I:\Explainer Dashboard\explainer-dashboard\lib\site-packages\explainerdashboard\dashboards.py:120, in (.0)
116 self.fluid = fluid
118 self.selector = PosLabelSelector(explainer, name="0", pos_label=pos_label)
119 self.tabs = [
--> 120 instantiate_component(tab, explainer, name=str(i + 1), **kwargs)
121 for i, tab in enumerate(tabs)
122 ]
123 assert (
124 len(self.tabs) > 0
125 ), "When passing a list to tabs, need to pass at least one valid tab!"
127 self.register_components(*self.tabs)

File I:\Explainer Dashboard\explainer-dashboard\lib\site-packages\explainerdashboard\dashboard_methods.py:890, in instantiate_component(component, explainer, name, **kwargs)
884 kwargs = {
885 k: v
886 for k, v in kwargs.items()
887 if k in init_argspec.args + init_argspec.kwonlyargs
888 }
889 if "name" in init_argspec.args + init_argspec.kwonlyargs:
--> 890 component = component(explainer, name=name, **kwargs)
891 else:
892 print(
893 f"ExplainerComponent {component} does not accept a name parameter, "
894 f"so cannot assign name='{name}': "
(...)
899 "cluster will generate its own random uuid name!"
900 )

File I:\Explainer Dashboard\explainer-dashboard\lib\site-packages\explainerdashboard\dashboard_components\composites.py:545, in IndividualPredictionsComposite.init(self, explainer, title, name, hide_predindexselector, hide_predictionsummary, hide_contributiongraph, hide_pdp, hide_contributiontable, hide_title, hide_selector, index_check, **kwargs)
538 self.summary = RegressionPredictionSummaryComponent(
539 explainer, hide_selector=hide_selector, **kwargs
540 )
542 self.contributions = ShapContributionsGraphComponent(
543 explainer, hide_selector=hide_selector, **kwargs
544 )
--> 545 self.pdp = PdpComponent(
546 explainer, name=self.name + "3", hide_selector=hide_selector, **kwargs
547 )
548 self.contributions_list = ShapContributionsTableComponent(
549 explainer, hide_selector=hide_selector, **kwargs
550 )
552 self.index_connector = IndexConnector(
553 self.index,
554 [self.summary, self.contributions, self.pdp, self.contributions_list],
555 explainer=explainer if index_check else None,
556 )

File I:\Explainer Dashboard\explainer-dashboard\lib\site-packages\explainerdashboard\dashboard_components\overview_components.py:639, in PdpComponent.init(self, explainer, title, name, subtitle, hide_col, hide_index, hide_title, hide_subtitle, hide_footer, hide_selector, hide_popout, hide_dropna, hide_sample, hide_gridlines, hide_gridpoints, hide_cats_sort, index_dropdown, feature_input_component, pos_label, col, index, dropna, sample, gridlines, gridpoints, cats_sort, description, **kwargs)
636 self.index_name = "pdp-index-" + self.name
638 if self.col is None:
--> 639 self.col = self.explainer.columns_ranked_by_shap()[0]
641 if self.feature_input_component is not None:
642 self.exclude_callbacks(self.feature_input_component)

File I:\Explainer Dashboard\explainer-dashboard\lib\site-packages\explainerdashboard\explainers.py:86, in insert_pos_label..inner(self, *args, **kwargs)
84 else:
85 kwargs.update(dict(pos_label=self.pos_label))
---> 86 return func(self, **kwargs)

File I:\Explainer Dashboard\explainer-dashboard\lib\site-packages\explainerdashboard\explainers.py:1318, in BaseExplainer.columns_ranked_by_shap(self, pos_label)
1306 @insert_pos_label
1307 def columns_ranked_by_shap(self, pos_label=None):
1308 """returns the columns of X, ranked by mean abs shap value
1309
1310 Args:
(...)
1316
1317 """
-> 1318 return self.mean_abs_shap_df(pos_label).Feature.tolist()

File I:\Explainer Dashboard\explainer-dashboard\lib\site-packages\explainerdashboard\explainers.py:86, in insert_pos_label..inner(self, *args, **kwargs)
84 else:
85 kwargs.update(dict(pos_label=self.pos_label))
---> 86 return func(self, **kwargs)

File I:\Explainer Dashboard\explainer-dashboard\lib\site-packages\explainerdashboard\explainers.py:3128, in ClassifierExplainer.mean_abs_shap_df(self, pos_label)
3126 """mean absolute SHAP values"""
3127 if not hasattr(self, "_mean_abs_shap_df"):
-> 3128 _ = self.get_shap_values_df()
3129 self._mean_abs_shap_df = [
3130 self.get_shap_values_df(pos_label)[self.merged_cols]
3131 .abs()
(...)
3138 for pos_label in self.labels
3139 ]
3140 return self._mean_abs_shap_df[pos_label]

File I:\Explainer Dashboard\explainer-dashboard\lib\site-packages\explainerdashboard\explainers.py:86, in insert_pos_label..inner(self, *args, **kwargs)
84 else:
85 kwargs.update(dict(pos_label=self.pos_label))
---> 86 return func(self, **kwargs)

File I:\Explainer Dashboard\explainer-dashboard\lib\site-packages\explainerdashboard\explainers.py:2845, in ClassifierExplainer.get_shap_values_df(self, pos_label)
2843 if len(self.labels) == 2:
2844 if not isinstance(_shap_values, list):
-> 2845 assert (
2846 len(_shap_values.shape) == 2
2847 ), f"shap_values should be 2d, instead shape={_shap_values.shape}!"
2848 elif isinstance(_shap_values, list) and len(_shap_values) == 2:
2849 # for binary classifier only keep positive class
2850 _shap_values = _shap_values[1]

AssertionError: shap_values should be 2d, instead shape=(200, 21, 2)!`

[Brian-AlphaPlay]

I have the same error as well. Running code that had no changes to it and worked fine before.

EDIT: Looks to be caused by "breaking change" in the newest version of shap: https://github.com/shap/shap/releases
Issue does not appear when downgrading to shap==0.44.1

[oegedijk]

Yes, tests are failing as well. Seems like the output shape of the shap library has changed. Will look into it...

[oegedijk]

okay, have the fix on master. Will see if I can release tomorrow...

[oegedijk]

okay it's released: 0.4.6. I actually had to change the github pypi release mechanism, so I would appreciate it if you could let me know that it worked!

[harshil17]

Thanks, So i just tried with 0.4.6 and it's still giving me the same error ?

[oegedijk]

pip install -U explainerdashboard should install version 0.4.6 or are you using conda? (it takes about a day for the conda-forge CI to pick up the latest version and release it)

[harshil17]

Yes, I am using conda. I see. I will wait until tomorrow then and see if it works.

[harshil17]

I do see though that i am upgraded to 0.4.6.

[oegedijk]

Should also be on conda now. What model are you using? Can you run the classifier example from the README?

[harshil17]

just checked with classifier example from readme with updated version of explainerdashboard and it's still giving me the same error.

[harshil17]

Nevermind, i just restart the jupyter and it worked. Thank you very much.