Fix num_batches and batch_size reading from config

configs/sklearnex_incremental_example.json

@@ -56,10 +56,6 @@
         }
     },
     "TEMPLATES": {
-        "covariance": {"SETS": ["common", "covariance", "unlabeled dataset"]},
-        "linear_regression": {
-            "SETS": ["common", "linear_regression", "labeled dataset"]
-        },
-        "pca": {"SETS": ["common", "pca", "unlabeled dataset"]}
+        "covariance": {"SETS": ["common", "covariance", "unlabeled dataset"]}
     }
 }

sklbench/benchmarks/sklearn_estimator.py

@@ -425,8 +425,12 @@ def measure_sklearn_estimator(
                         data_args = (x_test,)
 
                 if method == "partial_fit":
-                    num_batches = get_bench_case_value(bench_case, "data:num_batches")
-                    batch_size = get_bench_case_value(bench_case, "data:batch_size")
+                    num_batches = get_bench_case_value(
+                        bench_case, f"algorithm:num_batches:{stage}"
+                    )
+                    batch_size = get_bench_case_value(
+                        bench_case, f"algorithm:batch_size:{stage}"
+                    )
 
                     if batch_size is None:
                         if num_batches is None:

sklbench/report/implementation.py

@@ -236,6 +236,7 @@ def get_result_tables_as_df(
     splitby_columns=["estimator", "method", "function"],
     compatibility_mode=False,
 ):
+    print(results["bench_cases"])
     bench_cases = pd.DataFrame(
         [flatten_dict(bench_case) for bench_case in results["bench_cases"]]
     )
@@ -244,6 +245,7 @@ def get_result_tables_as_df(
     if compatibility_mode:
         bench_cases = transform_results_to_compatible(bench_cases)
 
+    print(bench_cases)
     for column in diffby_columns.copy():
         if bench_cases[column].nunique() == 1:
             bench_cases.drop(columns=[column], inplace=True)