Rename

Author: mdbenito

notebooks/msr_banzhaf_digits.ipynb

@@ -193,7 +193,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "As with all other model-based valuation methods, for Data Banzhaf we need a scoring function to measure performance of the model over the test set. We will use accuracy, but it can be anything, like e.g. $R^2$, using strings from the [standard sklearn scoring methods](https://scikit-learn.org/stable/modules/model_evaluation.html), passed to [SupervisedScorer][pydvl.valuation.scorers.supervised.SupervisedScorer].\n",
+    "As with all other model-based valuation methods, for Data Banzhaf we need a scoring function to measure performance of the model over the test set. We will use accuracy, but it can be anything, like e.g. $R^2$, using strings from the [standard sklearn scoring methods](https://scikit-learn.org/stable/modules/model_evaluation.html), passed to [SkorchSupervisedScorer][pydvl.valuation.scorers.torchscorer.SkorchSupervisedScorer].\n",
     "\n",
     "We group our torch model and the scoring function into an instance of [ModelUtility][pydvl.valuation.utility.ModelUtility]."
    ]
@@ -205,11 +205,11 @@
    "outputs": [],
    "source": [
     "from pydvl.valuation.samplers import PermutationSampler, RelativeTruncation\n",
-    "from pydvl.valuation.scorers import SupervisedScorer\n",
+    "from pydvl.valuation.scorers import SkorchSupervisedScorer\n",
     "from pydvl.valuation.stopping import MinUpdates\n",
     "from pydvl.valuation.utility import ModelUtility\n",
     "\n",
-    "accuracy_over_test_set = SupervisedScorer(\n",
+    "accuracy_over_test_set = SkorchSupervisedScorer(\n",
     "    model, test_data=test, default=0.0, range=(0, 1)\n",
     ")\n",
     "\n",

src/pydvl/valuation/scorers/__init__.py

@@ -13,6 +13,6 @@
 
 from .base import *
 from .classwise import *
+from .skorch import *
 from .supervised import *
-from .torchscorer import *
 from .utils import *