Add missing files

src/explainers/functional.py

@@ -0,0 +1,109 @@
+from typing import Dict, List, Optional, Protocol, Union
+
+import torch
+
+from src.explainers.base import Explainer
+from src.explainers.captum.similarity import CaptumSimilarityExplainer
+
+
+class ExplainFunc(Protocol):
+    def __call__(
+        self,
+        model: torch.nn.Module,
+        model_id: str,
+        cache_dir: Optional[str],
+        test_tensor: torch.Tensor,
+        explanation_targets: Optional[Union[List[int], torch.Tensor]],
+        train_dataset: torch.utils.data.Dataset,
+        explain_kwargs: Dict,
+        init_kwargs: Dict,
+        device: Union[str, torch.device],
+    ) -> torch.Tensor:
+        pass
+
+
+def explainer_functional_interface(
+    explainer_cls: Explainer,
+    model: torch.nn.Module,
+    model_id: str,
+    cache_dir: Optional[str],
+    test_tensor: torch.Tensor,
+    explanation_targets: Optional[Union[List[int], torch.Tensor]],
+    train_dataset: torch.utils.data.Dataset,
+    device: Union[str, torch.device],
+    init_kwargs: Optional[Dict] = {},
+    explain_kwargs: Optional[Dict] = {},
+) -> torch.Tensor:
+    explainer = explainer_cls(
+        model=model,
+        model_id=model_id,
+        cache_dir=cache_dir,
+        train_dataset=train_dataset,
+        device=device,
+        **init_kwargs,
+    )
+    return explainer.explain(test=test_tensor, **explain_kwargs)
+
+
+def explainer_self_influence_interface(
+    explainer_cls: Explainer,
+    model: torch.nn.Module,
+    model_id: str,
+    cache_dir: Optional[str],
+    train_dataset: torch.utils.data.Dataset,
+    init_kwargs: Dict,
+    device: Union[str, torch.device],
+) -> torch.Tensor:
+    explainer = explainer_cls(
+        model=model,
+        model_id=model_id,
+        cache_dir=cache_dir,
+        train_dataset=train_dataset,
+        device=device,
+        **init_kwargs,
+    )
+    return explainer.self_influence_ranking()
+
+
+def captum_similarity_explain(
+    model: torch.nn.Module,
+    model_id: str,
+    cache_dir: Optional[str],
+    test_tensor: torch.Tensor,
+    explanation_targets: Optional[Union[List[int], torch.Tensor]],
+    train_dataset: torch.utils.data.Dataset,
+    device: Union[str, torch.device],
+    init_kwargs: Optional[Dict] = {},
+    explain_kwargs: Optional[Dict] = {},
+) -> torch.Tensor:
+    return explainer_functional_interface(
+        explainer_cls=CaptumSimilarityExplainer,
+        model=model,
+        model_id=model_id,
+        cache_dir=cache_dir,
+        test_tensor=test_tensor,
+        explanation_targets=explanation_targets,
+        train_dataset=train_dataset,
+        device=device,
+        init_kwargs=init_kwargs,
+        explain_kwargs=explain_kwargs,
+    )
+
+
+def captum_similarity_self_influence_ranking(
+    model: torch.nn.Module,
+    model_id: str,
+    cache_dir: Optional[str],
+    train_dataset: torch.utils.data.Dataset,
+    init_kwargs: Dict,
+    device: Union[str, torch.device],
+) -> torch.Tensor:
+    return explainer_self_influence_interface(
+        explainer_cls=CaptumSimilarityExplainer,
+        model=model,
+        model_id=model_id,
+        cache_dir=cache_dir,
+        train_dataset=train_dataset,
+        device=device,
+        init_kwargs=init_kwargs,
+    )

tests/explainers/test_explainers.py

@@ -0,0 +1,77 @@
+import os
+
+import pytest
+import torch
+
+from src.explainers.captum.similarity import CaptumSimilarityExplainer
+from src.explainers.functional import captum_similarity_explain
+from src.utils.functions.similarities import cosine_similarity
+
+
+@pytest.mark.explainers
+@pytest.mark.parametrize(
+    "test_id, model, dataset, test_tensor, method, method_kwargs, explanations",
+    [
+        (
+            "mnist",
+            "load_mnist_model",
+            "load_mnist_dataset",
+            "load_mnist_test_samples_1",
+            "load_mnist_test_labels_1",
+            "SimilarityInfluence",
+            {"layer": "relu_4"},
+            "load_mnist_explanations_1",
+        ),
+    ],
+)
+def test_explain_functional(test_id, model, dataset, explanations, test_tensor, test_labels, method_kwargs, request):
+    model = request.getfixturevalue(model)
+    dataset = request.getfixturevalue(dataset)
+    test_tensor = request.getfixturevalue(test_tensor)
+    test_labels = request.getfixturevalue(test_labels)
+    explanations_exp = request.getfixturevalue(explanations)
+    explanations = captum_similarity_explain(
+        model,
+        "test_id",
+        os.path.join("./cache", "test_id"),
+        test_tensor,
+        test_labels,
+        dataset,
+        device="cpu",
+        init_kwargs=method_kwargs,
+    )
+    assert torch.allclose(explanations, explanations_exp), "Training data attributions are not as expected"
+
+
+@pytest.mark.explainers
+@pytest.mark.parametrize(
+    "test_id, model, dataset, test_tensor, method, method_kwargs, explanations",
+    [
+        (
+            "mnist",
+            "load_mnist_model",
+            "load_mnist_dataset",
+            "load_mnist_test_samples_1",
+            "load_mnist_test_labels_1",
+            "SimilarityInfluence",
+            {"layer": "relu_4", "similarity_metric": cosine_similarity},
+            "load_mnist_explanations_1",
+        ),
+    ],
+)
+def test_explain_stateful(test_id, model, dataset, explanations, test_tensor, test_labels, method_kwargs, request):
+    model = request.getfixturevalue(model)
+    dataset = request.getfixturevalue(dataset)
+    test_tensor = request.getfixturevalue(test_tensor)
+    test_labels = request.getfixturevalue(test_labels)
+    explanations_exp = request.getfixturevalue(explanations)
+    explainer = CaptumSimilarityExplainer(
+        model=model,
+        model_id="test_id",
+        cache_dir=os.path.join("./cache", "test_id"),
+        train_dataset=dataset,
+        device="cpu",
+        **method_kwargs,
+    )
+    explanations = explainer.explain(test_tensor, test_labels)
+    assert torch.allclose(explanations, explanations_exp), "Training data attributions are not as expected"