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torch_geometric.explain
=======================
.. currentmodule:: torch_geometric.explain
.. warning::
This module is in active development and may not be stable.
Access requires installing :pyg:`PyG` from master.
.. contents:: Contents
:local:
Philoshopy
----------
This module provides a set of tools to explain the predictions of a PyG model or to explain the underlying phenomenon of a dataset (see the `"GraphFramEx: Towards Systematic Evaluation of Explainability Methods for Graph Neural Networks" <https://arxiv.org/abs/2206.09677>`_ paper for more details).
We represent explanations using the :class:`torch_geometric.explain.Explanation` class, which is a :class:`~torch_geometric.data.Data` object containing masks for the nodes, edges, features and any attributes of the data.
The :class:`torch_geometric.explain.Explainer` class is designed to handle all explainability parameters (see the :class:`torch_geometric.explain.config.ExplainerConfig` class for more details):
- which algorithm from the :class:`torch_geometric.explain.algorithm` module to use (*e.g.*, :class:`~torch_geometric.explain.algorithm.GNNExplainer`)
- the type of explanation to compute (*e.g.*, :obj:`explanation_type="phenomenon"` or :obj:`explanation_type="model"`)
- the different type of masks for node and edges (*e.g.*, :obj:`mask="object"` or :obj:`mask="attributes"`)
- any postprocessing of the masks (*e.g.*, :obj:`threshold_type="topk"` or :obj:`threshold_type="hard"`)
This class allows the user to easily compare different explainability methods and to easily switch between different types of masks, while making sure the high-level framework stays the same.
Explainer
---------
.. autoclass:: torch_geometric.explain.Explainer
:show-inheritance:
:members:
:special-members: __call__
.. autoclass:: torch_geometric.explain.config.ExplainerConfig
:members:
.. autoclass:: torch_geometric.explain.config.ModelConfig
:members:
.. autoclass:: torch_geometric.explain.config.ThresholdConfig
:members:
Explanations
------------
.. autoclass:: torch_geometric.explain.Explanation
:show-inheritance:
:members:
.. autoclass:: torch_geometric.explain.HeteroExplanation
:show-inheritance:
:members:
Explainer Algorithms
--------------------
.. currentmodule:: torch_geometric.explain.algorithm
.. autosummary::
:nosignatures:
:toctree: ../generated
{% for name in torch_geometric.explain.algorithm.classes %}
{{ name }}
{% endfor %}
Explanation Metrics
-------------------
The quality of an explanation can be judged by a variety of different methods.
PyG supports the following metrics out-of-the-box:
.. currentmodule:: torch_geometric.explain.metric
.. autosummary::
:nosignatures:
:toctree: ../generated
{% for name in torch_geometric.explain.metric.classes %}
{{ name }}
{% endfor %}
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