encoder.supernode_pooling_config
================================

.. py:module:: encoder.supernode_pooling_config


Classes
-------

.. autoapisummary::

   encoder.supernode_pooling_config.SupernodePoolingConfig


Module Contents
---------------

.. py:class:: SupernodePoolingConfig(/, **data)

   Bases: :py:obj:`pydantic.BaseModel`


   !!! abstract "Usage Documentation"
       [Models](../concepts/models.md)

   A base class for creating Pydantic models.

   .. attribute:: __class_vars__

      The names of the class variables defined on the model.

   .. attribute:: __private_attributes__

      Metadata about the private attributes of the model.

   .. attribute:: __signature__

      The synthesized `__init__` [`Signature`][inspect.Signature] of the model.

   .. attribute:: __pydantic_complete__

      Whether model building is completed, or if there are still undefined fields.

   .. attribute:: __pydantic_core_schema__

      The core schema of the model.

   .. attribute:: __pydantic_custom_init__

      Whether the model has a custom `__init__` function.

   .. attribute:: __pydantic_decorators__

      Metadata containing the decorators defined on the model.
      This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.

   .. attribute:: __pydantic_generic_metadata__

      Metadata for generic models; contains data used for a similar purpose to
      __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

   .. attribute:: __pydantic_parent_namespace__

      Parent namespace of the model, used for automatic rebuilding of models.

   .. attribute:: __pydantic_post_init__

      The name of the post-init method for the model, if defined.

   .. attribute:: __pydantic_root_model__

      Whether the model is a [`RootModel`][pydantic.root_model.RootModel].

   .. attribute:: __pydantic_serializer__

      The `pydantic-core` `SchemaSerializer` used to dump instances of the model.

   .. attribute:: __pydantic_validator__

      The `pydantic-core` `SchemaValidator` used to validate instances of the model.

   .. attribute:: __pydantic_fields__

      A dictionary of field names and their corresponding [`FieldInfo`][pydantic.fields.FieldInfo] objects.

   .. attribute:: __pydantic_computed_fields__

      A dictionary of computed field names and their corresponding [`ComputedFieldInfo`][pydantic.fields.ComputedFieldInfo] objects.

   .. attribute:: __pydantic_extra__

      A dictionary containing extra values, if [`extra`][pydantic.config.ConfigDict.extra]
      is set to `'allow'`.

   .. attribute:: __pydantic_fields_set__

      The names of fields explicitly set during instantiation.

   .. attribute:: __pydantic_private__

      Values of private attributes set on the model instance.

   Create a new model by parsing and validating input data from keyword arguments.

   Raises [`ValidationError`][pydantic_core.ValidationError] if the input data cannot be
   validated to form a valid model.

   `self` is explicitly positional-only to allow `self` as a field name.


   .. py:attribute:: hidden_dim
      :type:  int
      :value: None


      Hidden dimension for positional embeddings, messages and the resulting output vector.


   .. py:attribute:: input_dim
      :type:  int
      :value: None


      Number of positional dimension (e.g., input_dim=2 for a 2D position, input_dim=3 for a 3D position)


   .. py:attribute:: radius
      :type:  float | None
      :value: None


      Radius around each supernode. From points within this radius, messages are passed to the supernode.


   .. py:attribute:: k
      :type:  int | None
      :value: None


      Number of neighbors for each supernode. From the k-NN points, messages are passed to the supernode.


   .. py:attribute:: max_degree
      :type:  int
      :value: None


      Maximum degree of the radius graph. Defaults to 32.


   .. py:attribute:: spool_pos_mode
      :type:  Literal['abspos', 'relpos', 'absrelpos']
      :value: None


      absolute space ("abspos"), relative space ("relpos") or both ("absrelpos").

      :type: Type of position embeddeding


   .. py:attribute:: init_weights
      :type:  emmi.types.InitWeightsMode
      :value: None


      Weight initialization of linear layers. Defaults to "truncnormal002".


   .. py:attribute:: readd_supernode_pos
      :type:  bool
      :value: None


      If true, the absolute positional encoding of the supernode is concatenated to the supernode vector after message passing and linearly projected back to hidden_dim. Defaults to True.


   .. py:attribute:: aggregation
      :type:  Literal['mean', 'sum']
      :value: None


      Aggregation for message passing ("mean" or "sum").


   .. py:attribute:: message_mode
      :type:  Literal['mlp', 'linear', 'identity']
      :value: None


      How messages are created. "mlp" (2 layer MLP), "linear" (nn.Linear), "identity" (nn.Identity). Defaults to "mlp".


   .. py:attribute:: num_input_features
      :type:  int | None
      :value: None


      number of input features per point. None will fall back to a version without features. Defaults to None, which means no input features.


   .. py:method:: validate_radius_and_k()