encoder.supernode_pooling_config¶
Classes¶
!!! abstract "Usage Documentation" |
Module Contents¶
- class encoder.supernode_pooling_config.SupernodePoolingConfig(/, **data)¶
Bases:
pydantic.BaseModel- !!! abstract “Usage Documentation”
[Models](../concepts/models.md)
A base class for creating Pydantic models.
- Parameters:
data (Any)
- __class_vars__¶
The names of the class variables defined on the model.
- __private_attributes__¶
Metadata about the private attributes of the model.
- __signature__¶
The synthesized __init__ [Signature][inspect.Signature] of the model.
- __pydantic_complete__¶
Whether model building is completed, or if there are still undefined fields.
- __pydantic_core_schema__¶
The core schema of the model.
- __pydantic_custom_init__¶
Whether the model has a custom __init__ function.
- __pydantic_decorators__¶
Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.
- __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.
- __pydantic_parent_namespace__¶
Parent namespace of the model, used for automatic rebuilding of models.
- __pydantic_post_init__¶
The name of the post-init method for the model, if defined.
- __pydantic_root_model__¶
Whether the model is a [RootModel][pydantic.root_model.RootModel].
- __pydantic_serializer__¶
The pydantic-core SchemaSerializer used to dump instances of the model.
- __pydantic_validator__¶
The pydantic-core SchemaValidator used to validate instances of the model.
- __pydantic_fields__¶
A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.
- __pydantic_computed_fields__¶
A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.
- __pydantic_extra__¶
A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to ‘allow’.
- __pydantic_fields_set__¶
The names of fields explicitly set during instantiation.
- __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.
Hidden dimension for positional embeddings, messages and the resulting output vector.
- input_dim: int = None¶
Number of positional dimension (e.g., input_dim=2 for a 2D position, input_dim=3 for a 3D position)
- radius: float | None = None¶
Radius around each supernode. From points within this radius, messages are passed to the supernode.
- k: int | None = None¶
Number of neighbors for each supernode. From the k-NN points, messages are passed to the supernode.
- spool_pos_mode: Literal['abspos', 'relpos', 'absrelpos'] = None¶
absolute space (“abspos”), relative space (“relpos”) or both (“absrelpos”).
- Type:
Type of position embeddeding
- init_weights: emmi.types.InitWeightsMode = None¶
Weight initialization of linear layers. Defaults to “truncnormal002”.
- readd_supernode_pos: bool = 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.
- aggregation: Literal['mean', 'sum'] = None¶
Aggregation for message passing (“mean” or “sum”).
- message_mode: Literal['mlp', 'linear', 'identity'] = None¶
How messages are created. “mlp” (2 layer MLP), “linear” (nn.Linear), “identity” (nn.Identity). Defaults to “mlp”.
- num_input_features: int | None = None¶
number of input features per point. None will fall back to a version without features. Defaults to None, which means no input features.
- validate_radius_and_k()¶