95 lines
3.5 KiB
Python
95 lines
3.5 KiB
Python
"""Module for the DataCondition class."""
|
|
|
|
import torch
|
|
from torch_geometric.data import Data
|
|
from .condition_interface import ConditionInterface
|
|
from ..label_tensor import LabelTensor
|
|
from ..graph import Graph
|
|
|
|
|
|
class DataCondition(ConditionInterface):
|
|
"""
|
|
Condition defined by input data and conditional variables. It can be used
|
|
in unsupervised learning problems. Based on the type of the input,
|
|
different condition implementations are available:
|
|
|
|
- :class:`TensorDataCondition`: For :class:`torch.Tensor` or
|
|
:class:`~pina.label_tensor.LabelTensor` input data.
|
|
- :class:`GraphDataCondition`: For :class:`~pina.graph.Graph` or
|
|
:class:`~torch_geometric.data.Data` input data.
|
|
"""
|
|
|
|
__slots__ = ["input", "conditional_variables"]
|
|
_avail_input_cls = (torch.Tensor, LabelTensor, Data, Graph, list, tuple)
|
|
_avail_conditional_variables_cls = (torch.Tensor, LabelTensor)
|
|
|
|
def __new__(cls, input, conditional_variables=None):
|
|
"""
|
|
Instantiate the appropriate subclass of :class:`DataCondition` based on
|
|
the type of ``input``.
|
|
|
|
:param input: Input data for the condition.
|
|
:type input: torch.Tensor | LabelTensor | Graph |
|
|
Data | list[Graph] | list[Data] | tuple[Graph] | tuple[Data]
|
|
:param conditional_variables: Conditional variables for the condition.
|
|
:type conditional_variables: torch.Tensor | LabelTensor, optional
|
|
:return: Subclass of DataCondition.
|
|
:rtype: pina.condition.data_condition.TensorDataCondition |
|
|
pina.condition.data_condition.GraphDataCondition
|
|
|
|
:raises ValueError: If input is not of type :class:`torch.Tensor`,
|
|
:class:`~pina.label_tensor.LabelTensor`, :class:`~pina.graph.Graph`,
|
|
or :class:`~torch_geometric.data.Data`.
|
|
"""
|
|
|
|
if cls != DataCondition:
|
|
return super().__new__(cls)
|
|
if isinstance(input, (torch.Tensor, LabelTensor)):
|
|
subclass = TensorDataCondition
|
|
return subclass.__new__(subclass, input, conditional_variables)
|
|
|
|
if isinstance(input, (Graph, Data, list, tuple)):
|
|
cls._check_graph_list_consistency(input)
|
|
subclass = GraphDataCondition
|
|
return subclass.__new__(subclass, input, conditional_variables)
|
|
|
|
raise ValueError(
|
|
"Invalid input types. "
|
|
"Please provide either torch_geometric.data.Data or Graph objects."
|
|
)
|
|
|
|
def __init__(self, input, conditional_variables=None):
|
|
"""
|
|
Initialize the object by storing the input and conditional
|
|
variables (if any).
|
|
|
|
:param input: Input data for the condition.
|
|
:type input: torch.Tensor | LabelTensor | Graph | Data | list[Graph] |
|
|
list[Data] | tuple[Graph] | tuple[Data]
|
|
:param conditional_variables: Conditional variables for the condition.
|
|
:type conditional_variables: torch.Tensor | LabelTensor
|
|
|
|
.. note::
|
|
If ``input`` consists of a list of :class:`~pina.graph.Graph` or
|
|
:class:`~torch_geometric.data.Data`, all elements must have the same
|
|
structure (keys and data types)
|
|
"""
|
|
|
|
super().__init__()
|
|
self.input = input
|
|
self.conditional_variables = conditional_variables
|
|
|
|
|
|
class TensorDataCondition(DataCondition):
|
|
"""
|
|
DataCondition for :class:`torch.Tensor` or
|
|
:class:`~pina.label_tensor.LabelTensor` input data
|
|
"""
|
|
|
|
|
|
class GraphDataCondition(DataCondition):
|
|
"""
|
|
DataCondition for :class:`~pina.graph.Graph` or
|
|
:class:`~torch_geometric.data.Data` input data
|
|
"""
|