Files
PINA/pina/condition/input_target_condition.py
2025-04-17 10:48:31 +02:00

148 lines
5.4 KiB
Python

"""
This module contains condition classes for supervised learning tasks.
"""
import torch
from torch_geometric.data import Data
from ..label_tensor import LabelTensor
from ..graph import Graph
from .condition_interface import ConditionInterface
class InputTargetCondition(ConditionInterface):
"""
Condition for domain/equation data. This condition must be used every
time a Physics Informed or a Supervised Loss is needed in the Solver.
"""
__slots__ = ["input", "target"]
_avail_input_cls = (torch.Tensor, LabelTensor, Data, Graph, list, tuple)
_avail_output_cls = (torch.Tensor, LabelTensor, Data, Graph, list, tuple)
def __new__(cls, input, target):
"""
Instantiate the appropriate subclass of InputTargetCondition based on
the types of input and target data.
:param input: Input data for the condition.
:type input: torch.Tensor | LabelTensor | Graph |
torch_geometric.data.Data | list[Graph] |
list[torch_geometric.data.Data] | tuple[Graph] |
tuple[torch_geometric.data.Data]
:param target: Target data for the condition.
:type target: torch.Tensor | LabelTensor | Graph |
torch_geometric.data.Data | list[Graph] |
list[torch_geometric.data.Data] | tuple[Graph] |
tuple[torch_geometric.data.Data]
:return: Subclass of InputTargetCondition
:rtype: TensorInputTensorTargetCondition | \
TensorInputGraphTargetCondition | \
GraphInputTensorTargetCondition | \
GraphInputGraphTargetCondition
:raises ValueError: If input and or target are not of type
:class:`torch.Tensor`, :class:`pina.label_tensor.LabelTensor`,
:class:`pina.graph.Graph`, or :class:`~torch_geometric.data.Data`.
"""
if cls != InputTargetCondition:
return super().__new__(cls)
if isinstance(input, (torch.Tensor, LabelTensor)) and isinstance(
target, (torch.Tensor, LabelTensor)
):
subclass = TensorInputTensorTargetCondition
return subclass.__new__(subclass, input, target)
if isinstance(input, (torch.Tensor, LabelTensor)) and isinstance(
target, (Graph, Data, list, tuple)
):
cls._check_graph_list_consistency(target)
subclass = TensorInputGraphTargetCondition
return subclass.__new__(subclass, input, target)
if isinstance(input, (Graph, Data, list, tuple)) and isinstance(
target, (torch.Tensor, LabelTensor)
):
cls._check_graph_list_consistency(input)
subclass = GraphInputTensorTargetCondition
return subclass.__new__(subclass, input, target)
if isinstance(input, (Graph, Data, list, tuple)) and isinstance(
target, (Graph, Data, list, tuple)
):
cls._check_graph_list_consistency(input)
cls._check_graph_list_consistency(target)
subclass = GraphInputGraphTargetCondition
return subclass.__new__(subclass, input, target)
raise ValueError(
"Invalid input/target types. "
"Please provide either torch_geometric.data.Data, Graph, "
"LabelTensor or torch.Tensor objects."
)
def __init__(self, input, target):
"""
Initialize the object storing the input and target data.
:param input: Input data for the condition.
:type input: torch.Tensor | LabelTensor | Graph | Data | list[Graph] |
list[Data] | tuple[Graph] |
tuple[Data]
:param target: Target data for the condition.
:type target: torch.Tensor | LabelTensor | Graph | Data | list[Graph] |
list[Data] | tuple[Graph] | tuple[Data]
.. note::
If either `input` or `target` are composed by a list of
:class:`pina.graph.Graph` or :class:`~torch_geometric.data.Data`
objects, all elements must have the same structure (keys and data
types)
"""
super().__init__()
self._check_input_target_len(input, target)
self.input = input
self.target = target
@staticmethod
def _check_input_target_len(input, target):
if isinstance(input, (Graph, Data)) or isinstance(
target, (Graph, Data)
):
return
if len(input) != len(target):
raise ValueError(
"The input and target lists must have the same length."
)
class TensorInputTensorTargetCondition(InputTargetCondition):
"""
InputTargetCondition subclass for :class:`torch.Tensor` or
:class:`pina.label_tensor.LabelTensor` input and target data.
"""
class TensorInputGraphTargetCondition(InputTargetCondition):
"""
InputTargetCondition subclass for :class:`torch.Tensor` or
:class:`pina.label_tensor.LabelTensor` input and
:class:`pina.graph.Graph` or :class:`~torch_geometric.data.Data` target
data.
"""
class GraphInputTensorTargetCondition(InputTargetCondition):
"""
InputTargetCondition subclass for :class:`pina.graph.Graph` o
:class:`~torch_geometric.data.Data` input and :class:`torch.Tensor` or
:class:`pina.label_tensor.LabelTensor` target data.
"""
class GraphInputGraphTargetCondition(InputTargetCondition):
"""
InputTargetCondition subclass for :class:`pina.graph.Graph`/
:class:`~torch_geometric.data.Data` input and target data.
"""