Single Graph Handling In Problem's Conditions

Apr 22, 2025 by ADMIN 46 views

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Problem Description

In the context of graph neural networks (GNNs), handling single graphs is a crucial aspect of problem formulation. However, when dealing with conditions in a problem, passing a single graph to the input of a Condition raises an error. This article aims to describe the bug, provide a reproducible example, and discuss the expected behavior.

Describe the Bug

The bug arises when attempting to pass a single graph to the input of a Condition in a problem. This results in an error being raised, preventing the code from executing as expected.

To Reproduce

To reproduce the bug, follow these steps:

from pina.graph import RadiusGraph
from pina.domain import CartesianDomain
from pina.problem import AbstractProblem
from pina.condition import Condition
from pina.trainer import Trainer
from pina.solver import SupervisedSolver
import torch

# Sample points
domain = CartesianDomain({"x": [-1, 1], "y": [-1, 1]})
pos = domain.sample(10, mode="grid")
radius = (pos.extract("x")[1] - pos.extract("x")[0])*1.1

# Create the graph
graph = RadiusGraph(pos=pos, radius=radius)
graph.y = torch.ones((pos.shape[0], 1), dtype=torch.float32)

# Define a problem
class MockProblem(AbstractProblem):
    input_variables = ["x", "y"]
    output_variables = ["u"]
    conditions = {"D": Condition(input=graph, target=graph.y)}

# Define a model
class MockGNN(torch.nn.Module):
    def __init__(self, in_features, out_features):
        super().__init__()
        self.fc = torch.nn.Linear(in_features, out_features)

    def forward(self, data):
        return self.fc(data.pos)

# Train
problem = MockProblem()
solver = SupervisedSolver(problem=problem, model=MockGNN(2, 1), use_lt=False)
trainer = Trainer(solver=solver, max_epochs=10, accelerator="gpu")
trainer.train()

Expected Behavior

The expected behavior is for the code to run without any errors. However, the current implementation raises an error when attempting to pass a single graph to the input of a Condition.

Output

The output of the code is an error message indicating that the GlobalStorage object has no attribute data.

File "/scratch/dir1/dir2/filename.py", line 67, in <module>
    trainer = Trainer(solver=solver, max_epochs=epochs, accelerator="gpu")
              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/scratch/dir1/PINA/pina/trainer.py", line 122, in __init__
    self._create_datamodule(
  File "/scratch/dir1/PINA/pina/trainer.py", line 209, in _create_datamodule
    self.data_module = PinaDataModule(
                       ^^^^^^^^^^^^^^^
  File "/scratch/dir1/PINA/pina/data/data_module.py", line 334, in __init__
    collector.store_fixed_data()
  File "/scratch/dir1/PINA/pina/.py", line 108, in store_fixed_data
    value.data if isinstance(value, Graph) else value
    ^^^^^^^^^^
  File "/u/g/dir1/miniconda3/envs/deep/lib/python3.12/site-packages/torch_geometric/data/data.py", line 561, in __getattr__
    return getattr(self._store, key)
           ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/u/g/dir1/miniconda3/envs/deep/lib/python3.12/site-packages/torch_geometric/data/storage.py", line 96, in __getattr__
    raise AttributeError(
AttributeError: 'GlobalStorage' object has no attribute 'data'

Additional Context

The issue can be resolved by internally transforming the input graph to a one-element list of graphs. A similar handling of the target is required.

Solution

To solve the issue, we need to modify the Condition class to handle single graphs. We can achieve this by adding a check to see if the input graph is a single graph or a list of graphs. If it's a single graph, we can transform it to a one-element list of graphs.

class Condition:
    def __init__(self, input, target):
        self.input = input
        self.target = target

    def __call__(self):
        if isinstance(self.input, Graph):
            self.input = [self.input]
        if isinstance(self.target, Graph):
            self.target = [self.target]
        # Rest of the code remains the same

By making this modification, we can ensure that the Condition class can handle single graphs correctly.

Conclusion

In conclusion, the bug in the Condition class arises when attempting to pass a single graph to the input of a Condition. This results in an error being raised, preventing the code from executing as expected. By modifying the Condition class to handle single graphs, we can resolve the issue and ensure that the code runs without any errors.

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Q: What is the issue with passing a single graph to the `input` of a `Condition`?

A: The issue arises because the Condition class is designed to handle lists of graphs, but when a single graph is passed, it raises an error. This is because the Condition class is trying to access attributes of the graph that do not exist when it's a single graph.

Q: How can I resolve this issue?

A: To resolve this issue, you can modify the Condition class to handle single graphs. This can be achieved by adding a check to see if the input graph is a single graph or a list of graphs. If it's a single graph, you can transform it to a one-element list of graphs.

Q: What is the expected behavior when passing a single graph to the `input` of a `Condition`?

A: The expected behavior is for the code to run without any errors. However, the current implementation raises an error when attempting to pass a single graph to the input of a Condition.

Q: What is the output of the code when passing a single graph to the `input` of a `Condition`?

A: The output of the code is an error message indicating that the GlobalStorage object has no attribute data.

Q: How can I modify the `Condition` class to handle single graphs?

A: You can modify the Condition class by adding a check to see if the input graph is a single graph or a list of graphs. If it's a single graph, you can transform it to a one-element list of graphs. Here's an example of how you can modify the Condition class:

class Condition:
    def __init__(self, input, target):
        self.input = input
        self.target = target

    def __call__(self):
        if isinstance(self.input, Graph):
            self.input = [self.input]
        if isinstance(self.target, Graph):
            self.target = [self.target]
        # Rest of the code remains the same

Q: What are the benefits of modifying the `Condition` class to handle single graphs?

A: The benefits of modifying the Condition class to handle single graphs include:

The code will run without any errors when passing a single graph to the input of a Condition.
The Condition class will be more flexible and able to handle different types of input graphs.
The code will be more robust and able to handle edge cases.

Q: Are there any potential drawbacks to modifying the `Condition` class to handle single graphs?

A: Yes, there are potential drawbacks to modifying the Condition class to handle single graphs. These include:

The code may become more complex and harder to maintain.
The modification may introduce new bugs or errors.
The modification may not be backward compatible with previous versions of the code.

Q: How can I test the modified `Condition` class to ensure it's working correctly?

A: You can test the modified Condition class by passing a single graph to input of a Condition and verifying that the code runs without any errors. You can also test the class by passing a list of graphs to the input of a Condition and verifying that the code runs correctly.

Q: What are some best practices for modifying the `Condition` class to handle single graphs?

A: Some best practices for modifying the Condition class to handle single graphs include:

Thoroughly test the modified class to ensure it's working correctly.
Document the changes made to the class to ensure that others understand the modifications.
Consider adding additional checks and error handling to ensure that the class is robust and able to handle edge cases.
Consider adding additional functionality to the class to make it more flexible and able to handle different types of input graphs.