Shortcuts

GraphClassifier

class flash.graph.classification.model.GraphClassifier(num_features, num_classes=None, labels=None, backbone='GCN', backbone_kwargs={}, pooling_fn='mean', head=None, loss_fn=torch.nn.functional.cross_entropy, learning_rate=None, optimizer='Adam', lr_scheduler=None, metrics=None)[source]

The GraphClassifier is a Task for classifying graphs. For more details, see Graph Classification.

Parameters
classmethod available_finetuning_strategies(cls)

Returns a list containing the keys of the available Finetuning Strategies.

Return type

List[str]

classmethod available_lr_schedulers(cls)

Returns a list containing the keys of the available LR schedulers.

Return type

List[str]

classmethod available_optimizers(cls)

Returns a list containing the keys of the available Optimizers.

Return type

List[str]

classmethod available_outputs(cls)

Returns the list of available outputs (that can be used during prediction or serving) for this Task.

Examples

..testsetup:

>>> from flash import Task
>>> print(Task.available_outputs())
['preds', 'raw']
Return type

List[str]

Read the Docs v: stable
Versions
latest
stable
0.7.5
0.7.4
0.7.3
0.7.2
0.7.1
0.7.0
0.6.0
0.5.2
0.5.1
0.5.0
0.4.0
0.3.2
0.3.1
0.3.0
0.2.3
0.2.2
0.2.1
0.2.0
0.1.0post1
docs-fix_typing
Downloads
html
On Read the Docs
Project Home
Builds

Free document hosting provided by Read the Docs.