o .wi @srddlZddlmZddlmZddlmZddlmZes!dgZdedefd d Z d ed ed e defddZ dS)N)Tensor)multiclass_confusion_matrix)check_cluster_labels)"_TORCH_LINEAR_ASSIGNMENT_AVAILABLEcluster_accuracyconfmatreturncCsXddlm}|d}|||}|d}|t|jd|f}||S)z9Computes the clustering accuracy from a confusion matrix.r)batch_linear_assignmentN)torch_linear_assignmentr maxtorcharangeshapeflattensum)rr assignmenttpsrp/home/ubuntu/sommelier/.venv/lib/python3.10/site-packages/torchmetrics/functional/clustering/cluster_accuracy.py_cluster_accuracy_computes rpredstarget num_classescCs,tstdt||t|||d}t|S)aComputes the clustering accuracy between the predicted and target clusters. Args: preds: predicted cluster labels target: ground truth cluster labels num_classes: number of classes Returns: Scalar tensor with clustering accuracy between 0.0 and 1.0 Raises: RuntimeError: If `torch_linear_assignment` is not installed Example: >>> from torchmetrics.functional.clustering import cluster_accuracy >>> preds = torch.tensor([0, 0, 1, 1]) >>> target = torch.tensor([1, 1, 0, 0]) >>> cluster_accuracy(preds, target, 2) tensor(1.000) zaMissing `torch_linear_assignment`. Please install it with `pip install torchmetrics[clustering]`.)r)r RuntimeErrorrrr)rrrrrrrr&s ) r r&torchmetrics.functional.classificationr(torchmetrics.functional.clustering.utilsrtorchmetrics.utilities.importsr__doctest_skip__rintrrrrrs