torchmetrics.utilities.data¶
select_topk¶
- torchmetrics.utilities.data.select_topk(prob_tensor, topk=1, dim=1)[source]¶
Convert a probability tensor to binary by selecting top-k the highest entries.
- Parameters:
- Return type:
- Returns:
A binary tensor of the same shape as the input tensor of type
torch.int32
Example
>>> x = torch.tensor([[1.1, 2.0, 3.0], [2.0, 1.0, 0.5]]) >>> select_topk(x, topk=2) tensor([[0, 1, 1], [1, 1, 0]], dtype=torch.int32)
to_categorical¶
to_onehot¶
- torchmetrics.utilities.data.to_onehot(label_tensor, num_classes=None)[source]¶
Convert a dense label tensor to one-hot format.
- Parameters:
- Return type:
- Returns:
A sparse label tensor with shape [N, C, d1, d2, …]
Example
>>> x = torch.tensor([1, 2, 3]) >>> to_onehot(x) tensor([[0, 1, 0, 0], [0, 0, 1, 0], [0, 0, 0, 1]])