o yi5 @sddlmZmZddlZddlmZddlmZdededeeeffdd Zddeded eedefd d Z ddeded eedefddZ dS))OptionalTupleN)Tensor)_check_same_shapepredstargetreturncCs"t|||}|}||fS)zUpdates and returns variables required to compute Cosine Similarity. Checks for same shape of input tensors. Args: preds: Predicted tensor target: Ground truth tensor )rfloat)rrr h/home/ubuntu/.local/lib/python3.10/site-packages/torchmetrics/functional/regression/cosine_similarity.py_cosine_similarity_updates r sum reductioncCsZ||jdd}|jdd}|jdd}|||}tjtjddddd}|||S)a&Computes Cosine Similarity. Args: preds: Predicted tensor target: Ground truth tensor reduction: The method of reducing along the batch dimension using sum, mean or taking the individual scores Example: >>> target = torch.tensor([[1, 2, 3, 4], [1, 2, 3, 4]]) >>> preds = torch.tensor([[1, 2, 3, 4], [-1, -2, -3, -4]]) >>> preds, target = _cosine_similarity_update(preds, target) >>> _cosine_similarity_compute(preds, target, 'none') tensor([ 1.0000, -1.0000]) )dimcS|SNr xr r r @z,_cosine_similarity_compute..cSrrr rr r r rAr)r meannoneN)r normtorchr)rrr dot_product preds_norm target_norm similarityreduction_mappingr r r _cosine_similarity_compute(s    r cCst||\}}t|||S)aComputes the `Cosine Similarity`_ between targets and predictions: .. math:: cos_{sim}(x,y) = \frac{x \cdot y}{||x|| \cdot ||y||} = \frac{\sum_{i=1}^n x_i y_i}{\sqrt{\sum_{i=1}^n x_i^2}\sqrt{\sum_{i=1}^n y_i^2}} where :math:`y` is a tensor of target values, and :math:`x` is a tensor of predictions. Args: preds: Predicted tensor with shape ``(N,d)`` target: Ground truth tensor with shape ``(N,d)`` reduction: The method of reducing along the batch dimension using sum, mean or taking the individual scores Example: >>> from torchmetrics.functional.regression import cosine_similarity >>> target = torch.tensor([[1, 2, 3, 4], ... [1, 2, 3, 4]]) >>> preds = torch.tensor([[1, 2, 3, 4], ... [-1, -2, -3, -4]]) >>> cosine_similarity(preds, target, 'none') tensor([ 1.0000, -1.0000]) )r r )rrrr r r cosine_similarityFs r!)r ) typingrrrrtorchmetrics.utilities.checksrr strr r!r r r r s     $