Add mrr calculation

CHANGELOG.md

@@ -7,7 +7,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 ## [20.07.1] - YYYY-MM-DD
 
 ### Added
-
+- MRR metrics calculation ([#886](https://github.com/catalyst-team/catalyst/pull/886))
 - 
 
 ### Changed

catalyst/utils/metrics/mrr.py

@@ -0,0 +1,36 @@
+import torch
+
+
+def mrr(outputs: torch.Tensor, targets: torch.Tensor):
+
+    """
+    Calculate the MRR score given model ouptputs and targets
+    Args:
+        outputs [batch_size, slate_length] (torch.Tensor): model outputs, logits
+        targets [batch_szie, slate_length] (torch.Tensor): ground truth, labels
+    Returns:
+        mrr (float): the mrr score
+    """
+    outputs = outputs.clone()
+    targets = targets.clone()
+    max_rank = targets.shape[0]
+
+    _, indices = outputs.sort(descending=True, dim=-1)
+    true_sorted_by_preds = torch.gather(targets, dim=0, index=indices)
+    values, indices = torch.max(true_sorted_by_preds, dim=0)
+    indices = indices.type_as(values).unsqueeze(dim=0).t()
+    ats_rep = torch.tensor(
+        data=max_rank, device=indices.device, dtype=torch.float32
+    )
+    within_at_mask = (indices < ats_rep).type(torch.float32)
+
+    result = torch.tensor(1.0) / (indices + torch.tensor(1.0))
+
+    zero_sum_mask = torch.sum(values) == 0.0
+    result[zero_sum_mask] = 0.0
+
+    mrr = result * within_at_mask
+    return mrr[0]
+
+
+__all__ = ["mrr"]

catalyst/utils/metrics/tests/test_mrr.py

@@ -0,0 +1,23 @@
+import torch
+
+from catalyst.utils import metrics
+
+
+def test_mrr():
+    """
+    Tests for catalyst.utils.metrics.mrr metric.
+    """
+
+    # check 0 simple case
+    y_pred = [0.5, 0.2]
+    y_true = [1.0, 0.0]
+
+    mrr = metrics.mrr(torch.Tensor(y_pred), torch.Tensor(y_true))
+    assert mrr == 1
+
+    # check 1 simple case
+    y_pred = [0.5, 0.2]
+    y_true = [0.0, 1.0]
+
+    mrr = metrics.mrr(torch.Tensor(y_pred), torch.Tensor(y_true))
+    assert mrr == 0.5