release code

Dassl.ProGrad.pytorch/dassl/metrics/accuracy.py

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+def compute_accuracy(output, target, topk=(1, )):
+    """Computes the accuracy over the k top predictions for
+    the specified values of k.
+
+    Args:
+        output (torch.Tensor): prediction matrix with shape (batch_size, num_classes).
+        target (torch.LongTensor): ground truth labels with shape (batch_size).
+        topk (tuple, optional): accuracy at top-k will be computed. For example,
+            topk=(1, 5) means accuracy at top-1 and top-5 will be computed.
+
+    Returns:
+        list: accuracy at top-k.
+    """
+    maxk = max(topk)
+    batch_size = target.size(0)
+
+    if isinstance(output, (tuple, list)):
+        output = output[0]
+
+    _, pred = output.topk(maxk, 1, True, True)
+    pred = pred.t()
+    correct = pred.eq(target.view(1, -1).expand_as(pred))
+
+    res = []
+    for k in topk:
+        correct_k = correct[:k].view(-1).float().sum(0, keepdim=True)
+        acc = correct_k.mul_(100.0 / batch_size)
+        res.append(acc)
+
+    return res