ba256835a4f33d9139a70b6440c3223123132bc8,torchnet/meter/confusionmeter.py,ConfusionMeter,add,#ConfusionMeter#,42

Before Change

        onehot = np.ndim(target) != 1
        assert output.shape[0] == target.shape[0], \
                "number of targets and outputs do not match"
        assert output.shape[1] == self.conf.shape[0], \
                "number of outputs does not match size of confusion matrix"
        assert not onehot or target.shape[1] == output.shape[1], \
                "target should be 1D Tensor or have size of output (one-hot)"
        if onehot:
            assert (target >= 0).all() and (target <= 1).all(), \

After Change

        if np.ndim(predicted) != 1:
            assert predicted.shape[1] == self.k, \
                "number of predictions does not match size of confusion matrix"
            predicted = np.argmax(predicted, 1)
        else:
            assert (predicted.max() < self.k) and (predicted.min() >= 0), \
                "predicted values are not between 1 and k"

Instances