nudles opened a new issue #702:
URL: https://github.com/apache/singa/issues/702
It would be better to implement a metric as a function in the metric.py as
metric typically has not states. Therefore, no need to make it as a class. e.g,
```python
def accuracy(y_pred, y_true):
"""compute the accuracy.
Args:
y_pred(numpy array or tensor): each value is a label index
y_true(numpy array or tensor): each value is a label index
"""
check shape match
convert y_pred and y_true to np array
return np.sum(y_pred== y_true) / y_true.shape[0]
```
Refer to https://keras.io/api/metrics/
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