Update the metric module about singa HOT 4 OPEN

Or we can convert SINGA Tensor to numpy array and use sklearn.metrics to compute the metrics https://scikit-learn.org/stable/modules/model_evaluation.html.

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When we use this accuracy:
y_true (each value is a label index) is provided directly by the dataset
y_pred (each value is a label index) needs to be obtained by applying max function to the network output (i.e. logit) BEFORE the softmaxCrossEntropy

so we need a max function to turn the logits into pred label index?

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I suggest to use sklearn's functions to evaluate the metrics.
We can them remove the metric.py module.

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sklearn.metrics.accuracy_score API:
https://scikit-learn.org/stable/modules/generated/sklearn.metrics.accuracy_score.html#sklearn.metrics.accuracy_score

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