tensor operation type lang pair - kInt CPU, cuda

[dcslin]

added tensor operation type lang pair - cuda kint
fixed tensor operation type lang pair - cpu, kint
fixed tensor operation nrm2 type
added testing for mix type tensor operations

[chrishkchris]

This PR is a problem (bug) fix to issue #744 , and can be merged after I complied and tested it with GPU.

1. test_onnx_backend.py

root@71ac539cda77:~/dcsysh/singa/test/python# python3 test_onnx_backend.py
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----------------------------------------------------------------------
Ran 1114 tests in 1.256s

OK (skipped=603)

2. simple training test (just to see if it introduces other serious bug)

root@71ac539cda77:~/dcsysh/singa/examples/cnn# python3 train_cnn.py cnn mnist
Starting Epoch 0:
Training loss = 582.622375, training accuracy = 0.792789
Evaluation accuracy = 0.933393, Elapsed Time = 3.197757s
Starting Epoch 1:
Training loss = 234.050247, training accuracy = 0.921675
Evaluation accuracy = 0.956430, Elapsed Time = 3.176632s
Starting Epoch 2:
Training loss = 167.452026, training accuracy = 0.944854
Evaluation accuracy = 0.969351, Elapsed Time = 3.174831s
Starting Epoch 3:
Training loss = 141.909851, training accuracy = 0.952591
Evaluation accuracy = 0.969752, Elapsed Time = 3.174302s
Starting Epoch 4:
Training loss = 121.488564, training accuracy = 0.959212
Evaluation accuracy = 0.970853, Elapsed Time = 3.173884s
Starting Epoch 5:
Training loss = 106.590233, training accuracy = 0.965181
Evaluation accuracy = 0.976362, Elapsed Time = 3.271060s
Starting Epoch 6:
Training loss = 97.972565, training accuracy = 0.967399
Evaluation accuracy = 0.976863, Elapsed Time = 3.177941s
Starting Epoch 7:
Training loss = 89.360428, training accuracy = 0.970484
Evaluation accuracy = 0.973658, Elapsed Time = 3.177838s
Starting Epoch 8:
Training loss = 82.499229, training accuracy = 0.972719
Evaluation accuracy = 0.977865, Elapsed Time = 3.312110s
Starting Epoch 9:
Training loss = 79.484062, training accuracy = 0.973252
Evaluation accuracy = 0.981070, Elapsed Time = 3.180323s