Adding one hot operator

[markbookk]

Description

Adding the one hot operator. This is similar to https://mxnet.apache.org/versions/1.6/api/r/docs/api/mx.nd.one.hot.html

• Implemented using MXNet and Tensorflow engine.

[codecov-io]

Codecov Report

Merging #684 (58775d5) into master (5b28382) will increase coverage by 0.05%.
The diff coverage is 70.00%.

@@             Coverage Diff              @@
##             master     #684      +/-   ##
============================================
+ Coverage     68.53%   68.59%   +0.05%     
- Complexity     3928     3932       +4     
============================================
  Files           461      461              
  Lines         18220    18222       +2     
  Branches       1963     1963              
============================================
+ Hits          12487    12499      +12     
+ Misses         4716     4706      -10     
  Partials       1017     1017              

Impacted Files	Coverage Δ	Complexity Δ
...i/src/main/java/ai/djl/ndarray/NDArrayAdapter.java	0.00% <0.00%> (ø)	0.00 <0.00> (ø)
...jl/nn/transformer/BertMaskedLanguageModelLoss.java	17.85% <0.00%> (ø)	1.00 <0.00> (ø)
...va/ai/djl/nn/transformer/BertNextSentenceLoss.java	18.18% <0.00%> (ø)	1.00 <0.00> (ø)
...rc/main/java/ai/djl/nn/transformer/MissingOps.java	0.00% <ø> (ø)	0.00 <0.00> (ø)
api/src/main/java/ai/djl/ndarray/NDArray.java	74.25% <100.00%> (+0.15%)	89.00 <1.00> (+1.00)
...e/src/main/java/ai/djl/mxnet/engine/MxNDArray.java	86.43% <100.00%> (+0.14%)	208.00 <1.00> (+1.00)
api/src/main/java/ai/djl/repository/Artifact.java	89.65% <0.00%> (-1.73%)	36.00% <0.00%> (-1.00%)
.../ai/djl/serving/http/ManagementRequestHandler.java	92.92% <0.00%> (+1.76%)	25.00% <0.00%> (+1.00%)
api/src/main/java/ai/djl/ndarray/NDManager.java	61.65% <0.00%> (+3.75%)	63.00% <0.00%> (+2.00%)

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[lanking520]

Is this operator commonly used in the mathmatical operations? Or it is jusr for BERT model?

[markbookk]

It is often used to convert categorical value tokens to a more expressive feature vector, not just for BERT model. Check this and this for an example.