NN Built-In for Embedding Layers

[MaximilianSchreff]

This PR adds the embedding layer as a built-in operator in our nn/layers library. The functionality is similar to pytorch.nn.Embedding (https://pytorch.org/docs/stable/generated/torch.nn.Embedding.html)

The layer receives indices as input which refer to indices of an embedding dictionary and returns an embedding matrix where row i refers to embedding vector indices[i] of the embedding dictionary.

This layer is used in every transformer architecture. Here the indices usually come from a tokenizer and the embedding matrix is the input to the actual transformer model.

Testing

• Testing forward pass and backward pass for correctness
• Implemented as a component test in NNComponentTest.java
• Manually calculated test cases for the forward pass
• For backward pass, comparison against pytorches autograd module

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 72.47%. Comparing base (78b23cf) to head (336ef19).
Report is 22 commits behind head on main.

Additional details and impacted files

@@            Coverage Diff            @@
##               main    #2237   +/-   ##
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  Coverage     72.46%   72.47%           
- Complexity    45453    45465   +12     
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  Files          1469     1469           
  Lines        170893   170893           
  Branches      33325    33325           
=========================================
+ Hits         123846   123863   +17     
+ Misses        37630    37617   -13     
+ Partials       9417     9413    -4     

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[phaniarnab]

Thanks @MaximilianSchreff. I will merge it in.