TF Python producing malformed JSON for numpy style arrays.

TF Python serializes numpy style arrays (e.g. Java NdArray) in the format 'normalizer': array([[0.2, 0.2], [0.1, 0.3]], dtype=float32)'.
This is not standard JSON, and tools, like GSON, throw a MalformedJsonException when trying to parse this.

The issue is how to best handle this in TF Java.

I have looked at GSON using customized TypeAdapter and Serilaizers/Deserializers, but I cannot get past the low level parsing throwing the MalformedJsonException. Right now I think my only alternative is to write a pre-parser to convert the array() format string to a wellformed JSON string.
For example, for the above example:

         {
             'normalizer': {
                " '_ArraySize_' = [1,2],    
                " '_ArrayData_' =  [[0.2, 0.2], [0.1, 0.3]], 
                " '_ArrayType_' = 'float32' 
              }
          }

_ArraySize_ is the array's shape and _ArrayType_ is the datatype for the NdArray.
This format is taken from OpenJData

Also, once we settle on a way to do this, should the NdArray package be modified to include serialize/deserialize methods.
What about compatibility with TF Python?

Any suggestions?

Start by reproducing the TF Python serialization shown in the issue and tracing how TF Java NdArray data reaches GSON parsing. Compare the proposed array representation with the OpenJData format and define the expected compatibility behavior; done means the format and serialization/deserialization ownership are agreed and malformed JSON is no longer produced.