MLPipeline does not preserve metadata from JSON pipeline annotation

[micahjsmith]

• MLBlocks version: 0.4
• Python version: 3.8

Description

I'm trying to get metadata from an MLPipeline object that was present in the JSON pipeline annotation that was loaded. For example, the annotation has a metadata.name field that I'd like to access from the pipeline.

What I Did

In the following example, I would expect that the MLPipeline has a metadata dict which has name key, just like the JSON. But it doesn't.

$ mkdir -p mlprimitives mlpipelines
$ curl -s https://raw.githubusercontent.com/MLBazaar/MLPrimitives/master/mlprimitives/primitives/sklearn.ensemble.RandomForestRegressor.json -o mlprimitives/sklearn.ensemble.RandomForestRegressor.json
$ curl -s https://raw.githubusercontent.com/MLBazaar/MLPrimitives/master/mlprimitives/pipelines/sklearn.ensemble.RandomForestRegressor.json -o mlpipelines/sklearn.ensemble.RandomForestRegressor.json
$ jq .metadata.name mlpipelines/sklearn.ensemble.RandomForestRegressor.json 
"sklearn.ensemble.RandomForestRegressor"
$ python
Python 3.8.3 (default, Jul 20 2020, 16:43:14) 
[Clang 11.0.3 (clang-1103.0.32.62)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> from mlblocks import load_pipeline, MLPipeline
>>> pipeline = MLPipeline(load_pipeline('sklearn.ensemble.RandomForestRegressor'))
>>> pipeline.metadata
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
AttributeError: 'MLPipeline' object has no attribute 'metadata'

Suggestions

1. Explicitly support persisting metadata on the MLPipeline object (and presumably on underlying MLBlock objects)
2. Raise an error of the JSON input contains unused (unsupported) keys
3. Guarantee that MLPipeline.load and MLPipeline.save are inverse operations, i.e. that no data is lost (currently metadata fields are lost)