Unify out results of LGBM_BoosterDumpModel and LGBM_BoosterSaveModel

[StrikerRUS]

At present these two functions produce different output content. For example, text representation contains parameters and feature importance, while JSON format - not. These functions should produce the same content but in different formats. It will help many third-party libraries that work with LightGBM model's dumps.

import json

import numpy as np
import lightgbm as lgb

X = np.random.random((100, 2))
y = np.random.random(100)
lgb_data = lgb.Dataset(X, y)
bst = lgb.train({}, lgb_data, num_boost_round=3)
bst.save_model('save_model.txt')
with open('dump_model.json', 'w') as json_dump:
    json.dump(bst.dump_model(), json_dump, indent=2)

Unify:

• feature importance (added feature importance to JSON dump  #2656)
• feature infos (added feature infos to JSON dump #2660)
• parameters
• trees' structure
• linear trees (Expose information about linear trees in JSON format #4186)

[StrikerRUS]

Closed in favor of being in #2302. We decided to keep all feature requests in one place.

Welcome to contribute this feature! Please re-open this issue (or post a comment if you are not a topic starter) if you are actively working on implementing this feature.

[jameslamb]

This was locked accidentally. I just unlocked it. We'd still welcome contributions related to this feature!