Merge model compatibility fixes from 1.0rc branch. (#5305)

* Port test model compatibility.
* Port logit model fix.

https://github.com/dmlc/xgboost/pull/5248
https://github.com/dmlc/xgboost/pull/5281

tests/python/test_model_compatibility.py

@@ -0,0 +1,130 @@
+import xgboost
+import os
+import generate_models as gm
+import json
+import zipfile
+import pytest
+
+
+def run_model_param_check(config):
+    assert config['learner']['learner_model_param']['num_feature'] == str(4)
+    assert config['learner']['learner_train_param']['booster'] == 'gbtree'
+
+
+def run_booster_check(booster, name):
+    config = json.loads(booster.save_config())
+    run_model_param_check(config)
+    if name.find('cls') != -1:
+        assert (len(booster.get_dump()) == gm.kForests * gm.kRounds *
+                gm.kClasses)
+        assert float(
+            config['learner']['learner_model_param']['base_score']) == 0.5
+        assert config['learner']['learner_train_param'][
+            'objective'] == 'multi:softmax'
+    elif name.find('logit') != -1:
+        assert len(booster.get_dump()) == gm.kForests * gm.kRounds
+        assert config['learner']['learner_model_param']['num_class'] == str(0)
+        assert config['learner']['learner_train_param'][
+            'objective'] == 'binary:logistic'
+    elif name.find('ltr') != -1:
+        assert config['learner']['learner_train_param'][
+            'objective'] == 'rank:ndcg'
+    else:
+        assert name.find('reg') != -1
+        assert len(booster.get_dump()) == gm.kForests * gm.kRounds
+        assert float(
+            config['learner']['learner_model_param']['base_score']) == 0.5
+        assert config['learner']['learner_train_param'][
+            'objective'] == 'reg:squarederror'
+
+
+def run_scikit_model_check(name, path):
+    if name.find('reg') != -1:
+        reg = xgboost.XGBRegressor()
+        reg.load_model(path)
+        config = json.loads(reg.get_booster().save_config())
+        if name.find('0.90') != -1:
+            assert config['learner']['learner_train_param'][
+                'objective'] == 'reg:linear'
+        else:
+            assert config['learner']['learner_train_param'][
+                'objective'] == 'reg:squarederror'
+        assert (len(reg.get_booster().get_dump()) ==
+                gm.kRounds * gm.kForests)
+        run_model_param_check(config)
+    elif name.find('cls') != -1:
+        cls = xgboost.XGBClassifier()
+        cls.load_model(path)
+        if name.find('0.90') == -1:
+            assert len(cls.classes_) == gm.kClasses
+            assert len(cls._le.classes_) == gm.kClasses
+            assert cls.n_classes_ == gm.kClasses
+        assert (len(cls.get_booster().get_dump()) ==
+                gm.kRounds * gm.kForests * gm.kClasses), path
+        config = json.loads(cls.get_booster().save_config())
+        assert config['learner']['learner_train_param'][
+            'objective'] == 'multi:softprob', path
+        run_model_param_check(config)
+    elif name.find('ltr') != -1:
+        ltr = xgboost.XGBRanker()
+        ltr.load_model(path)
+        assert (len(ltr.get_booster().get_dump()) ==
+                gm.kRounds * gm.kForests)
+        config = json.loads(ltr.get_booster().save_config())
+        assert config['learner']['learner_train_param'][
+            'objective'] == 'rank:ndcg'
+        run_model_param_check(config)
+    elif name.find('logit') != -1:
+        logit = xgboost.XGBClassifier()
+        logit.load_model(path)
+        assert (len(logit.get_booster().get_dump()) ==
+                gm.kRounds * gm.kForests)
+        config = json.loads(logit.get_booster().save_config())
+        assert config['learner']['learner_train_param'][
+            'objective'] == 'binary:logistic'
+    else:
+        assert False
+
+
+@pytest.mark.ci
+def test_model_compatibility():
+    '''Test model compatibility, can only be run on CI as others don't
+    have the credentials.
+
+    '''
+    path = os.path.dirname(os.path.abspath(__file__))
+    path = os.path.join(path, 'models')
+    try:
+        import boto3
+        import botocore
+    except ImportError:
+        pytest.skip(
+            'Skiping compatibility tests as boto3 is not installed.')
+
+    try:
+        s3_bucket = boto3.resource('s3').Bucket('xgboost-ci-jenkins-artifacts')
+        zip_path = 'xgboost_model_compatibility_test.zip'
+        s3_bucket.download_file(zip_path, zip_path)
+    except botocore.exceptions.NoCredentialsError:
+        pytest.skip(
+            'Skiping compatibility tests as running on non-CI environment.')
+
+    with zipfile.ZipFile(zip_path, 'r') as z:
+        z.extractall(path)
+
+    models = [
+        os.path.join(root, f) for root, subdir, files in os.walk(path)
+        for f in files
+        if f != 'version'
+    ]
+    assert models
+
+    for path in models:
+        name = os.path.basename(path)
+        if name.startswith('xgboost-'):
+            booster = xgboost.Booster(model_file=path)
+            run_booster_check(booster, name)
+        elif name.startswith('xgboost_scikit'):
+            run_scikit_model_check(name, path)
+        else:
+            assert False