Release DRUM v1.5.13 (#427)

* [RAPTOR-6387] update DRUM readme

Author: yakov-g

custom_model_runner/CHANGELOG.md

@@ -9,6 +9,10 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 ##### Fixed
 ##### Added 
 
+#### [1.5.13] - 2021-09-17
+####
+- compile DRUM with Java 11
+
 #### [1.5.12] - 2021-09-15
 ##### Fixed
 - R custom tasks sampling

custom_model_runner/README.md

@@ -28,8 +28,7 @@ All models:
 - If you are using a drop-in environment found in this repo, you must pip install these dependencies.
 
 Python models:
-- Python 3.6 or 3.7 is required unless you are using DRUM with a Docker image.
-- This is because DRUM only runs with Python 3.6 or 3.7.
+- Check https://pypi.org/project/datarobot-drum/ for supported Python versions.
 
 Java models:
 - JRE >= 11.

custom_model_runner/datarobot_drum/drum/description.py

@@ -1,3 +1,3 @@
-version = "1.5.12"
+version = "1.5.13"
 __version__ = version
 project_name = "datarobot-drum"

public_dropin_environments/java_codegen/dr_requirements.txt

@@ -1,3 +1,3 @@
 pandas==1.0.5
 pyarrow==0.14.1
-datarobot-drum==1.5.12
+datarobot-drum==1.5.13

public_dropin_environments/java_codegen/env_info.json

@@ -3,6 +3,6 @@
   "name": "[DataRobot] Java Drop-In (DR Codegen, H2O)",
   "description": "This template can be used as an environment for DataRobot generated scoring code or models that implement the either the IClassificationPredictor or IRegressionPredictor interface from the datarobot-prediction package and for H2O models exported as POJO or MOJO.",
   "programmingLanguage": "java",
-  "environmentVersionId": "614235a4eef323a0d7af0c4d",
+  "environmentVersionId": "61451f149f56415553ced151",
   "isPublic": true
 }

public_dropin_environments/julia_mlj/dr_requirements.txt

@@ -1,3 +1,3 @@
 pandas==1.0.5
 pyarrow==0.14.1
-datarobot-drum==1.5.12
+datarobot-drum==1.5.13

public_dropin_environments/julia_mlj/env_info.json

@@ -3,6 +3,6 @@
   "name": "[DataRobot] Julia Drop-In",
   "description": "This template environment can be used to create artifact-only Julia MLJ custom models. This environment contains Julia and a number of models accessilbe via MLJ interfaces and only requires your model artifact as a .jlso file and optionally a custom.jl file.",
   "programmingLanguage": "julia",
-  "environmentVersionId": "614235a4eef323a0d7af0c50",
+  "environmentVersionId": "61451f149f56415553ced154",
   "isPublic": true
 }

public_dropin_environments/python3_keras/dr_requirements.txt

@@ -1,2 +1,2 @@
 pyarrow==0.14.1
-datarobot-drum==1.5.12
+datarobot-drum==1.5.13

public_dropin_environments/python3_keras/env_info.json

@@ -3,6 +3,6 @@
   "name": "[DataRobot] Python 3 Keras Drop-In",
   "description": "This template environment can be used to create artifact-only keras custom models. This environment contains keras backed by tensorflow and only requires your model artifact as a .h5 file and optionally a custom.py file.",
   "programmingLanguage": "python",
-  "environmentVersionId": "614235a4eef323a0d7af0c52",
+  "environmentVersionId": "61451f149f56415553ced152",
   "isPublic": true
 }

public_dropin_environments/python3_pmml/dr_requirements.txt

@@ -1,2 +1,2 @@
 pyarrow==0.14.1
-datarobot-drum==1.5.12
+datarobot-drum==1.5.13

public_dropin_environments/python3_pmml/env_info.json

@@ -3,6 +3,6 @@
   "name": "[DataRobot] Python 3 PMML Drop-In",
   "description": "This template environment can be used to create artifact-only PMML custom models. This environment contains PyPMML and only requires your model artifact as a .pmml file and optionally a custom.py file.",
   "programmingLanguage": "python",
-  "environmentVersionId": "614235a4eef323a0d7af0c51",
+  "environmentVersionId": "61451f149f56415553ced153",
   "isPublic": true
 }

public_dropin_environments/python3_pytorch/dr_requirements.txt

@@ -1,2 +1,2 @@
 pyarrow==0.14.1
-datarobot-drum==1.5.12
+datarobot-drum==1.5.13

public_dropin_environments/python3_pytorch/env_info.json

@@ -3,6 +3,6 @@
   "name": "[DataRobot] Python 3 PyTorch Drop-In",
   "description": "This template environment can be used to create artifact-only PyTorch custom models. This environment contains PyTorch and requires only your model artifact as a .pth file, any other code needed to deserialize your model, and optionally a custom.py file.",
   "programmingLanguage": "python",
-  "environmentVersionId": "614235a4eef323a0d7af0c4f",
+  "environmentVersionId": "61451f149f56415553ced14e",
   "isPublic": true
 }

public_dropin_environments/python3_sklearn/dr_requirements.txt

@@ -1,2 +1,2 @@
 pyarrow==0.14.1
-datarobot-drum==1.5.12
+datarobot-drum==1.5.13

public_dropin_environments/python3_sklearn/env_info.json

@@ -3,6 +3,6 @@
   "name": "[DataRobot] Python 3 Scikit-Learn Drop-In",
   "description": "This template environment can be used to create artifact-only scikit-learn custom models. This environment contains scikit-learn and only requires your model artifact as a .pkl file and optionally a custom.py file.",
   "programmingLanguage": "python",
-  "environmentVersionId": "614235a4eef323a0d7af0c53",
+  "environmentVersionId": "61451f149f56415553ced14f",
   "isPublic": true
 }

public_dropin_environments/python3_xgboost/dr_requirements.txt

@@ -1,2 +1,2 @@
 pyarrow==0.14.1
-datarobot-drum==1.5.12
+datarobot-drum==1.5.13

public_dropin_environments/python3_xgboost/env_info.json

@@ -3,6 +3,6 @@
   "name": "[DataRobot] Python 3 XGBoost Drop-In",
   "description": "This template environment can be used to create artifact-only xgboost custom models. This environment contains xgboost and only requires your model artifact as a .pkl file and optionally a custom.py file.",
   "programmingLanguage": "python",
-  "environmentVersionId": "614235a4eef323a0d7af0c4c",
+  "environmentVersionId": "61451f149f56415553ced150",
   "isPublic": true
 }

public_dropin_environments/r_lang/dr_requirements.txt

@@ -2,4 +2,4 @@ numpy==1.19.5
 pandas==1.0.5
 rpy2<=3.3.6
 pyarrow==0.14.1
-datarobot-drum[R]==1.5.12
+datarobot-drum[R]==1.5.13

public_dropin_environments/r_lang/env_info.json

@@ -3,6 +3,6 @@
   "name": "[DataRobot] R Drop-In",
   "description": "This template environment can be used to create artifact-only R custom models that use the caret library. Your custom model archive need only contain your model artifacts if you use the environment correctly.",
   "programmingLanguage": "r",
-  "environmentVersionId": "614235a4eef323a0d7af0c4e",
+  "environmentVersionId": "61451f149f56415553ced14d",
   "isPublic": true
 }