Wallaroo SDK Guides

Reference Guide for the most essential Wallaroo SDK Commands

The following ML Model versions and Python libraries are supported by Wallaroo. When using the Wallaroo autoconversion library or working with a local version of the Wallaroo SDK, use the following versions for maximum compatibility.

Library Supported Version
Python 3.8.6 and above
onnx onnx==1.12.1
tensorflow tensorflow==2.9.3
keras keras==2.9.0
pytorch torch==1.13.1
sk-learn aka scikit-learn scikit-learn==1.3.0
statsmodels statsmodels==0.13.2
XGBoost xgboost==1.7.4
MLFlow xgboost==1.7.4

Supported Data Types

The following data types are supported for transporting data to and from Wallaroo in the following run times:

  • ONNX
  • TensorFlow
  • MLFlow

Data Type Conditions

The following conditions apply to data types used in inference requests.

  • None or Null data types are not submitted. All fields must have submitted values that match their data type. For example, if the schema expects a float value, then some value of type float must be submitted and can not be None or Null. If a schema expects a string value, then some value of type string must be submitted, etc.
  • datetime data types must be converted to string.
  • ONNX models support multiple inputs only of the same data type.
Runtime BFloat16* Float16 Float32 Float64
TensorFlow X X X
MLFlow X X X
  • * (Brain Float 16, represented internally as a f32)

Runtime Int8 Int16 Int32 Int64
TensorFlow X X X X
MLFlow X X X X
Runtime Uint8 Uint16 Uint32 Uint64
TensorFlow X X X X
MLFlow X X X X
Runtime Boolean Utf8 (String) Complex 64 Complex 128 FixedSizeList*
Tensor X X X
MLFlow X X X
  • * Fixed sized lists of any of the previously supported data types.

When using the Wallaroo SDK, it is recommended that the Python modules used are the same as those used in the Wallaroo JupyterHub environments to ensure maximum compatibility. When installing modules in the Wallaroo JupyterHub environments, do not override the following modules or versions, as that may impact how the JupyterHub environments performance.

"appdirs == 1.4.4",
"gql == 3.4.0",
"ipython == 7.24.1",
"matplotlib == 3.5.0",
"numpy == 1.22.3",
"orjson == 3.8.0",
"pandas == 1.3.4",
"pyarrow == 12.0.1",
"PyJWT == 2.4.0",
"python_dateutil == 2.8.2",
"PyYAML == 6.0",
"requests == 2.25.1",
"scipy == 1.8.0",
"seaborn == 0.11.2",
"tenacity == 8.0.1",
# Required by gql?
# Required by the autogenerated ML Ops client
"httpx >= 0.15.4,<0.24.0",
"attrs >= 21.3.0",
# These are documented as part of the autogenerated ML Ops requirements
# "python = ^3.7",
# "python-dateutil = ^2.8.0",

Wallaroo SDK Install Guides

How to install the Wallaroo SDK

Wallaroo SDK Essentials Guide

Reference Guide for the most essential Wallaroo SDK Commands

Wallaroo SDK Reference Guide

Wallaroo SDK Reference Guide