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.

LibrarySupported Version
Python3.8.6 and above
onnxonnx==1.12.0
tensorflowtensorflow==2.9.3
keraskeras==2.9.0
pytorchtorch==2.0.0
sk-learn aka scikit-learnscikit-learn==1.3.0
statsmodelsstatsmodels==0.13.2
XGBoostxgboost==1.7.4
MLFlowmlflow==1.3.0

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. The exception are BYOP models, which can accept optional inputs.
  • datetime data types must be converted to string.
  • ONNX models support multiple inputs only of the same data type.
RuntimeBFloat16*Float16Float32Float64
ONNXXX
TensorFlowXXX
MLFlowXXX
  • * (Brain Float 16, represented internally as a f32)

RuntimeInt8Int16Int32Int64
ONNXXXXX
TensorFlowXXXX
MLFlowXXXX
RuntimeUint8Uint16Uint32Uint64
ONNXXXXX
TensorFlowXXXX
MLFlowXXXX
RuntimeBooleanUtf8 (String)Complex 64Complex 128FixedSizeList*
ONNXX
TensorXXX
MLFlowXXX
  • * 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?
"requests_toolbelt>=0.9.1,<1",
# 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