Wallaroo SDK AWS Sagemaker Install Guide
How to install the Wallaroo SDK in AWS Sagemaker
The following guides demonstrate how to install the Wallaroo SDK in different environments. The Wallaroo SDK is installed by default into a Wallaroo instance for use with the JupyterHub service.
The Wallaroo SDK requires Python 3.8.6 and above and is available through the Wallaroo SDK Page.
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",
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==1.12.0 |
tensorflow | tensorflow==2.9.3 |
keras | keras==2.9.0 |
pytorch | torch==2.0.0 |
sk-learn aka scikit-learn | scikit-learn==1.3.0 |
statsmodels | statsmodels==0.13.2 |
XGBoost | xgboost==1.7.4 |
MLFlow | mlflow==1.3.0 |
The following data types are supported for transporting data to and from Wallaroo in the following run times:
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
.Runtime | BFloat16* | Float16 | Float32 | Float64 |
---|---|---|---|---|
ONNX | X | X | ||
TensorFlow | X | X | X | |
MLFlow | X | X | X |
* (Brain Float 16, represented internally as a f32)
Runtime | Int8 | Int16 | Int32 | Int64 |
---|---|---|---|---|
ONNX | X | X | X | X |
TensorFlow | X | X | X | X |
MLFlow | X | X | X | X |
Runtime | Uint8 | Uint16 | Uint32 | Uint64 |
---|---|---|---|---|
ONNX | X | X | X | X |
TensorFlow | X | X | X | X |
MLFlow | X | X | X | X |
Runtime | Boolean | Utf8 (String) | Complex 64 | Complex 128 | FixedSizeList* |
---|---|---|---|---|---|
ONNX | X | ||||
Tensor | X | X | X | ||
MLFlow | X | X | X |
* Fixed sized lists of any of the previously supported data types.
How to install the Wallaroo SDK in AWS Sagemaker
How to install the Wallaroo SDK in AzureML
How to install the Wallaroo SDK in Azure Databricks
How to install the Wallaroo SDK in Google Vertex
How to install the Wallaroo SDK in typical environment