Oracle Cloud Infrastructure Documentation

ONNX

Learn about ONNX conda environments.

ONNX 1.13 for CPU on Python 3.9 (version 1.0)

A description of the ONNX 1.13 for CPU on Python 3.9 (version 1.0) conda environment.

Released

May 25, 2023

Description

This environment includes oracle-ads, onnx, onnxruntime, and their dependencies. The purpose of this environment is to offer a runtime for your ONNX model artifacts. ONNX is an open source, open model format that enables you to save a model from different machine learning (ML) libraries into a single, portable format that's independent of the training library. ONNX models can be deployed using model deployments. You can use this conda environment to convert models from different ML libraries into ONNX format, including the Oracle Labs AutoML model. Use ONNX for runtime inferencing, and plotting your model workflow.

To get started with this conda environment, review the Getting Started notebook, using the Launcher.

Python Version

3.9
Slug

onnx113_p39_cpu_v1
Object Storage Path 
oci://service-conda-packs@id19sfcrra6z/service_pack/cpu/ONNX_1.10_for_CPU_on_Python_3.9/1.0/onnx113_p39_cpu_v1

Top Libraries

  • onnx (v1.13.0)

  • onnxconverter-common (v1.13.0)

  • onnxmltools (v1.11.0)

  • onnxruntime (v1.14.1)

  • oracle-ads (v2.8.5)

  • scikit-learn (v1.1.1)

  • lightgbm (v3.3.5)

  • xgboost (v1.7.3)

For a complete list of preinstalled Python libraries, see onnx113_p39_cpu_v1.txt.
ONNX 1.13 for GPU on Python 3.9 (version 1.0)

A description of the ONNX 1.13 for GPU on Python 3.9 (version 1.0) conda environment.

Released

July 10, 2023

Description

This environment includes oracle-ads, onnx, onnxruntime, and their dependencies. The purpose of this environment is to offer a runtime for your ONNX model artifacts. ONNX is an open source, open model format that enables you to save a model from different machine learning (ML) libraries into a single, portable format that's independent of the training library. ONNX models can be deployed using model deployments. You can use this conda environment to convert models from different ML libraries into ONNX format, including the Oracle Labs AutoML model. Use ONNX for runtime inferencing, and plotting your model workflow.

To get started with this conda environment, review the Getting Started notebook, using the Launcher.

Python Version

3.9
Slug

onnx113_p39_gpu_v1
Object Storage Path 
oci://service-conda-packs@id19sfcrra6z/service_pack/gpu/ONNX_1.10_for_GPU_on_Python_3.9/1.0/onnx113_p39_gpu_v1

Top Libraries

  • onnx (v1.13.1)

  • onnxconverter-common (v1.13.0)

  • onnxmltools (v1.11.2)

  • onnxruntime_gpu (v1.15.1)

  • oracle-ads (v2.8.7)

  • scikit-learn (v1.1.1)

For a complete list of preinstalled Python libraries, see onnx110_p39_gpu_v1.txt.