Table of Contents

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  1. Preface
  2. Informatica Intelligent Cloud Services REST API
  3. Platform REST API version 2 resources
  4. Platform REST API version 3 resources
  5. Data Integration REST API
  6. File Ingestion and Replication REST API
  7. Streaming Ingestion and Replication REST API
  8. Model Serve REST API
  9. RunAJob utility
  10. ParamSetCli utility
  11. REST API codes
  12. REST API resource quick references

REST API Reference

REST API Reference

Editing a machine learning model

Editing a machine learning model

Use the Documents resource to edit a machine learning model.

PATCH request

To edit a machine learning model, include the machine learning model ID in the URI. Use the following URI:
/frs/v1/Documents('<model ID>')
Get the model ID from the response to register a machine learning model.
Include the following fields in the request:
Field
Type
Description
name
String
Machine learning model asset name.
description
String
Optional. Description of the machine learning model.
documentType
String
Use
MLOPS_MODEL
.
nativeData
Object
Blob object that defines the machine learning model.
Include the following fields in the nativeData object:
Field
Type
Description
name
String
Machine learning model asset name.
framework
String
Framework used to create the machine learning model. Use one of the following values:
  • Python
  • PyTorch
  • TensorFlow
framework_type
String
Internal type of the framework.
For a Python model, use
Custom
.
For a PyTorch or TensorFlow model, use
Standard
.
file_id
String
Model file ID generated when you upload the model file.
file_name
String
Name of the model file. The name must match the file name you used to generate the model file ID.
size
String
Size of the model file in GB.
file_type
String
Use
zip
.
inputField
Input fields that the machine learning model expects. Include at least one input field.
name
String
Name of the field.
dataType
String
Data type of the field.
shape
String
Required for array data types. Shape of the array. For example,
[2,3]
.
outputField
Output fields that the machine learning model returns. Include at least one output field.
name
String
Name of the field.
dataType
String
Data type of the field.
shape
String
Required for array data types. Shape of the array. For example,
[2,3]
.

PATCH response

Returns a summary of the machine learning model.

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