Hi using designer, I have not been able to make the modeling using xgboost possible.
Please show how to do this in custom python modeling script.

The log output in azure ML designer changed the log format.

Used to be in azureml-logs file 70_driver_log.txt.

It used to capture stdout text out which I use for logging.

Where is it captured now?

After I have created a pipeline on Azure ML Designer, I'm not able to create an inference pipeline.
When I click on that option, it does nothing.

Background:
We have successfully deployed a pipeline that incorporates an "Web Service Input", "Enter Data Manually", "Execute Python Script" & "Web Service output" modules, which interacts with the GPT-3.5 Turbo hosted on Azure OpenAI. The script within python module takes prompts from a script bundle and inputs from both the "enter_data_manually" and the "web service input" ports(Screenshot is attached below)

Issue:
The primary concern is the significant delay in response time from the deployed endpoint. Despite efforts to optimize the deployment, including scaling the AksCompute from Standard_A2_v2 to higher specifications such as Standard_A4_v2 and Standard_A8_v2, the response time remains consistently high at approximately 8-9 seconds minimum (Postman screenshot is attached)

Steps Taken:

1. Increased AksCompute specifications (Standard_A4_v2 and Standard_A8_v2).
2. Tested deployment in the same location as the Azure OpenAI subscription.
3. Checked Application insights
   
   

Having successfully completed a successful job training a model in designer I have been getting error messages when trying to create a batch inference pipeline. The most recent relates to one designer component to create indicator variables. The batch inference pipeline job fails to create the TD and throws out a "An item with the same key has already been added. Key: Indicator_values_transformation". This has happened before with a cleaning data transformation step, which I needed to remove. The validate button does not pick up on any issue with respect to this which is also puzzling - if node information naming convention is limited to no duplication across components then a simple fix would be to ensure the validator picks up on this error. An example of the most recent error message is:

UserError
An item with the same key has already been added. Key: Indicator_values_transformation
Properties
Stack trace
Error: Request failed with status code 400
    at e.exports (https://ml.azure.com/static/js/index.4c6d02e5.chunk.js:2:3161896)
    at Soal.e.exports (https://ml.azure.com/static/js/index.4c6d02e5.chunk.js:2:1999144)
    at XMLHttpRequest.y (https://ml.azure.com/static/js/index.4c6d02e5.chunk.js:2:1079868)
Target
-
Client request ID
4058b1f6-0d44-4408-ba3a-4f451a4c1298
Trace ID
66ed3c4b-3246-4ad9-9869-e87a87228909
Service request ID
-

YAML

{
  "error": {
    "code": "UserError",
    "message": "An item with the same key has already been added. Key: Indicator_values_transformation",
    "additionalInfo": null,
    "details": []
  },
  "correlation": {
    "operation": "61ae723306a24d1b9db01e4f723d4beb",
    "request": "8337dcab96838c3b"
  }
}