Hi all, As we know Azure Machine Learning Studio (classic) has been deprecated. We can no longer create new workspaces for it in Azure. It has been replaced by the Azure Machine Learning Service, which provides similar functionality and more. But I am facing pipeline run issue, Can somebody please give insights?
I chose Option 2: Manually set up your machine learning workspace
When I run the pipeline from Machine learning studio manually with sampleInput.csv file, it runs successfully.
But, when the pipeline is triggered through D365 F&O application through Generate statistical baseline forecasting, pipeline fails with the below error message:
Execution failed. User process '/azureml-envs/azureml_f3f7e6c5fb83d94df23933000bf02da3/bin/python' exited with status code 1. Please check log file 'user_logs/std_log.txt' for error details. Error: dataflow = _transform_and_validate( File //azureml-envs/azureml_f3f7e6c5fb83d94df23933000bf02da3/lib/python3.8/site-packages/azureml/data/dataset_factory.py/, line 1225, in _transform_and_validate _validate_has_data(dataflow, 'Failed to validate the data.') File //azureml-envs/azureml_f3f7e6c5fb83d94df23933000bf02da3/lib/python3.8/site-packages/azureml/data/dataset_error_handling.py/, line 69, in _validate_has_data raise DatasetValidationError(error_message + '/' + e.compliant_message, exception=e)azureml.data.dataset_error_handling.DatasetValidationError: DatasetValidationError:  Message: Failed to validate the data.ScriptExecutionException was caused by StreamAccessException. StreamAccessException was caused by NotFoundException. Found no resources for the input provided: '[REDACTED]'| session_id=ed1dc30e-1477-4445-8f7f-d34bc9daec6e  InnerException None  ErrorResponse { /error/: { /code/: /UserError/, /message/: /Failed to validate the data./ScriptExecutionException was caused by StreamAccessException./ StreamAccessException was caused by NotFoundException./ Found no resources for the input provided: '[REDACTED]'/| session_id=ed1dc30e-1477-4445-8f7f-d34bc9daec6e/ }}
