hello,
I'm installing Azure Machine learning workspace using the script "quick_setup"
here are some thing which are not working :
line 293 : $mlExtensionName = az extension list --query "[?name=='azure-cli-ml'].name" --output tsv
azure-cli-ml is not the proper name, it's "ml" only now

line 146 : $res = az ml workspace create --workspace-name $workspaceName --resource-group $resourceGroupName --storage-account $storageAccountId

"--storage-account" is not a valid parameters now (https://learn.microsoft.com/en-us/cli/azure/ml/workspace?view=azure-cli-latest#az-ml-workspace-create)

and there are many other thinks like "Invalid ARM Id /subscriptions/94a144ed-a2" after executing the "az ml workspace create"

thanks for corrections !

Hello,

A business consultant reported me that the demand forecasting was failing in FO with a message saying that the pipeline run into an error.

After investigating, i found out this in user_logs/std_log.txt :

_Traceback (most recent call last):
  File "run.py", line 17, in <module>
    from azureml.pipeline.core import Pipeline, PipelineData
  File "/azureml-envs/azureml_f3f7e6c5fb83d94df23933000bf02da3/lib/python3.8/site-packages/azureml/pipeline/core/__init__.py", line 24, in <module>
    from .builder import PipelineStep, PipelineData, StepSequence
  File "/azureml-envs/azureml_f3f7e6c5fb83d94df23933000bf02da3/lib/python3.8/site-packages/azureml/pipeline/core/builder.py", line 17, in <module>
    from azureml.pipeline.core.graph import Graph, Node, InputPortBinding, OutputPortBinding, \
  File "/azureml-envs/azureml_f3f7e6c5fb83d94df23933000bf02da3/lib/python3.8/site-packages/azureml/pipeline/core/graph.py", line 36, in <module>
    from azureml.pipeline.core.pipeline_output_dataset import PipelineOutputAbstractDataset
  File "/azureml-envs/azureml_f3f7e6c5fb83d94df23933000bf02da3/lib/python3.8/site-packages/azureml/pipeline/core/pipeline_output_dataset.py", line 18, in <module>
    from azureml.data._dataprep_helper import dataprep_stub, dataprep
ImportError: cannot import name 'dataprep_stub' from 'azureml.data._dataprep_helper' (/azureml-envs/azureml_f3f7e6c5fb83d94df23933000bf02da3/lib/python3.8/site-packages/azureml/data/_dataprep_helper.py)_

To fix the issue, I had to update the "run.py" script in order to force importing the previous version (1.53) of the azureml-pipeline package. Then, I created a new version of the pipeline by executing the "api_trigger.py" and now, it is ok. I guess there is a breaking change in the new version (1.54) of the package ?

Best regards,
Mirko

When running the script from both D365 and with the sample data, getting several errors but it appears that this is the issue causing it in the std_txt file:

Expected a StepRun object but received <class 'azureml.core.run.Run'> instead.

I've also tried updating the ml packages to the latest version, but still getting the error.

We are getting below error, when we try to run Demand forecast experiment manually from newly created Azure Machine Learning workspace. However existing workspace working without any issue. Any one come across this issue?

Error Message:

Expected a StepRun object but received <class 'azureml.core.run.Run'> instead.
This usually indicates a package conflict with one of the dependencies of azureml-core or azureml-pipeline-core.
Please check for package conflicts in your python environment
Elapsed time: 0:28:38.617563
Cleaning up all outstanding Run operations, waiting 300.0 seconds
3 items cleaning up...
Cleanup took 0.2656395435333252 seconds
Traceback (most recent call last):
File "/azureml-envs/azureml_f3f7e6c5fb83d94df23933000bf02da3/lib/python3.8/site-packages/azureml/pipeline/core/run.py", line 295, in wait_for_completion
step_run.wait_for_completion(timeout_seconds=timeout_seconds - time_elapsed,
TypeError: wait_for_completion() got an unexpected keyword argument 'timeout_seconds'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "", line 197, in
File "", line 193, in main
File "/azureml-envs/azureml_f3f7e6c5fb83d94df23933000bf02da3/lib/python3.8/runpy.py", line 265, in run_path
return _run_module_code(code, init_globals, run_name,
File "/azureml-envs/azureml_f3f7e6c5fb83d94df23933000bf02da3/lib/python3.8/runpy.py", line 97, in _run_module_code
_run_code(code, mod_globals, init_globals,
File "/azureml-envs/azureml_f3f7e6c5fb83d94df23933000bf02da3/lib/python3.8/runpy.py", line 87, in _run_code
exec(code, run_globals)
File "run.py", line 163, in
runParallel(args.input_path, args.output_path)
File "run.py", line 140, in runParallel
run.wait_for_completion(show_output=True, timeout_seconds=parameters.timeout_seconds)
File "/azureml-envs/azureml_f3f7e6c5fb83d94df23933000bf02da3/lib/python3.8/site-packages/azureml/pipeline/core/run.py", line 310, in wait_for_completion
step_run.wait_for_completion(raise_on_error=raise_on_error)
File "/azureml-envs/azureml_f3f7e6c5fb83d94df23933000bf02da3/lib/python3.8/site-packages/azureml/core/run.py", line 882, in wait_for_completion
raise ActivityFailedException(error_details=json.dumps(error, indent=4))
azureml.exceptions._azureml_exception.ActivityFailedException: ActivityFailedException:
Message: Activity Failed:
{
"error": {
"code": "UserError",
"message": "Execution failed. User process 'python' exited with status code 42. Please check log file 'user_logs/std_log_5.txt' for error details. Error: Traceback (most recent call last):\n File "driver/amlbi_main.py", line 275, in \n main()\n File "driver/amlbi_main.py", line 226, in main\n sys.exit(exitcode_candidate)\nSystemExit: 42\n\n",
"messageParameters": {},
"details": []
},
"time": "0001-01-01T00:00:00.000Z",
"componentName": "CommonRuntime"
}
InnerException None
ErrorResponse
{
"error": {
"message": "Activity Failed:\n{\n "error": {\n "code": "UserError",\n "message": "Execution failed. User process 'python' exited with status code 42. Please check log file 'user_logs/std_log_5.txt' for error details. Error: Traceback (most recent call last):\n File \"driver/amlbi_main.py\", line 275, in \n main()\n File \"driver/amlbi_main.py\", line 226, in main\n sys.exit(exitcode_candidate)\nSystemExit: 42\n\n",\n "messageParameters": {},\n "details": []\n },\n "time": "0001-01-01T00:00:00.000Z",\n "componentName": "CommonRuntime"\n}"
}
}
File "run.py", line 163, in
runParallel(args.input_path, args.output_path)
File "run.py", line 140, in runParallel
run.wait_for_completion(show_output=True, timeout_seconds=parameters.timeout_seconds)
File "/azureml-envs/azureml_f3f7e6c5fb83d94df23933000bf02da3/lib/python3.8/site-packages/azureml/pipeline/core/run.py", line 310, in wait_for_completion
step_run.wait_for_completion(raise_on_error=raise_on_error)
File "/azureml-envs/azureml_f3f7e6c5fb83d94df23933000bf02da3/lib/python3.8/site-packages/azureml/core/run.py", line 882, in wait_for_completion
raise ActivityFailedException(error_details=json.dumps(error, indent=4))
azureml.exceptions._azureml_exception.ActivityFailedException: ActivityFailedException:
Message: Activity Failed:
{
"error": {
"code": "UserError",
"message": "Execution failed. User process 'python' exited with status code 42. Please check log file 'user_logs/std_log_5.txt' for error details. Error: Traceback (most recent call last):\n File "driver/amlbi_main.py", line 275, in \n main()\n File "driver/amlbi_main.py", line 226, in main\n sys.exit(exitcode_candidate)\nSystemExit: 42\n\n",
"messageParameters": {},
"details": []
},
"time": "0001-01-01T00:00:00.000Z",
"componentName": "CommonRuntime"
}
InnerException None
ErrorResponse
{
"error": {
"message": "Activity Failed:\n{\n "error": {\n "code": "UserError",\n "message": "Execution failed. User process 'python' exited with status code 42. Please check log file 'user_logs/std_log_5.txt' for error details. Error: Traceback (most recent call last):\n File \"driver/amlbi_main.py\", line 275, in \n main()\n File \"driver/amlbi_main.py\", line 226, in main\n sys.exit(exitcode_candidate)\nSystemExit: 42\n\n",\n "messageParameters": {},\n "details": []\n },\n "time": "0001-01-01T00:00:00.000Z",\n "componentName": "CommonRuntime"\n}"
}
}

Hi all,

Yesterday (12/04/2023) azureml-pipeline package for python has been updated. Running the forecast through the pipeline, the package will be updated and the pipeline won't work anymore giving the error below.

I fixed the error specifying the package version to install (1.49.0). Has someone find a different solution?

Thanks,
Giuseppe

Logs

Traceback (most recent call last):
  File "run.py", line 20, in <module>
    from azureml.pipeline.steps import ParallelRunConfig, ParallelRunStep
  File "/azureml-envs/azureml_f3f7e6c5fb83d94df23933000bf02da3/lib/python3.8/site-packages/azureml/pipeline/steps/__init__.py", line 26, in <module>
    from .automl_step import AutoMLStep, AutoMLStepRun
  File "/azureml-envs/azureml_f3f7e6c5fb83d94df23933000bf02da3/lib/python3.8/site-packages/azureml/pipeline/steps/automl_step.py", line 26, in <module>
    from azureml.train.automl import constants
  File "/azureml-envs/azureml_f3f7e6c5fb83d94df23933000bf02da3/lib/python3.8/site-packages/azureml/train/automl/__init__.py", line 26, in <module>
    from azureml.train.automl.automlconfig import AutoMLConfig
  File "/azureml-envs/azureml_f3f7e6c5fb83d94df23933000bf02da3/lib/python3.8/site-packages/azureml/train/automl/automlconfig.py", line 17, in <module>
    from azureml._common._error_definition.user_error import \
ImportError: cannot import name 'ArgsNotSupportedForScenario' from 'azureml._common._error_definition.user_error' (/azureml-envs/azureml_f3f7e6c5fb83d94df23933000bf02da3/lib/python3.8/site-packages/azureml/_common/_error_definition/user_error.py)

Hello Team,

I was trying to follow this repo, inside my AML WS and when I added the files and tried to run them, I got multiple errors:

When I run the run.py file I get: AttributeError: '_OfflineRun' object has no attribute 'experiment'

When I run the api_trigger.py file I get:

azureuser@ruaburub3:~/cloudfiles/code/Users/ruaburub$ python api_trigger.py
Pipeline does not exists, creating new: TriggerDemandForecastGeneration
Traceback (most recent call last):
File "api_trigger.py", line 48, in
pipelineEndpoint = PipelineEndpoint.publish(workspace = workspace, name = pipelineName, pipeline=pipeline, description="Initiate demand forecast generation.")
File "/anaconda/envs/azureml_py38/lib/python3.8/site-packages/azureml/pipeline/core/pipeline_endpoint.py", line 323, in publish
pipeline = pipeline.publish(name=pipeline_name, description="Description for " + pipeline_name)
File "/anaconda/envs/azureml_py38/lib/python3.8/site-packages/azureml/pipeline/core/pipeline.py", line 309, in publish
return self.graph._save(name=name, description=description, version=version,
File "/anaconda/envs/azureml_py38/lib/python3.8/site-packages/azureml/pipeline/core/graph.py", line 3844, in _save
self._validate_and_finalize(pipeline_parameters=None, regenerate_outputs=regenerate_outputs)
File "/anaconda/envs/azureml_py38/lib/python3.8/site-packages/azureml/pipeline/core/graph.py", line 3863, in _validate_and_finalize
self.finalize(dry_run=False, regenerate_outputs=regenerate_outputs)
File "/anaconda/envs/azureml_py38/lib/python3.8/site-packages/azureml/pipeline/core/graph.py", line 3609, in finalize
Graph._check_threadpool_exceptions(done, not_done)
File "/anaconda/envs/azureml_py38/lib/python3.8/site-packages/azureml/pipeline/core/graph.py", line 3734, in _check_threadpool_exceptions
raise ex
File "/anaconda/envs/azureml_py38/lib/python3.8/concurrent/futures/thread.py", line 57, in run
result = self.fn(*self.args, **self.kwargs)
File "/anaconda/envs/azureml_py38/lib/python3.8/site-packages/azureml/pipeline/core/graph.py", line 3596, in get_or_create_module_for_fingerprint
raise ex
File "/anaconda/envs/azureml_py38/lib/python3.8/site-packages/azureml/pipeline/core/graph.py", line 3594, in get_or_create_module_for_fingerprint
module_id = node._module_builder.build()
File "/anaconda/envs/azureml_py38/lib/python3.8/site-packages/azureml/pipeline/core/_module_builder.py", line 62, in build
module_id = self._module_provider.create_module(
File "/anaconda/envs/azureml_py38/lib/python3.8/site-packages/azureml/pipeline/core/_aeva_provider.py", line 327, in create_module
module_entity = _AevaModuleProvider.module_creation(module_def, content_path,
File "/anaconda/envs/azureml_py38/lib/python3.8/site-packages/azureml/pipeline/core/_aeva_provider.py", line 293, in module_creation
storage_id = module_uploader.upload(directory=content_path)
File "/anaconda/envs/azureml_py38/lib/python3.8/site-packages/azureml/pipeline/core/_aeva_provider.py", line 81, in upload
storage_id = snapshots_client.create_snapshot(directory)
File "/anaconda/envs/azureml_py38/lib/python3.8/site-packages/azureml/_restclient/snapshots_client.py", line 110, in create_snapshot
self._validate_snapshot_file_count(file_or_folder_path, len(entries_to_send), raise_on_validation_failure)
File "/anaconda/envs/azureml_py38/lib/python3.8/site-packages/azureml/_restclient/snapshots_client.py", line 79, in _validate_snapshot_file_count
raise SnapshotException(error_message)
azureml.exceptions._azureml_exception.SnapshotException: SnapshotException:
Message: ====================================================================

While attempting to take snapshot of /mnt/batch/tasks/shared/LS_root/mounts/clusters/ruaburub3/code/Users/ruaburub
Your project exceeds the file limit of 2000.

====================================================================

    InnerException None
    ErrorResponse 

{
"error": {
"message": "====================================================================\n\nWhile attempting to take snapshot of /mnt/batch/tasks/shared/LS_root/mounts/clusters/ruaburub3/code/Users/ruaburub\nYour project exceeds the file limit of 2000.\n\n====================================================================\n\n"
}
}

And When I run the forecast.r I get:
azureuser@ruaburub3:~/cloudfiles/code/Users/ruaburub/REntryScript$ Rscript forecast.r
/bin/bash: /anaconda/envs/azureml_py38/lib/libtinfo.so.6: no version information available (required by /bin/bash)
Error in library(forecast) : there is no package called ‘forecast’
Execution halted

This is how my files look like:

ERROR: Could not find a version that satisfies the requirement azureml-data (from versions: none)
ERROR: No matching distribution found for azureml-data

We are getting below error, from last three weeks (this issue appearing when creating new pipeline or running existing from Demand forecast), any one come across this issue?

Error:
Expected a StepRun object but received <class 'azureml.core.run.Run'> instead.
This usually indicates a package conflict with one of the dependencies of azureml-core or azureml-pipeline-core.
Please check for package conflicts in your python environment
Elapsed time: 0:14:03.650006
Cleaning up all outstanding Run operations, waiting 300.0 seconds
3 items cleaning up...
Cleanup took 0.235382080078125 seconds
Traceback (most recent call last):
File "/azureml-envs/azureml_f3f7e6c5fb83d94df23933000bf02da3/lib/python3.8/site-packages/azureml/pipeline/core/run.py", line 295, in wait_for_completion
step_run.wait_for_completion(timeout_seconds=timeout_seconds - time_elapsed,
TypeError: wait_for_completion() got an unexpected keyword argument 'timeout_seconds'

The compute instance name is hardcoded in quick_setup.ps1, but is required to be unique within the Azure region. Creation is likely to fail with a message similar to:

ERROR: {'Azure-cli-ml Version': '1.41.0', 'Error': ComputeTargetException:
        Message: Compute name 'notebookScryptExecutor' is not available. Reason: AlreadyExists. Message: The specified name notebookScryptExecutor is already in use and is therefore unavailable
        InnerException None
        ErrorResponse
{
    "error": {
        "message": "Compute name 'notebookScryptExecutor' is not available. Reason: AlreadyExists. Message: The specified name notebookScryptExecutor is already in use and is therefore unavailable"
    }
}}

Modifying the script to change the name is an effective workaround.