CODEWITHSUNDEEP
pythonazuretensorflowcondaml-studio
aishah
aishah

Reputation: 43

Python code failed in Azure ML Experiments but runs in conda environment

I have created custom conda environment in my Azure ML compute instance and has verified that the python code runs in the environment. However, when I submit the .py file in Azure ML Experiment, the run fails even with the same conda environment set for the experiment.

This is how I submit the experiment:

ws = Workspace.from_config()
compute_name = os.environ.get("AML_COMPUTE_CLUSTER_NAME", "mycompute_cluster")
compute_target = ws.compute_targets[compute_name]
env = Environment.from_existing_conda_environment('expEnv', "myEnv")
experiment = Experiment(workspace=ws, name='exp')
config = ScriptRunConfig(source_directory='./',
                             script='exp1.py',
                             compute_target=compute_target)

config.run_config.environment = env
run = experiment.submit(config)
aml_url = run.get_portal_url()
print(aml_url)

I also tried with creating Azure ML Environments from the conda YAML file and using it when submitting the experiment, but I still get the same error.

Error:

UserError: module 'tensorflow.python.training.experimental.mixed_precision' has no attribute '_register_wrapper_optimizer_cls'

Upvotes: 2

Views: 307

Answers (1)

Utkarsh Pal
Utkarsh Pal

Reputation: 4544

It seems the required module is missing or renamed. You need to make sure you are using the same module version in your code which has required attribute.

Additionally, you might need to install module tf-nightly using pip3 install tf-nightly command as suggested by @HarshithaVeeramalla-MT in comment section.

Upvotes: 1

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