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fix od batch scoring notebook #2220

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merged 3 commits into from
Apr 21, 2023
Merged

fix od batch scoring notebook #2220

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d902c5a
fix od batch scoring notebook
sharma-riti Apr 20, 2023
6813089
format file
sharma-riti Apr 20, 2023
46d3e20
update broken path
sharma-riti Apr 21, 2023
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41 changes: 35 additions & 6 deletions ...sk-fridge-items-batch-scoring/image-object-detection-batch-scoring-non-mlflow-model.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -813,7 +813,7 @@
"env = Environment(\n",
" name=\"automl-images-env\",\n",
" description=\"environment for automl images inference\",\n",
" image=\"mcr.microsoft.com/azureml/openmpi4.1.0-cuda11.1-cudnn8-ubuntu18.04\",\n",
" image=\"mcr.microsoft.com/azureml/openmpi4.1.0-cuda11.1-cudnn8-ubuntu20.04\",\n",
" conda_file=\"artifact_downloads/outputs/conda_env_v_1_0_0.yml\",\n",
")"
]
Expand Down Expand Up @@ -1079,7 +1079,7 @@
"# get the details of the job\n",
"job_name = job.name\n",
"batch_job = ml_client.jobs.get(name=job_name)\n",
"print(batch_job.status)\n",
"print(batch_job)\n",
"# stream the job logs\n",
"ml_client.jobs.stream(name=job_name)"
]
Expand All @@ -1097,13 +1097,42 @@
"metadata": {},
"outputs": [],
"source": [
"output_dir = \"./scoring_results\"\n",
"ml_client.jobs.download(\n",
" name=job.name, output_name=deployment.output_file_name, download_path=output_dir\n",
"from azureml.core import Experiment, Workspace\n",
"from azureml.pipeline.core import PipelineRun, StepRun, PortDataReference\n",
"\n",
"workspace_obj = Workspace(\n",
" subscription_id=ml_client.subscription_id,\n",
" resource_group=ml_client.resource_group_name,\n",
" workspace_name=ml_client.workspace_name,\n",
")\n",
"\n",
"# Get the Pipeline Run\n",
"experiment = Experiment(workspace=workspace_obj, name=batch_job.experiment_name)\n",
"pipeline_run = PipelineRun(experiment, batch_job.name)\n",
"\n",
"# Get the Step Run\n",
"step_run_id = pipeline_run.find_step_run(\"BatchScoring\")[0].id\n",
"node_id = pipeline_run.get_graph().node_name_dict[\"BatchScoring\"][0].node_id\n",
"print(\n",
" \"Pipeline Run ID: {} Step Run ID: {}, Step Run Node ID: {}\".format(\n",
" pipeline_run.id, step_run_id, node_id\n",
" )\n",
")\n",
"step_run = StepRun(experiment, step_run_id, pipeline_run.id, node_id)\n",
"\n",
"# Download Data\n",
"port_data_reference = step_run.get_output_data(\"score\")\n",
"port_data_reference.download(local_path=\".\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Print the first five lines of the output\n",
"result_file = os.path.join(output_dir, deployment.output_file_name)\n",
"result_file = os.path.join(\"azureml\", step_run_id, \"score\", deployment.output_file_name)\n",
"with open(result_file) as f:\n",
" for x in range(5):\n",
" print(next(f))"
Expand Down