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add hugging face dir and user identity for prediction job test #74

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merged 1 commit into from
Jan 8, 2025
+14 −2
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add hugging face dir and user identity for prediction job test #74

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16 changes: 14 additions & 2 deletions bajor/batch/predictions.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,6 +13,7 @@

# Zoobot Azure Batch predictions pool ID
predictions_pool_id = os.getenv('POOL_ID', 'predictions_0')
huggingface_dir = '$AZ_BATCH_NODE_SHARED_DIR/.cache/huggingface'

# wrapper functions to isolate the jobs to the training pool
def active_jobs_running():
Expand Down Expand Up @@ -84,9 +85,10 @@ def create_batch_job(job_id, manifest_url, pool_id, checkpoint_target='ZOOBOT_CH

# job preparation task
create_results_dir = f'mkdir -p $AZ_BATCH_NODE_MOUNTS_DIR/$PREDICTIONS_CONTAINER_MOUNT_DIR/$PREDICTIONS_JOB_RESULTS_DIR'
setup_huggingface_cache_dir = f'mkdir -p {huggingface_dir}'
copy_code_to_shared_dir = 'cp -Rf $AZ_BATCH_NODE_MOUNTS_DIR/$PREDICTIONS_CONTAINER_MOUNT_DIR/$CODE_DIR_PATH/* $AZ_BATCH_NODE_SHARED_DIR/'
job.job_preparation_task = batchmodels.JobPreparationTask(
command_line=f'/bin/bash -c \"set -ex; {create_results_dir}; {copy_code_to_shared_dir}\"',
command_line=f'/bin/bash -c \"set -ex; {create_results_dir}; {setup_huggingface_cache_dir}; {copy_code_to_shared_dir}\"',
constraints=batchmodels.TaskConstraints(max_task_retry_count=3),
user_identity = batchmodels.UserIdentity(
auto_user=batchmodels.AutoUserSpecification(
Expand Down Expand Up @@ -179,10 +181,11 @@ def create_job_tasks(job_id, task_id=1, run_opts=''):
# ZOOBOT command for catalogue predictions!
# see jobPreparation task for code setup
prediction_code_path = os.getenv('ZOOBOT_PREDICTION_CMD', 'predict_catalog_with_model.py')
setup_hugging_face_cache_env_var = f'HF_HOME={huggingface_dir}'
# TODO: perhaps we can add the output file extension as a job env param that can be modified by job runtime params
prediction_cmd = f'$AZ_BATCH_NODE_SHARED_DIR/{prediction_code_path} {run_opts} --checkpoint-path $AZ_BATCH_NODE_MOUNTS_DIR/$MODELS_CONTAINER_MOUNT_DIR/$ZOOBOT_CHECKPOINT_TARGET --catalog-url $MANIFEST_URL --save-path $AZ_BATCH_NODE_MOUNTS_DIR/$PREDICTIONS_CONTAINER_MOUNT_DIR/$PREDICTIONS_JOB_RESULTS_DIR/predictions.json'
# redirect the stdout to stderr for logging
command = f'/bin/bash -c \"set -ex; python {prediction_cmd}\"'
command = f'/bin/bash -c \"set -ex; {setup_hugging_face_cache_env_var}; python {prediction_cmd}\"'

# create a job task to run the Zoobot training system command via the zoobot docker conatiner
#
Expand All @@ -194,6 +197,15 @@ def create_job_tasks(job_id, task_id=1, run_opts=''):
working_directory='taskWorkingDirectory',
container_run_options='--ipc=host'
),
user_identity = batchmodels.UserIdentity(
auto_user=batchmodels.AutoUserSpecification(
scope=batchmodels.AutoUserScope.task,
elevation_level=batchmodels.ElevationLevel.admin
)
),
environment_settings=[
batchmodels.EnvironmentSetting(name="HF_HOME", value=huggingface_dir),
],
output_files=std_err_and_out
)
tasks.append(task)
Expand Down
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