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fix(train): use valid shell identifiers for channel and hyperparameter env names - #6439
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…r env names
The training container's script sources /opt/ml/input/sm_training.env under
'set -e' with an ERR trap. Channel names and hyperparameter keys may contain
'-' or '.' (allowed by the API, e.g. channel 'train-data' or key 'model.lr'),
which produced exports such as SM_CHANNEL_TRAIN-DATA=... that bash rejects
('not a valid identifier'), killing the job before the entry script ran.
Map non-identifier characters in variable names to '_' (SM_HP_* already did
this for '-'). aws#6517 already shell-quotes the values. Applied to the
sagemaker-train and sagemaker-core copies.
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Issue #, if available: N/A
Description of changes:
Narrowed after #6517, which shell-quotes the values written to
sm_training.env. Variable names were still a problem.The training container sources
/opt/ml/input/sm_training.envunderset -ewith an ERR trap. Channel names and hyperparameter keys may contain-or.(allowed by the API, e.g. channeltrain-dataor keymodel.lr), which produces:That kills the job before the entry script runs.
This change maps characters that aren't valid in a shell identifier to
_in the variable names;SM_HP_*already did this for-. It's applied to both the sagemaker-train and the sagemaker-core copies ofenvironment.py.Testing:
train-datachannel, amodel.lrkey and anit's a testvalue, then sources it withbash -c 'set -e; trap ... ERR; source ...'and checks the values. Both fail on master.By submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice.