prepare-training-data-bert
Automatically generated README for this automation recipe: prepare-training-data-bert
Category: MLPerf benchmark support
License: Apache 2.0
- CM meta description for this script: _cm.json
- Output cached? True
Reuse this script in your project
Install MLCommons CM automation meta-framework
Pull CM repository with this automation recipe (CM script)
cm pull repo mlcommons@cm4mlops
Print CM help from the command line
cmr "prepare mlperf training data input bert" --help
Run this script
Run this script via CLI
cm run script --tags=prepare,mlperf,training,data,input,bert[,variations] [--input_flags]
Run this script via CLI (alternative)
cmr "prepare mlperf training data input bert [variations]" [--input_flags]
Run this script from Python
import cmind
r = cmind.access({'action':'run'
'automation':'script',
'tags':'prepare,mlperf,training,data,input,bert'
'out':'con',
...
(other input keys for this script)
...
})
if r['return']>0:
print (r['error'])
Run this script via Docker (beta)
cm docker script "prepare mlperf training data input bert[variations]" [--input_flags]
Variations
-
Group "implementation"
Click here to expand this section.
_nvidia
(default)- ENV variables:
- CM_TMP_VARIATION:
nvidia
- CM_TMP_VARIATION:
- ENV variables:
_reference
- ENV variables:
- CM_TMP_VARIATION:
reference
- CM_TMP_VARIATION:
- ENV variables:
Default variations
_nvidia
Script flags mapped to environment
--clean=value
→CM_MLPERF_TRAINING_CLEAN_TFRECORDS=value
--data_dir=value
→CM_DATA_DIR=value
Native script being run
No run file exists for Windows
Script output
cmr "prepare mlperf training data input bert [variations]" [--input_flags] -j