calibrate-model-for.qaic
Automatically generated README for this automation recipe: calibrate-model-for.qaic
Category: AI/ML optimization
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 "qaic calibrate profile qaic-profile qaic-calibrate" --help
Run this script
Run this script via CLI
cm run script --tags=qaic,calibrate,profile,qaic-profile,qaic-calibrate[,variations]
Run this script via CLI (alternative)
cmr "qaic calibrate profile qaic-profile qaic-calibrate [variations]"
Run this script from Python
import cmind
r = cmind.access({'action':'run'
'automation':'script',
'tags':'qaic,calibrate,profile,qaic-profile,qaic-calibrate'
'out':'con',
...
(other input keys for this script)
...
})
if r['return']>0:
print (r['error'])
Run this script via Docker (beta)
cm docker script "qaic calibrate profile qaic-profile qaic-calibrate[variations]"
Variations
-
No group (any combination of variations can be selected)
Click here to expand this section.
_first.#
-
Group "batch-size"
Click here to expand this section.
_bs.#
- ENV variables:
- CM_QAIC_MODEL_BATCH_SIZE:
#
- CM_CREATE_INPUT_BATCH:
yes
- CM_QAIC_MODEL_BATCH_SIZE:
- ENV variables:
_bs.1
- ENV variables:
- CM_QAIC_MODEL_BATCH_SIZE:
1
- CM_CREATE_INPUT_BATCH:
yes
- CM_QAIC_MODEL_BATCH_SIZE:
- ENV variables:
-
Group "calib-dataset-filter-size"
Click here to expand this section.
_filter-size.#
-
Group "calibration-option"
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_mlperf.option1
_mlperf.option2
-
Group "model"
Click here to expand this section.
_bert-99
- ENV variables:
- CM_CALIBRATE_SQUAD:
yes
- CM_QAIC_COMPILER_ARGS: ``
- CM_QAIC_COMPILER_PARAMS:
-onnx-define-symbol=batch_size,1 -onnx-define-symbol=seg_length,<<<CM_DATASET_SQUAD_TOKENIZED_MAX_SEQ_LENGTH>>> -input-list-file=<<<CM_DATASET_SQUAD_TOKENIZED_PACKED_FILENAMES_FILE>>> -num-histogram-bins=512 -profiling-threads=<<<CM_HOST_CPU_PHYSICAL_CORES_PER_SOCKET>>>
- CM_QAIC_MODEL_TO_CONVERT:
calibrate_bert_mlperf
- CM_CALIBRATE_SQUAD:
- ENV variables:
_resnet50
- ENV variables:
- CM_QAIC_MODEL_NAME:
resnet50
- CM_CALIBRATE_IMAGENET:
yes
- CM_QAIC_COMPILER_ARGS: ``
- CM_QAIC_COMPILER_PARAMS:
-output-node-name=ArgMax -profiling-threads=<<<CM_HOST_CPU_PHYSICAL_CORES_PER_SOCKET>>>
- CM_QAIC_OUTPUT_NODE_NAME:
-output-node-name=ArgMax
- CM_QAIC_MODEL_TO_CONVERT:
calibrate_resnet50_tf
- CM_QAIC_MODEL_NAME:
- ENV variables:
_retinanet
- ENV variables:
- CM_QAIC_MODEL_NAME:
retinanet
- CM_CALIBRATE_OPENIMAGES:
yes
- CM_QAIC_COMPILER_ARGS: ``
- CM_QAIC_COMPILER_PARAMS:
-enable-channelwise -profiling-threads=<<<CM_HOST_CPU_PHYSICAL_CORES_PER_SOCKET>>> -onnx-define-symbol=batch_size,<<<CM_QAIC_MODEL_BATCH_SIZE>>> -node-precision-info=<<<CM_ML_MODEL_RETINANET_QAIC_NODE_PRECISION_INFO_FILE_PATH>>>
- CM_QAIC_MODEL_TO_CONVERT:
calibrate_retinanet_no_nms_mlperf
- CM_QAIC_MODEL_NAME:
- ENV variables:
-
Group "model-framework"
Click here to expand this section.
_tf
-
Group "seq-length"
Click here to expand this section.
_seq.#
- ENV variables:
- CM_DATASET_SQUAD_TOKENIZED_MAX_SEQ_LENGTH:
#
- CM_DATASET_SQUAD_TOKENIZED_MAX_SEQ_LENGTH:
- ENV variables:
_seq.384
- ENV variables:
- CM_DATASET_SQUAD_TOKENIZED_MAX_SEQ_LENGTH:
#
- CM_DATASET_SQUAD_TOKENIZED_MAX_SEQ_LENGTH:
- ENV variables:
Native script being run
No run file exists for Windows
Script output
cmr "qaic calibrate profile qaic-profile qaic-calibrate [variations]" -j