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get-ml-model-dlrm-terabyte

Automatically generated README for this automation recipe: get-ml-model-dlrm-terabyte

Category: AI/ML models

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

cmr "get ml-model dlrm raw terabyte criteo-terabyte criteo recommendation" --help

Run this script

Run this script via CLI
cm run script --tags=get,ml-model,dlrm,raw,terabyte,criteo-terabyte,criteo,recommendation[,variations] [--input_flags]
Run this script via CLI (alternative)
cmr "get ml-model dlrm raw terabyte criteo-terabyte criteo recommendation [variations]" [--input_flags]
Run this script from Python
import cmind

r = cmind.access({'action':'run'
              'automation':'script',
              'tags':'get,ml-model,dlrm,raw,terabyte,criteo-terabyte,criteo,recommendation'
              'out':'con',
              ...
              (other input keys for this script)
              ...
             })

if r['return']>0:
    print (r['error'])
Run this script via Docker (beta)
cm docker script "get ml-model dlrm raw terabyte criteo-terabyte criteo recommendation[variations]" [--input_flags]

Variations

  • No group (any combination of variations can be selected)

    Click here to expand this section.

    • _debug
      • ENV variables:
        • CM_ML_MODEL_DEBUG: yes

  • Group "download-tool"

    Click here to expand this section.

    • _rclone
    • _wget

  • Group "framework"

    Click here to expand this section.

    • _onnx
      • ENV variables:
        • CM_ML_MODEL_FRAMEWORK: onnx
    • _pytorch (default)
      • ENV variables:
        • CM_ML_MODEL_FRAMEWORK: pytorch
        • CM_TMP_MODEL_ADDITIONAL_NAME: dlrm_terabyte.pytorch

  • Group "precision"

    Click here to expand this section.

    • _fp32 (default)
      • ENV variables:
        • CM_ML_MODEL_INPUT_DATA_TYPES: fp32
        • CM_ML_MODEL_PRECISION: fp32
        • CM_ML_MODEL_WEIGHT_DATA_TYPES: fp32

  • Group "type"

    Click here to expand this section.

    • _weight_sharded (default)
      • ENV variables:
        • CM_DLRM_MULTIHOT_MODEL: yes
Default variations

_fp32,_pytorch,_weight_sharded

Script flags mapped to environment

  • --dir=value → CM_DOWNLOAD_PATH=value
  • --download_path=value → CM_DOWNLOAD_PATH=value
  • --to=value → CM_DOWNLOAD_PATH=value

Native script being run

No run file exists for Windows

Script output

cmr "get ml-model dlrm raw terabyte criteo-terabyte criteo recommendation [variations]" [--input_flags] -j