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rsareddy0329Roja Reddy Sareddysage-makernargokul
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Revert the change "Add Numpy 2.0 support" (#5307)
* Add numpy 2.0 support * Add numpy 2.0 support * Add numpy 2.0 support * Add numpy 2.0 support * Add numpy 2.0 support * Fix incompatible_dependecies test * Fix incompatible_dependecies test * Fix incompatible_dependecies test * Fix incompatible_dependecies test * Fix incompatible_dependecies test * update tensorflow artifacts * update tensorflow artifacts * update tensorflow artifacts * testfile codestyle fixes * testfile codestyle fixes * update SKLearn image URI config * update SKLearn image URI config * docstyle fixes * docstyle fixes * numpy fixes * numpy fixes * numpy fixes * numpy fixes * numpy fixes * numpy fixes * numpy fixes * numpy fixes * numpy fix for slow test * numpy fix for slow test * numpy fix for slow test * numpy fix for slow test * Revert 'Add numpy 2.0 support' * Revert 'Add numpy 2.0 support' * Revert 'Add numpy 2.0 support' --------- Co-authored-by: Roja Reddy Sareddy <[email protected]> Co-authored-by: parknate@ <[email protected]> Co-authored-by: Gokul Anantha Narayanan <[email protected]>
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pyproject.toml

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"google-pasta",
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"importlib-metadata>=1.4.0,<7.0",
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"jsonschema",
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"numpy>=1.26.4,<2.3.3",
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"numpy==1.26.4",
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"omegaconf>=2.2,<3",
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"packaging>=23.0,<25",
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"pandas",
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scipy==1.13.0
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scipy==1.11.3

requirements/extras/test_requirements.txt

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tox==3.24.5
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numpy>=2.0.0, <2.3.3
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numpy==1.26.4
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build[virtualenv]==1.2.1
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flake8==7.1.2
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pytest==6.2.5
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sagemaker-experiments==0.1.35
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Jinja2==3.1.6
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pyvis==0.2.1
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pandas>=2.3.0
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scikit-learn==1.6.1
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pandas==1.4.4
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scikit-learn==1.3.0
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cloudpickle==2.2.1
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jsonpickle<4.0.0
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PyYAML>=6.0.1
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nbformat>=5.9,<6
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accelerate>=0.24.1,<=0.27.0
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schema==0.7.5
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tensorflow>=2.16.2,<=2.19.0
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tensorflow>=2.16.2,<=2.18.0
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mlflow>=2.14.2,<3
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huggingface_hub==0.26.2
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uvicorn>=0.30.1

src/sagemaker/image_uri_config/sklearn.json

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"us-west-2": "246618743249"
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},
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"repository": "sagemaker-scikit-learn"
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},
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"1.4-2": {
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"processors": [
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"cpu"
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],
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"py_versions": [
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"py3"
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],
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"registries": {
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"af-south-1": "510948584623",
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"ap-east-1": "651117190479",
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"ap-northeast-1": "354813040037",
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"ap-northeast-2": "366743142698",
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"ap-northeast-3": "867004704886",
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"ap-south-1": "720646828776",
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"ap-south-2": "628508329040",
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"ap-southeast-1": "121021644041",
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"ap-southeast-2": "783357654285",
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"ap-southeast-3": "951798379941",
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"ap-southeast-4": "106583098589",
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"ca-central-1": "341280168497",
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"ca-west-1": "190319476487",
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"cn-north-1": "450853457545",
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"cn-northwest-1": "451049120500",
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"eu-central-1": "492215442770",
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"eu-central-2": "680994064768",
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"eu-north-1": "662702820516",
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"eu-south-1": "978288397137",
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"eu-south-2": "104374241257",
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"eu-west-1": "141502667606",
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"eu-west-2": "764974769150",
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"eu-west-3": "659782779980",
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"il-central-1": "898809789911",
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"me-central-1": "272398656194",
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"me-south-1": "801668240914",
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"sa-east-1": "737474898029",
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"us-east-1": "683313688378",
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"us-east-2": "257758044811",
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"us-gov-east-1": "237065988967",
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"us-gov-west-1": "414596584902",
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"us-iso-east-1": "833128469047",
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"us-isob-east-1": "281123927165",
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"us-isof-east-1": "108575199400",
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"us-isof-south-1": "124985052026",
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"us-west-1": "746614075791",
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"us-west-2": "246618743249"
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},
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"repository": "sagemaker-scikit-learn"
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}
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}
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},

src/sagemaker/serve/utils/conda_in_process.yml

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- boto3>=1.34.142,<2.0
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- cloudpickle==2.2.1
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- google-pasta
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- numpy>=2.0.0,<2.3.3
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- numpy==1.26.4
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- protobuf>=3.12,<5.0
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- smdebug_rulesconfig==1.0.1
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- importlib-metadata>=1.4.0,<7.0
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- multiprocess>=0.70.14
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- networkx>=3.1
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- packaging>=23.1
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- pandas>=2.3.0
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- pandas>=1.5.3
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- pathos>=0.3.0
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- pillow>=9.5.0
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- platformdirs>=3.2.0
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scipy==1.13.0
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scipy==1.11.3

tests/data/serve_resources/mlflow/pytorch/MLmodel

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code: null
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model_data: data
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pytorch_version: 2.0.1+cu117
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mlflow_version: 2.10.2
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mlflow_version: 2.11.1
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model_size_bytes: 4971001
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model_uuid: 2d85043bbf504b1e9950e124c46a1719
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run_id: 98b8d2e2c0e74ab59f4c26f7cb3de233

tests/data/serve_resources/mlflow/pytorch/conda.yaml

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- conda-forge
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dependencies:
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- python=3.10.13
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- pip<=24.3
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- pip<=23.3.1
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- pip:
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- mlflow>=2.16.1
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- mlflow==2.10.2
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- astunparse==1.6.3
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- cffi==1.16.0
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- cloudpickle==2.2.1
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- defusedxml==0.7.1
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- dill==0.3.9
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- gmpy2==2.1.2
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- numpy>=2.0.0,<2.3.3
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- numpy==1.26.4
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- opt-einsum==3.3.0
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- packaging==24.0
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- pandas>=2.3.0
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- pandas==2.2.1
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- pyyaml==6.0.1
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- requests==2.31.0
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- torch>=2.6.0
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- torchvision>=0.17.0
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- tqdm==4.66.2
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- scikit-learn==1.6.1
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- scikit-learn==1.3.2
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name: mlflow-env

tests/data/serve_resources/mlflow/pytorch/requirements.txt

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defusedxml==0.7.1
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dill==0.3.9
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gmpy2==2.1.2
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numpy>=2.0.0,<2.3.3
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numpy==1.26.4
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opt-einsum==3.3.0
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packaging>=23.0,<25
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pandas>=2.3.0
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pandas==2.2.1
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pyyaml==6.0.1
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requests==2.32.4
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torch>=2.6.0

tests/data/serve_resources/mlflow/tensorflow/conda.yaml

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- conda-forge
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dependencies:
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- python=3.10.13
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- pip<=24.3
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- pip<=23.3.1
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- pip:
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- mlflow>=2.16.1
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- cloudpickle>=2.2.1
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- numpy>=1.26.4,<2.3.3
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- tensorflow==2.18.0
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- mlflow==2.11.1
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- cloudpickle==2.2.1
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- numpy==1.26.4
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- tensorflow==2.16.1
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name: mlflow-env

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