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gradientskyNivekNeyandre-marcos-perezmufaddal-rohawala
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JoseJuan98
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feature: AutoGluon 0.6.1 image_uris (aws#3544)
* fix: type hint of PySparkProcessor __init__ (aws#3297) * fix: fix PySparkProcessor __init__ params type (aws#3354) * fix: Revert "fix: type hint of PySparkProcessor __init__" (aws#3524) * fix: type hint of PySparkProcessor __init__ (aws#3297) * fix: fix PySparkProcessor __init__ params type (aws#3354) * fix: Revert "fix: type hint of PySparkProcessor __init__" (aws#3524) * feature: AutoGluon 0.6.1 image_uris * feature: AutoGluon 0.6.1 image_uris * Added processors for training images for consistency * Formatting * Formatting Co-authored-by: Kevin <[email protected]> Co-authored-by: André Perez <[email protected]> Co-authored-by: Mufaddal Rohawala <[email protected]>
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‎src/sagemaker/image_uri_config/autogluon.json‎

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"version_aliases": {
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"0.3": "0.3.2",
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"0.4": "0.4.3",
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"0.5": "0.5.2"
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"0.5": "0.5.2",
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"0.6": "0.6.1"
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},
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"versions": {
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"0.3.1": {
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"us-west-2": "763104351884"
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},
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"repository": "autogluon-training",
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"processors": ["cpu", "gpu"],
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"py_versions": ["py38"]
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},
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"0.4.2": {
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"us-west-2": "763104351884"
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},
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"repository": "autogluon-training",
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"processors": ["cpu", "gpu"],
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"py_versions": ["py38"]
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},
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"0.4.3": {
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"us-west-2": "763104351884"
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},
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"repository": "autogluon-training",
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"processors": ["cpu", "gpu"],
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"py_versions": ["py38"]
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},
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"0.5.2": {
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"us-west-2": "763104351884"
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},
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"repository": "autogluon-training",
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"processors": ["cpu", "gpu"],
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"py_versions": ["py38"]
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},
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"0.6.1": {
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"registries": {
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"af-south-1": "626614931356",
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"ap-east-1": "871362719292",
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"ap-northeast-1": "763104351884",
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"ap-northeast-2": "763104351884",
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"ap-northeast-3": "364406365360",
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"ap-south-1": "763104351884",
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"ap-southeast-1": "763104351884",
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"ap-southeast-2": "763104351884",
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"ap-southeast-3": "907027046896",
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"ca-central-1": "763104351884",
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"eu-central-1": "763104351884",
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"eu-north-1": "763104351884",
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"eu-west-1": "763104351884",
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"eu-west-2": "763104351884",
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"eu-west-3": "763104351884",
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"eu-south-1": "692866216735",
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"me-south-1": "217643126080",
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"sa-east-1": "763104351884",
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"us-east-1": "763104351884",
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"us-east-2": "763104351884",
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"us-gov-east-1": "446045086412",
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"us-gov-west-1": "442386744353",
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"us-iso-east-1": "886529160074",
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"us-west-1": "763104351884",
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"us-west-2": "763104351884"
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},
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"repository": "autogluon-training",
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"processors": ["cpu", "gpu"],
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"py_versions": ["py38"]
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}
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}
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"version_aliases": {
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"0.3": "0.3.2",
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"0.4": "0.4.3",
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"0.5": "0.5.2"
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"0.5": "0.5.2",
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"0.6": "0.6.1"
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},
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"versions": {
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"0.3.1": {
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"repository": "autogluon-inference",
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"processors": ["cpu", "gpu"],
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"py_versions": ["py38"]
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},
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"0.6.1": {
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"registries": {
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"af-south-1": "626614931356",
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"ap-east-1": "871362719292",
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"ap-northeast-1": "763104351884",
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"ap-northeast-2": "763104351884",
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"ap-northeast-3": "364406365360",
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"ap-south-1": "763104351884",
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"ap-southeast-1": "763104351884",
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"ap-southeast-2": "763104351884",
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"ap-southeast-3": "907027046896",
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"ca-central-1": "763104351884",
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"cn-north-1": "727897471807",
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"cn-northwest-1": "727897471807",
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"eu-central-1": "763104351884",
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"eu-north-1": "763104351884",
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"eu-west-1": "763104351884",
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"eu-west-2": "763104351884",
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"eu-west-3": "763104351884",
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"eu-south-1": "692866216735",
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"me-south-1": "217643126080",
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"sa-east-1": "763104351884",
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"us-east-1": "763104351884",
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"us-east-2": "763104351884",
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"us-gov-east-1": "446045086412",
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"us-gov-west-1": "442386744353",
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"us-iso-east-1": "886529160074",
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"us-west-1": "763104351884",
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"us-west-2": "763104351884"
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},
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"repository": "autogluon-inference",
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"processors": ["cpu", "gpu"],
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"py_versions": ["py38"]
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}
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}
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}

‎tests/unit/sagemaker/image_uris/test_autogluon.py‎

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"sa-east-1": "763104351884",
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"us-east-1": "763104351884",
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"us-east-2": "763104351884",
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"us-gov-east-1": "446045086412",
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"us-gov-west-1": "442386744353",
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"us-iso-east-1": "886529160074",
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"us-west-1": "763104351884",
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"us-west-2": "763104351884",
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}
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VERSIONS = ["0.3.1", "0.3.2", "0.4.0", "0.4.2", "0.4.3", "0.3", "0.4", "0.5.2", "0.5"]
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VERSIONS = [
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"0.3.1",
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"0.3.2",
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"0.4.0",
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"0.4.2",
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"0.4.3",
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"0.3",
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"0.4",
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"0.5.2",
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"0.5",
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"0.6.1",
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"0.6",
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]
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SCOPES = ["training", "inference"]
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PROCESSORS = ["cpu", "gpu"]
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