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Merge branch 'master' into cv_s3_upload
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‎CHANGELOG.md

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# Changelog
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## v2.147.0 (2023-04-18)
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### Features
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* support different types of deletion mode
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## v2.146.1 (2023-04-17)
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### Bug Fixes and Other Changes

‎VERSION

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2.146.2.dev0
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2.147.1.dev0

‎src/sagemaker/fw_utils.py

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"1.12.0",
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"1.12.1",
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"1.13.1",
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"2.0.0",
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],
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}
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"1.12.0",
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"1.12.1",
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"1.13.1",
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"2.0.0",
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]
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TORCH_DISTRIBUTED_GPU_SUPPORTED_FRAMEWORK_VERSIONS = ["1.13.1"]
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TORCH_DISTRIBUTED_GPU_SUPPORTED_FRAMEWORK_VERSIONS = ["1.13.1", "2.0.0"]
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TRAINIUM_SUPPORTED_DISTRIBUTION_STRATEGIES = ["torch_distributed"]
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TRAINIUM_SUPPORTED_TORCH_DISTRIBUTED_FRAMEWORK_VERSIONS = [
@@ -161,6 +163,7 @@
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"1.12.0",
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"1.12.1",
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"1.13.1",
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"2.0.0",
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]
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SMDISTRIBUTED_SUPPORTED_STRATEGIES = ["dataparallel", "modelparallel"]

‎src/sagemaker/image_uri_config/pytorch.json

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"1.10": "1.10.2",
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"1.11": "1.11.0",
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"1.12": "1.12.1",
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"1.13": "1.13.1"
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"1.13": "1.13.1",
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"2.0": "2.0.0"
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},
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"versions": {
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"0.4.0": {
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"us-west-2": "763104351884"
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},
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"repository": "pytorch-inference"
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},
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"2.0.0": {
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"py_versions": [
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"py310"
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],
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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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"ap-southeast-4": "457447274322",
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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-isob-east-1": "094389454867",
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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": "pytorch-inference"
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}
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}
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},
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"cpu"
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],
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"version_aliases": {
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"1.12": "1.12.1"
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"1.12": "1.12.1",
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"2.0": "2.0.0"
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},
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"versions": {
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"1.12.1": {
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},
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"repository": "pytorch-inference-graviton",
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"container_version": {"cpu": "ubuntu20.04"}
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},
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"2.0.0": {
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"py_versions": [
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"py310"
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],
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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-south-2": "772153158452",
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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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"ap-southeast-4": "457447274322",
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"ca-central-1": "763104351884",
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"eu-central-1": "763104351884",
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"eu-central-2": "380420809688",
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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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"eu-south-2": "503227376785",
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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-west-1": "763104351884",
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"us-west-2": "763104351884"
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},
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"repository": "pytorch-inference-graviton",
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"container_version": {"cpu": "ubuntu20.04"}
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}
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}
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},
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"1.10": "1.10.2",
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"1.11": "1.11.0",
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"1.12": "1.12.1",
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"1.13": "1.13.1"
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"1.13": "1.13.1",
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"2.0": "2.0.0"
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},
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"versions": {
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"0.4.0": {
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"us-west-2": "763104351884"
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},
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"repository": "pytorch-training"
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},
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"2.0.0": {
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"py_versions": [
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"py310"
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],
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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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"ap-southeast-4": "457447274322",
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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-isob-east-1": "094389454867",
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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": "pytorch-training"
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}
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}
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}

‎src/sagemaker/model_monitor/model_monitoring.py

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network_config=None,
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role=None,
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image_uri=None,
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batch_transform_input=None,
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):
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"""Updates the existing monitoring schedule.
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role (str): An AWS IAM role name or ARN. The Amazon SageMaker jobs use this role.
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image_uri (str): The uri of the image to use for the jobs started by
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the Monitor.
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batch_transform_input (sagemaker.model_monitor.BatchTransformInput): Inputs to
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run the monitoring schedule on the batch transform (default: None)
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479482
"""
480483
monitoring_inputs = None
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if (batch_transform_input is not None) and (endpoint_input is not None):
486+
message = (
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"Cannot update both batch_transform_input and endpoint_input to update an "
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"Amazon Model Monitoring Schedule. "
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"Please provide atmost one of the above required inputs"
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)
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_LOGGER.error(message)
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raise ValueError(message)
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if endpoint_input is not None:
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monitoring_inputs = [
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self._normalize_endpoint_input(endpoint_input=endpoint_input)._to_request_dict()
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]
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elif batch_transform_input is not None:
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monitoring_inputs = [batch_transform_input._to_request_dict()]
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486502
monitoring_output_config = None
487503
if output is not None:
488504
normalized_monitoring_output = self._normalize_monitoring_output_fields(output=output)
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network_config=None,
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enable_cloudwatch_metrics=None,
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role=None,
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batch_transform_input=None,
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):
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"""Updates the existing monitoring schedule.
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enable_cloudwatch_metrics (bool): Whether to publish cloudwatch metrics as part of
19371954
the baselining or monitoring jobs.
19381955
role (str): An AWS IAM role name or ARN. The Amazon SageMaker jobs use this role.
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batch_transform_input (sagemaker.model_monitor.BatchTransformInput): Inputs to
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run the monitoring schedule on the batch transform (default: None)
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"""
1960+
1961+
if (batch_transform_input is not None) and (endpoint_input is not None):
1962+
message = (
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"Cannot update both batch_transform_input and endpoint_input to update an "
1964+
"Amazon Model Monitoring Schedule. "
1965+
"Please provide atmost one of the above required inputs"
1966+
)
1967+
_LOGGER.error(message)
1968+
raise ValueError(message)
1969+
19411970
# check if this schedule is in v2 format and update as per v2 format if it is
19421971
if self.job_definition_name is not None:
19431972
self._update_data_quality_monitoring_schedule(
@@ -1958,13 +1987,17 @@ def update_monitoring_schedule(
19581987
network_config=network_config,
19591988
enable_cloudwatch_metrics=enable_cloudwatch_metrics,
19601989
role=role,
1990+
batch_transform_input=batch_transform_input,
19611991
)
19621992
return
19631993

19641994
monitoring_inputs = None
19651995
if endpoint_input is not None:
19661996
monitoring_inputs = [self._normalize_endpoint_input(endpoint_input)._to_request_dict()]
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elif batch_transform_input is not None:
1999+
monitoring_inputs = [batch_transform_input._to_request_dict()]
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19682001
record_preprocessor_script_s3_uri = None
19692002
if record_preprocessor_script is not None:
19702003
record_preprocessor_script_s3_uri = self._s3_uri_from_local_path(
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30223055
self._update_monitoring_schedule(self.job_definition_name, schedule_cron_expression)
30233056
return
30243057

3058+
if (batch_transform_input is not None) and (endpoint_input is not None):
3059+
message = (
3060+
"Cannot update both batch_transform_input and endpoint_input to update an "
3061+
"Amazon Model Monitoring Schedule. "
3062+
"Please provide atmost one of the above required inputs"
3063+
)
3064+
_LOGGER.error(message)
3065+
raise ValueError(message)
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30253067
# Need to update schedule with a new job definition
30263068
job_desc = self.sagemaker_session.sagemaker_client.describe_model_quality_job_definition(
30273069
JobDefinitionName=self.job_definition_name

‎tests/conftest.py

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@pytest.fixture(scope="module", params=["py2", "py3"])
245245
def pytorch_training_py_version(pytorch_training_version, request):
246-
if Version(pytorch_training_version) >= Version("1.13"):
246+
if Version(pytorch_training_version) >= Version("2.0"):
247+
return "py310"
248+
elif Version(pytorch_training_version) >= Version("1.13"):
247249
return "py39"
248250
elif Version(pytorch_training_version) >= Version("1.9"):
249251
return "py38"
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256258
@pytest.fixture(scope="module", params=["py2", "py3"])
257259
def pytorch_inference_py_version(pytorch_inference_version, request):
258-
if Version(pytorch_inference_version) >= Version("1.13"):
260+
if Version(pytorch_inference_version) >= Version("2.0"):
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return "py310"
262+
elif Version(pytorch_inference_version) >= Version("1.13"):
259263
return "py39"
260264
elif Version(pytorch_inference_version) >= Version("1.9"):
261265
return "py38"

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