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Merge branch 'aws:master' into master
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‎CHANGELOG.md

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# Changelog
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## v2.45.0 (2021-06-07)
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### Features
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* Add support for Callback steps in model building pipelines
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## v2.44.0 (2021-06-01)
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### Features
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* support endpoint_name_prefix, seed and version for Clarify
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## v2.43.0 (2021-05-31)
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### Features
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* add xgboost framework version 1.3-1
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### Bug Fixes and Other Changes
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* remove duplicated tags in _append_project_tags
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## v2.42.1 (2021-05-27)
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### Bug Fixes and Other Changes
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* default value removed if zero for integer param
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## v2.42.0 (2021-05-24)
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### Features
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* support for custom pipeline execution name
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* Add data ingestion only data-wrangler flow recipe generation helper function
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### Bug Fixes and Other Changes
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* add kms key for processing job code upload
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* remove failing notebooks from notebook pr test
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* fix in and not in condition bug
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* Update overview.rst
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### Documentation Changes
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* Update "Ask a question" contact link
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* Update smdp docs with sparse_as_dense support
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## v2.41.0 (2021-05-17)
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### Features

‎VERSION

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2.41.1.dev0
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2.45.1.dev0

‎src/sagemaker/_studio.py

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return tags
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all_tags = tags or []
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additional_tags = [tag for tag in additional_tags if tag not in all_tags]
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all_tags.extend(additional_tags)
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return all_tags

‎src/sagemaker/clarify.py

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import json
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import os
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import tempfile
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import re
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from sagemaker.processing import ProcessingInput, ProcessingOutput, Processor
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from sagemaker import image_uris, s3, utils
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content_template=None,
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custom_attributes=None,
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accelerator_type=None,
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endpoint_name_prefix=None,
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):
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"""Initializes a configuration of a model and the endpoint to be created for it.
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r"""Initializes a configuration of a model and the endpoint to be created for it.
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Args:
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model_name (str): Model name (as created by 'CreateModel').
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accelerator_type (str): The Elastic Inference accelerator type to deploy to the model
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endpoint instance for making inferences to the model, see
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https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html.
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endpoint_name_prefix (str): The endpoint name prefix of a new endpoint. Must follow
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pattern "^[a-zA-Z0-9](-\*[a-zA-Z0-9]".
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"""
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self.predictor_config = {
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"model_name": model_name,
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"instance_type": instance_type,
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"initial_instance_count": instance_count,
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}
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if endpoint_name_prefix is not None:
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if re.search("^[a-zA-Z0-9](-*[a-zA-Z0-9])", endpoint_name_prefix) is None:
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raise ValueError(
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"Invalid endpoint_name_prefix."
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" Please follow pattern ^[a-zA-Z0-9](-*[a-zA-Z0-9])."
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)
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self.predictor_config["endpoint_name_prefix"] = endpoint_name_prefix
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if accept_type is not None:
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if accept_type not in ["text/csv", "application/jsonlines"]:
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raise ValueError(
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agg_method,
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use_logit=False,
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save_local_shap_values=True,
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seed=None,
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):
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"""Initializes config for SHAP.
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have log-odds units.
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save_local_shap_values (bool): Indicator of whether to save the local SHAP values
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in the output location. Default is True.
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seed (int): seed value to get deterministic SHAP values. Default is None.
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"""
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if agg_method not in ["mean_abs", "median", "mean_sq"]:
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raise ValueError(
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"use_logit": use_logit,
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"save_local_shap_values": save_local_shap_values,
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}
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if seed is not None:
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self.shap_config["seed"] = seed
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def get_explainability_config(self):
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"""Returns config."""
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env=None,
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tags=None,
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network_config=None,
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version=None,
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):
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"""Initializes a ``Processor`` instance, computing bias metrics and model explanations.
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A :class:`~sagemaker.network.NetworkConfig`
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object that configures network isolation, encryption of
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inter-container traffic, security group IDs, and subnets.
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version (str): Clarify version want to be used.
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"""
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container_uri = image_uris.retrieve("clarify", sagemaker_session.boto_region_name)
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container_uri = image_uris.retrieve("clarify", sagemaker_session.boto_region_name, version)
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super(SageMakerClarifyProcessor, self).__init__(
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role,
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container_uri,

‎src/sagemaker/image_uri_config/huggingface.json

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"processors": ["gpu"],
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"version_aliases": {
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"4.4": "4.4.2",
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"4.5": "4.5.0"
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"4.5": "4.5.0",
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"4.6": "4.6.1"
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},
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"versions": {
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"4.4.2": {
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},
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"repository": "huggingface-tensorflow-training"
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}
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},
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"4.6.1": {
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"version_aliases": {
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"pytorch1.6": "pytorch1.6.0",
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"pytorch1.7": "pytorch1.7.1",
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"tensorflow2.4": "tensorflow2.4.1"
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},
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"pytorch1.6.0": {
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"py_versions": ["py36"],
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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-south-1": "763104351884",
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"ap-southeast-1": "763104351884",
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"ap-southeast-2": "763104351884",
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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-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": "huggingface-pytorch-training"
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},
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"pytorch1.7.1": {
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"py_versions": ["py36"],
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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-south-1": "763104351884",
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"ap-southeast-1": "763104351884",
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"ap-southeast-2": "763104351884",
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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-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": "huggingface-pytorch-training"
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},
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"tensorflow2.4.1": {
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"py_versions": ["py37"],
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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-south-1": "763104351884",
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"ap-southeast-1": "763104351884",
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"ap-southeast-2": "763104351884",
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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-south-1": "692866216735",
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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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"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-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": "huggingface-tensorflow-training"
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}
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}
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}
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}

‎src/sagemaker/image_uri_config/xgboost.json

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"us-west-2": "246618743249"
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},
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"repository": "sagemaker-xgboost"
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},
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"1.3-1": {
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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-south-1": "720646828776",
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"ap-southeast-1": "121021644041",
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"ap-southeast-2": "783357654285",
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"ca-central-1": "341280168497",
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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-north-1": "662702820516",
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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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"eu-south-1": "978288397137",
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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-west-1": "414596584902",
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"us-iso-east-1": "833128469047",
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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-xgboost"
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}
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}
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}

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