Merge branch 'master' into user-short-lived-credentials-override

Author: wcarpenter1-godaddy

doc/api/governance/model_card.rst

@@ -41,3 +41,9 @@ see `Amazon SageMaker Model Cards <https://docs.aws.amazon.com/sagemaker/latest/
 
 .. autoclass:: TrainingJobDetails
     :show-inheritance:
+
+.. autoclass:: BusinessDetails
+    :show-inheritance:
+
+.. autoclass:: HyperParameter
+    :show-inheritance:

src/sagemaker/clarify.py

@@ -1423,8 +1423,8 @@ def run_post_training_bias(
         self,
         data_config: DataConfig,
         data_bias_config: BiasConfig,
-        model_config: ModelConfig,
-        model_predicted_label_config: ModelPredictedLabelConfig,
+        model_config: Optional[ModelConfig] = None,
+        model_predicted_label_config: Optional[ModelPredictedLabelConfig] = None,
         methods: Union[str, List[str]] = "all",
         wait: bool = True,
         logs: bool = True,
@@ -1444,7 +1444,8 @@ def run_post_training_bias(
             data_config (:class:`~sagemaker.clarify.DataConfig`): Config of the input/output data.
             data_bias_config (:class:`~sagemaker.clarify.BiasConfig`): Config of sensitive groups.
             model_config (:class:`~sagemaker.clarify.ModelConfig`): Config of the model and its
-                endpoint to be created.
+                endpoint to be created. This is required unless``predicted_label_dataset_uri`` or
+                ``predicted_label`` is provided in ``data_config``.
             model_predicted_label_config (:class:`~sagemaker.clarify.ModelPredictedLabelConfig`):
                 Config of how to extract the predicted label from the model output.
             methods (str or list[str]): Selector of a subset of potential metrics:
@@ -1508,7 +1509,7 @@ def run_bias(
         self,
         data_config: DataConfig,
         bias_config: BiasConfig,
-        model_config: ModelConfig,
+        model_config: Optional[ModelConfig] = None,
         model_predicted_label_config: Optional[ModelPredictedLabelConfig] = None,
         pre_training_methods: Union[str, List[str]] = "all",
         post_training_methods: Union[str, List[str]] = "all",
@@ -1529,7 +1530,8 @@ def run_bias(
             data_config (:class:`~sagemaker.clarify.DataConfig`): Config of the input/output data.
             bias_config (:class:`~sagemaker.clarify.BiasConfig`): Config of sensitive groups.
             model_config (:class:`~sagemaker.clarify.ModelConfig`): Config of the model and its
-                endpoint to be created.
+                endpoint to be created. This is required unless``predicted_label_dataset_uri`` or
+                ``predicted_label`` is provided in ``data_config``.
             model_predicted_label_config (:class:`~sagemaker.clarify.ModelPredictedLabelConfig`):
                 Config of how to extract the predicted label from the model output.
             pre_training_methods (str or list[str]): Selector of a subset of potential metrics:
@@ -1930,16 +1932,30 @@ def _add_predictor(
     ):
         """Extends analysis config with predictor."""
         analysis_config = {**analysis_config}
-        analysis_config["predictor"] = model_config.get_predictor_config()
+        if isinstance(model_config, ModelConfig):
+            analysis_config["predictor"] = model_config.get_predictor_config()
+        else:
+            if "shap" in analysis_config["methods"] or "pdp" in analysis_config["methods"]:
+                raise ValueError(
+                    "model_config must be provided when explainability methods are selected."
+                )
+            if (
+                "predicted_label_dataset_uri" not in analysis_config
+                and "predicted_label" not in analysis_config
+            ):
+                raise ValueError(
+                    "model_config must be provided when `predicted_label_dataset_uri` or "
+                    "`predicted_label` are not provided in data_config."
+                )
         if isinstance(model_predicted_label_config, ModelPredictedLabelConfig):
             (
                 probability_threshold,
                 predictor_config,
             ) = model_predicted_label_config.get_predictor_config()
-            if predictor_config:
+            if predictor_config and "predictor" in analysis_config:
                 analysis_config["predictor"].update(predictor_config)
             _set(probability_threshold, "probability_threshold", analysis_config)
-        else:
+        elif "predictor" in analysis_config:
             _set(model_predicted_label_config, "label", analysis_config["predictor"])
         return analysis_config
 

src/sagemaker/image_uri_config/autogluon.json

@@ -5,7 +5,7 @@
             "0.3": "0.3.2",
             "0.4": "0.4.3",
             "0.5": "0.5.2",
-            "0.6": "0.6.1"
+            "0.6": "0.6.2"
         },
         "versions": {
             "0.3.1": {
@@ -242,6 +242,39 @@
                 "repository": "autogluon-training",
                 "processors": ["cpu", "gpu"],
                 "py_versions": ["py38"]
+            },
+            "0.6.2": {
+                "registries": {
+                    "af-south-1": "626614931356",
+                    "ap-east-1": "871362719292",
+                    "ap-northeast-1": "763104351884",
+                    "ap-northeast-2": "763104351884",
+                    "ap-northeast-3": "364406365360",
+                    "ap-south-1": "763104351884",
+                    "ap-southeast-1": "763104351884",
+                    "ap-southeast-2": "763104351884",
+                    "ap-southeast-3": "907027046896",
+                    "ca-central-1": "763104351884",
+                    "eu-central-1": "763104351884",
+                    "eu-north-1": "763104351884",
+                    "eu-west-1": "763104351884",
+                    "eu-west-2": "763104351884",
+                    "eu-west-3": "763104351884",
+                    "eu-south-1": "692866216735",
+                    "me-south-1": "217643126080",
+                    "sa-east-1": "763104351884",
+                    "us-east-1": "763104351884",
+                    "us-east-2": "763104351884",
+                    "us-gov-east-1": "446045086412",
+                    "us-gov-west-1": "442386744353",
+                    "us-iso-east-1": "886529160074",
+                    "us-isob-east-1": "094389454867",
+                    "us-west-1": "763104351884",
+                    "us-west-2": "763104351884"
+                },
+                "repository": "autogluon-training",
+                "processors": ["cpu", "gpu"],
+                "py_versions": ["py38"]
             }
         }
     },
@@ -250,7 +283,7 @@
             "0.3": "0.3.2",
             "0.4": "0.4.3",
             "0.5": "0.5.2",
-            "0.6": "0.6.1"
+            "0.6": "0.6.2"
         },
         "versions": {
             "0.3.1": {
@@ -521,6 +554,41 @@
                 "repository": "autogluon-inference",
                 "processors": ["cpu", "gpu"],
                 "py_versions": ["py38"]
+            },
+            "0.6.2": {
+                "registries": {
+                    "af-south-1": "626614931356",
+                    "ap-east-1": "871362719292",
+                    "ap-northeast-1": "763104351884",
+                    "ap-northeast-2": "763104351884",
+                    "ap-northeast-3": "364406365360",
+                    "ap-south-1": "763104351884",
+                    "ap-southeast-1": "763104351884",
+                    "ap-southeast-2": "763104351884",
+                    "ap-southeast-3": "907027046896",
+                    "ca-central-1": "763104351884",
+                    "cn-north-1": "727897471807",
+                    "cn-northwest-1": "727897471807",
+                    "eu-central-1": "763104351884",
+                    "eu-north-1": "763104351884",
+                    "eu-west-1": "763104351884",
+                    "eu-west-2": "763104351884",
+                    "eu-west-3": "763104351884",
+                    "eu-south-1": "692866216735",
+                    "me-south-1": "217643126080",
+                    "sa-east-1": "763104351884",
+                    "us-east-1": "763104351884",
+                    "us-east-2": "763104351884",
+                    "us-gov-east-1": "446045086412",
+                    "us-gov-west-1": "442386744353",
+                    "us-iso-east-1": "886529160074",
+                    "us-isob-east-1": "094389454867",
+                    "us-west-1": "763104351884",
+                    "us-west-2": "763104351884"
+                },
+                "repository": "autogluon-inference",
+                "processors": ["cpu", "gpu"],
+                "py_versions": ["py38"]
             }
         }
     }

src/sagemaker/image_uri_config/pytorch-training-compiler.json

@@ -4,7 +4,8 @@
             "gpu"
         ],
         "version_aliases": {
-            "1.12": "1.12.0"
+            "1.12": "1.12.0",
+            "1.13": "1.13.1"
         },
         "versions": {
             "1.12.0": {
@@ -35,6 +36,35 @@
                     "us-west-2": "763104351884"
                 },
                 "repository": "pytorch-trcomp-training"
+            },
+            "1.13.1": {
+                "py_versions": [
+                    "py39"
+                ],
+                "registries": {
+                    "af-south-1": "626614931356",
+                    "ap-east-1": "871362719292",
+                    "ap-northeast-1": "763104351884",
+                    "ap-northeast-2": "763104351884",
+                    "ap-northeast-3": "364406365360",
+                    "ap-south-1": "763104351884",
+                    "ap-southeast-1": "763104351884",
+                    "ap-southeast-2": "763104351884",
+                    "ca-central-1": "763104351884",
+                    "eu-central-1": "763104351884",
+                    "eu-north-1": "763104351884",
+                    "eu-west-1": "763104351884",
+                    "eu-west-2": "763104351884",
+                    "eu-west-3": "763104351884",
+                    "eu-south-1": "692866216735",
+                    "me-south-1": "217643126080",
+                    "sa-east-1": "763104351884",
+                    "us-east-1": "763104351884",
+                    "us-east-2": "763104351884",
+                    "us-west-1": "763104351884",
+                    "us-west-2": "763104351884"
+                },
+                "repository": "pytorch-trcomp-training"
             }
         }
     }

src/sagemaker/inference_recommender/__init__.py

@@ -12,3 +12,7 @@
 # language governing permissions and limitations under the License.
 """Classes for using Inference Recommender with Amazon SageMaker."""
 from __future__ import absolute_import
+from sagemaker.inference_recommender.inference_recommender_mixin import (  # noqa: F401
+    Phase,
+    ModelLatencyThreshold,
+)

src/sagemaker/inference_recommender/inference_recommender_mixin.py

@@ -464,18 +464,24 @@ def _convert_to_resource_limit_json(self, max_tests: int, max_parallel_tests: in
         """Bundle right_size() parameters into a resource limit for Advanced job"""
         if not max_tests and not max_parallel_tests:
             return None
-        return {
-            "MaxNumberOfTests": max_tests,
-            "MaxParallelOfTests": max_parallel_tests,
-        }
+        resource_limit = {}
+        if max_tests:
+            resource_limit["MaxNumberOfTests"] = max_tests
+        if max_parallel_tests:
+            resource_limit["MaxParallelOfTests"] = max_parallel_tests
+        return resource_limit
 
     def _convert_to_stopping_conditions_json(
         self, max_invocations: int, model_latency_thresholds: List[ModelLatencyThreshold]
     ):
         """Bundle right_size() parameters into stopping conditions for Advanced job"""
         if not max_invocations and not model_latency_thresholds:
             return None
-        return {
-            "MaxInvocations": max_invocations,
-            "ModelLatencyThresholds": [threshold.to_json for threshold in model_latency_thresholds],
-        }
+        stopping_conditions = {}
+        if max_invocations:
+            stopping_conditions["MaxInvocations"] = max_invocations
+        if model_latency_thresholds:
+            stopping_conditions["ModelLatencyThresholds"] = [
+                threshold.to_json for threshold in model_latency_thresholds
+            ]
+        return stopping_conditions

src/sagemaker/model_card/__init__.py

@@ -16,8 +16,10 @@
     Environment,
     ModelOverview,
     IntendedUses,
+    BusinessDetails,
     ObjectiveFunction,
     TrainingMetric,
+    HyperParameter,
     Metric,
     Function,
     TrainingJobDetails,