SageMaker Core v2

CONTRIBUTING.md

@@ -33,7 +33,7 @@ source .env
 ## Run CodeGen
 * To generate all CodeGen code run the below
 ```
-python src/sagemaker_core/tools/codegen.py
+python src/sagemaker/core/tools/codegen.py
 ```
 
 ## Testing

docs/index.rst

@@ -4,7 +4,7 @@
 SageMaker Core Resources
 ########################
 
-.. automodule:: sagemaker_core.main.resources
+.. automodule:: sagemaker.core.resources
     :members:
     :noindex:
 
@@ -13,6 +13,6 @@ SageMaker Core Resources
 SageMaker Core Shapes
 ########################
 
-.. automodule:: sagemaker_core.main.shapes
+.. automodule:: sagemaker.core.shapes
     :members:
     :noindex:

example_notebooks/get_started.ipynb

@@ -36,7 +36,7 @@
    "outputs": [],
    "source": [
     "import time\n",
-    "from sagemaker_core.helper.session_helper import Session, get_execution_role\n",
+    "from sagemaker.core.helper.session_helper import Session, get_execution_role\n",
     "\n",
     "# Set up region, role and bucket parameters used throughout the notebook.\n",
     "sagemaker_session = Session()\n",
@@ -197,8 +197,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from sagemaker_core.resources import TrainingJob\n",
-    "from sagemaker_core.shapes import AlgorithmSpecification, Channel, DataSource, S3DataSource, ResourceConfig, StoppingCondition, OutputDataConfig\n",
+    "from sagemaker.core.resources import TrainingJob\n",
+    "from sagemaker.core.shapes import AlgorithmSpecification, Channel, DataSource, S3DataSource, ResourceConfig, StoppingCondition, OutputDataConfig\n",
     "\n",
     "job_name = 'xgboost-churn-' + time.strftime(\"%Y-%m-%d-%H-%M-%S\", time.gmtime())  # Name of training job\n",
     "instance_type = 'ml.m4.xlarge'  # SageMaker instance type to use for training\n",
@@ -291,8 +291,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from sagemaker_core.resources import HyperParameterTuningJob\n",
-    "from sagemaker_core.shapes import HyperParameterTuningJobConfig, \\\n",
+    "from sagemaker.core.resources import HyperParameterTuningJob\n",
+    "from sagemaker.core.shapes import HyperParameterTuningJobConfig, \\\n",
     "     ResourceLimits, HyperParameterTuningJobWarmStartConfig, ParameterRanges, AutoParameter, \\\n",
     "     Autotune, HyperParameterTrainingJobDefinition, HyperParameterTuningJobObjective, HyperParameterAlgorithmSpecification, \\\n",
     "     OutputDataConfig, StoppingCondition, ResourceConfig\n",
@@ -436,8 +436,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from sagemaker_core.resources import Model\n",
-    "from sagemaker_core.shapes import ContainerDefinition\n",
+    "from sagemaker.core.resources import Model\n",
+    "from sagemaker.core.shapes import ContainerDefinition\n",
     "\n",
     "#model_s3_uri = training_job.model_artifacts.s3_model_artifacts  # Get URI of model artifacts from the training job.\n",
     "model_s3_uri = TrainingJob.get(tuning_job.best_training_job.training_job_name).model_artifacts.s3_model_artifacts # Get URI of model artifacts of the best model from the tuning job.\n",
@@ -469,8 +469,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from sagemaker_core.resources import TransformJob\n",
-    "from sagemaker_core.shapes import TransformInput, TransformDataSource, TransformS3DataSource, TransformOutput, TransformResources\n",
+    "from sagemaker.core.resources import TransformJob\n",
+    "from sagemaker.core.shapes import TransformInput, TransformDataSource, TransformS3DataSource, TransformOutput, TransformResources\n",
     "\n",
     "model_name = customer_churn_model.get_name()\n",
     "transform_job_name = 'churn-prediction' + time.strftime(\"%Y-%m-%d-%H-%M-%S\", time.gmtime())  # Name of TranformJob\n",
@@ -576,8 +576,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from sagemaker_core.resources import Endpoint, EndpointConfig\n",
-    "from sagemaker_core.shapes import ProductionVariant\n",
+    "from sagemaker.core.resources import Endpoint, EndpointConfig\n",
+    "from sagemaker.core.shapes import ProductionVariant\n",
     "\n",
     "endpoint_config_name = 'churn-prediction-endpoint-config'  # Name of endpoint configuration\n",
     "model_name = customer_churn_model.get_name()  # Get name of SageMaker model created in previous step\n",

example_notebooks/inference_and_resource_chaining.ipynb

@@ -135,7 +135,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from sagemaker_core.helper.session_helper import get_execution_role, Session\n",
+    "from sagemaker.core.helper.session_helper import get_execution_role, Session\n",
     "from rich import print\n",
     "\n",
     "# Get region, role, bucket\n",
@@ -266,7 +266,7 @@
     "# Create TrainingJob with SageMakerCore\n",
     "\n",
     "import time\n",
-    "from sagemaker_core.resources import TrainingJob, AlgorithmSpecification, Channel, DataSource, S3DataSource, \\\n",
+    "from sagemaker.core.resources import TrainingJob, AlgorithmSpecification, Channel, DataSource, S3DataSource, \\\n",
     "    OutputDataConfig, ResourceConfig, StoppingCondition\n",
     "\n",
     "job_name_v3 = 'xgboost-iris-' + time.strftime(\"%Y-%m-%d-%H-%M-%S\", time.gmtime())\n",
@@ -377,8 +377,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from sagemaker_core.shapes import ContainerDefinition, ProductionVariant\n",
-    "from sagemaker_core.resources import Model, EndpointConfig, Endpoint\n",
+    "from sagemaker.core.shapes import ContainerDefinition, ProductionVariant\n",
+    "from sagemaker.core.resources import Model, EndpointConfig, Endpoint\n",
     "from time import gmtime, strftime\n",
     "\n",
     "# Get model_data_url from training_job object\n",
@@ -611,7 +611,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from sagemaker_core.shapes import ProductionVariant, AsyncInferenceConfig, AsyncInferenceOutputConfig, AsyncInferenceClientConfig\n",
+    "from sagemaker.core.shapes import ProductionVariant, AsyncInferenceConfig, AsyncInferenceOutputConfig, AsyncInferenceClientConfig\n",
     "\n",
     "async_endpoint_config = EndpointConfig.create(\n",
     "    endpoint_config_name=key,\n",
@@ -755,7 +755,7 @@
     "# Delete any sagemaker core resource objects created in this notebook\n",
     "def delete_all_sagemaker_resources():\n",
     "    all_objects = list(locals().values()) + list(globals().values())\n",
-    "    deletable_objects = [obj for obj in all_objects if hasattr(obj, 'delete') and obj.__class__.__module__ == 'sagemaker_core.main.resources']\n",
+    "    deletable_objects = [obj for obj in all_objects if hasattr(obj, 'delete') and obj.__class__.__module__ == 'sagemaker.core.resources']\n",
     "    \n",
     "    for obj in deletable_objects:\n",
     "        obj.delete()\n",
@@ -766,7 +766,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "py3.10",
    "language": "python",
    "name": "python3"
   },

example_notebooks/intelligent_defaults_and_logging.ipynb

@@ -106,7 +106,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Uninstall previous version of sagemaker_core and restart kernel\n",
+    "# Uninstall previous version of sagemaker-core and restart kernel\n",
     "!pip uninstall sagemaker-core -y"
    ]
   },
@@ -116,7 +116,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Install the latest version of sagemaker_core\n",
+    "# Install the latest version of sagemaker-core\n",
     "\n",
     "!pip install sagemaker-core --upgrade"
    ]
@@ -127,7 +127,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Check the version of sagemaker_core\n",
+    "# Check the version of sagemaker-core\n",
     "!pip show -v sagemaker-core"
    ]
   },
@@ -167,7 +167,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from sagemaker_core.helper.session_helper import Session, get_execution_role\n",
+    "from sagemaker.core.helper.session_helper import Session, get_execution_role\n",
     "from rich import print\n",
     "\n",
     "# Get region, role, bucket\n",
@@ -362,8 +362,8 @@
    "outputs": [],
    "source": [
     "import time\n",
-    "from sagemaker_core.resources import Cluster\n",
-    "from sagemaker_core.shapes import ClusterInstanceGroupSpecification, ClusterLifeCycleConfig\n",
+    "from sagemaker.core.resources import Cluster\n",
+    "from sagemaker.core.shapes import ClusterInstanceGroupSpecification, ClusterLifeCycleConfig\n",
     "    \n",
     "cluster_name_v3 = 'xgboost-cluster-' + time.strftime(\"%Y-%m-%d-%H-%M-%S\", time.gmtime())\n",
     "\n",
@@ -408,8 +408,8 @@
    "outputs": [],
    "source": [
     "import time\n",
-    "from sagemaker_core.resources import TrainingJob\n",
-    "from sagemaker_core.shapes import  AlgorithmSpecification, Channel, DataSource, S3DataSource, ResourceConfig, StoppingCondition\n",
+    "from sagemaker.core.resources import TrainingJob\n",
+    "from sagemaker.core.shapes import  AlgorithmSpecification, Channel, DataSource, S3DataSource, ResourceConfig, StoppingCondition\n",
     "\n",
     "job_name_v3 = 'xgboost-iris-' + time.strftime(\"%Y-%m-%d-%H-%M-%S\", time.gmtime())\n",
     "\n",
@@ -481,7 +481,7 @@
    "outputs": [],
    "source": [
     "# Setting log_level to DEBUG using configure_logging with string parameter \n",
-    "from sagemaker_core.main.utils import configure_logging\n",
+    "from sagemaker.core.utils import configure_logging\n",
     "\n",
     "configure_logging('DEBUG')"
    ]
@@ -493,7 +493,7 @@
    "outputs": [],
    "source": [
     "# Get TrainingJob with DEBUG log_level\n",
-    "from sagemaker_core.resources import TrainingJob\n",
+    "from sagemaker.core.resources import TrainingJob\n",
     "\n",
     "training_job = TrainingJob.get(job_name_v3)"
    ]
@@ -549,7 +549,7 @@
     "# Delete any sagemaker core resource objects created in this notebook\n",
     "def delete_all_sagemaker_resources():\n",
     "    all_objects = list(locals().values()) + list(globals().values())\n",
-    "    deletable_objects = [obj for obj in all_objects if hasattr(obj, 'delete') and obj.__class__.__module__ == 'sagemaker_core.main.resources']\n",
+    "    deletable_objects = [obj for obj in all_objects if hasattr(obj, 'delete') and obj.__class__.__module__ == 'sagemaker.core.resources']\n",
     "    \n",
     "    for obj in deletable_objects:\n",
     "        obj.delete()\n",

example_notebooks/sagemaker-core-llama-3-8B-speculative-decoding.ipynb

@@ -18,7 +18,7 @@
     "## 1. Dependency Installation\n",
     "### 1.1. Python Dependencies & Imports\n",
     "This notebook requires the following Python dependencies:\n",
-    "* AWS [`sagemaker_core`]()\n",
+    "* AWS [`sagemaker-core`]()\n",
     "\n",
     "Let's install or upgrade these dependencies using the following command:"
    ]
@@ -46,7 +46,7 @@
     "import json\n",
     "import os\n",
     "\n",
-    "from sagemaker_core.helper.session_helper import get_execution_role, Session\n",
+    "from sagemaker.core.helper.session_helper import get_execution_role, Session\n",
     "import pathlib \n",
     "import huggingface_hub"
    ]
@@ -135,8 +135,8 @@
    },
    "outputs": [],
    "source": [
-    "from sagemaker_core.shapes import ContainerDefinition, ProductionVariant\n",
-    "from sagemaker_core.resources import Model, EndpointConfig, Endpoint\n",
+    "from sagemaker.core.shapes import ContainerDefinition, ProductionVariant\n",
+    "from sagemaker.core.resources import Model, EndpointConfig, Endpoint\n",
     "from time import gmtime, strftime"
    ]
   },
@@ -194,7 +194,7 @@
    },
    "outputs": [],
    "source": [
-    "from sagemaker_core.shapes import ProductionVariantRoutingConfig\n",
+    "from sagemaker.core.shapes import ProductionVariantRoutingConfig\n",
     "\n",
     "routing_config = ProductionVariantRoutingConfig(\n",
     "    routing_strategy=\"LEAST_OUTSTANDING_REQUESTS\"\n",
@@ -314,7 +314,7 @@
     "# Delete any sagemaker core resource objects created in this notebook\n",
     "def delete_all_sagemaker_resources():\n",
     "    all_objects = list(locals().values()) + list(globals().values())\n",
-    "    deletable_objects = [obj for obj in all_objects if hasattr(obj, 'delete') and obj.__class__.__module__ == 'sagemaker_core.main.resources']\n",
+    "    deletable_objects = [obj for obj in all_objects if hasattr(obj, 'delete') and obj.__class__.__module__ == 'sagemaker.core.resources']\n",
     "    \n",
     "    for obj in deletable_objects:\n",
     "        obj.delete()\n",

example_notebooks/sagemaker-core-llama-3-8B.ipynb

@@ -15,7 +15,7 @@
     "## 1. Dependency Installation\n",
     "### 1.1. Python Dependencies & Imports\n",
     "This notebook requires the following Python dependencies:\n",
-    "* AWS [`sagemaker_core`]()\n",
+    "* AWS [`sagemaker-core`]()\n",
     "\n",
     "Let's install or upgrade these dependencies using the following command:"
    ]
@@ -43,7 +43,7 @@
     "import json\n",
     "import os\n",
     "\n",
-    "from sagemaker_core.helper.session_helper import get_execution_role, Session\n",
+    "from sagemaker.core.helper.session_helper import get_execution_role, Session\n",
     "import pathlib \n",
     "import huggingface_hub"
    ]
@@ -124,8 +124,8 @@
    },
    "outputs": [],
    "source": [
-    "from sagemaker_core.shapes import ContainerDefinition, ProductionVariant\n",
-    "from sagemaker_core.resources import Model, EndpointConfig, Endpoint\n",
+    "from sagemaker.core.shapes import ContainerDefinition, ProductionVariant\n",
+    "from sagemaker.core.resources import Model, EndpointConfig, Endpoint\n",
     "from time import gmtime, strftime"
    ]
   },
@@ -182,7 +182,7 @@
    },
    "outputs": [],
    "source": [
-    "from sagemaker_core.shapes import ProductionVariantRoutingConfig\n",
+    "from sagemaker.core.shapes import ProductionVariantRoutingConfig\n",
     "\n",
     "routing_config = ProductionVariantRoutingConfig(\n",
     "    routing_strategy=\"LEAST_OUTSTANDING_REQUESTS\"\n",
@@ -302,7 +302,7 @@
     "# Delete any sagemaker core resource objects created in this notebook\n",
     "def delete_all_sagemaker_resources():\n",
     "    all_objects = list(locals().values()) + list(globals().values())\n",
-    "    deletable_objects = [obj for obj in all_objects if hasattr(obj, 'delete') and obj.__class__.__module__ == 'sagemaker_core.main.resources']\n",
+    "    deletable_objects = [obj for obj in all_objects if hasattr(obj, 'delete') and obj.__class__.__module__ == 'sagemaker.core.resources']\n",
     "    \n",
     "    for obj in deletable_objects:\n",
     "        obj.delete()\n",

example_notebooks/sagemaker_core_overview.ipynb

@@ -92,7 +92,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Uninstall previous version of sagemaker_core and restart kernel\n",
+    "# Uninstall previous version of sagemaker-core and restart kernel\n",
     "!pip uninstall sagemaker-core -y"
    ]
   },
@@ -102,7 +102,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Install the latest version of sagemaker_core\n",
+    "# Install the latest version of sagemaker-core\n",
     "\n",
     "!pip install sagemaker-core --upgrade"
    ]
@@ -113,7 +113,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Check the version of sagemaker_core\n",
+    "# Check the version of sagemaker-core\n",
     "!pip show -v sagemaker-core"
    ]
   },
@@ -153,7 +153,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from sagemaker_core.helper.session_helper import Session, get_execution_role\n",
+    "from sagemaker.core.helper.session_helper import Session, get_execution_role\n",
     "from rich import print\n",
     "\n",
     "# Get region, role, bucket\n",
@@ -382,7 +382,7 @@
     "# Create TrainingJob with SageMakerCore\n",
     "\n",
     "import time\n",
-    "from sagemaker_core.resources import TrainingJob, AlgorithmSpecification, Channel, DataSource, S3DataSource, \\\n",
+    "from sagemaker.core.resources import TrainingJob, AlgorithmSpecification, Channel, DataSource, S3DataSource, \\\n",
     "    OutputDataConfig, ResourceConfig, StoppingCondition\n",
     "\n",
     "job_name_v3 = 'xgboost-iris-' + time.strftime(\"%Y-%m-%d-%H-%M-%S\", time.gmtime())\n",
@@ -531,7 +531,7 @@
    "source": [
     "# List TrainingJobs with SageMakerCore\n",
     "import datetime\n",
-    "from sagemaker_core.resources import TrainingJob\n",
+    "from sagemaker.core.resources import TrainingJob\n",
     "\n",
     "creation_time_after = datetime.datetime.now() - datetime.timedelta(days=1)\n",
     "\n",
@@ -562,7 +562,7 @@
     "# Delete any sagemaker core resource objects created in this notebook\n",
     "def delete_all_sagemaker_resources():\n",
     "    all_objects = list(locals().values()) + list(globals().values())\n",
-    "    deletable_objects = [obj for obj in all_objects if hasattr(obj, 'delete') and obj.__class__.__module__ == 'sagemaker_core.main.resources']\n",
+    "    deletable_objects = [obj for obj in all_objects if hasattr(obj, 'delete') and obj.__class__.__module__ == 'sagemaker.core.resources']\n",
     "    \n",
     "    for obj in deletable_objects:\n",
     "        obj.delete()\n",