Merge Master ci py312 for PR test

.github/workflows/codebuild-ci-health.yml

@@ -26,7 +26,7 @@ jobs:
     strategy:
         fail-fast: false
         matrix:
-          python-version: ["py38", "py39", "py310", "py311"]
+          python-version: ["py38", "py39", "py310", "py311","py312"]
     steps:
       - name: Configure AWS Credentials
         uses: aws-actions/configure-aws-credentials@v4

.github/workflows/codebuild-ci.yml

@@ -63,7 +63,7 @@ jobs:
     strategy:
         fail-fast: false
         matrix:
-          python-version: ["py38","py39","py310","py311"]
+          python-version: ["py38","py39","py310","py311","py312"]
     steps:
       - name: Configure AWS Credentials
         uses: aws-actions/configure-aws-credentials@v4

pyproject.toml

@@ -29,6 +29,7 @@ classifiers = [
   "Programming Language :: Python :: 3.9",
   "Programming Language :: Python :: 3.10",
   "Programming Language :: Python :: 3.11",
+  "Programming Language :: Python :: 3.12",
 ]
 dependencies = [
   "attrs>=23.1.0,<24",
@@ -39,7 +40,7 @@ dependencies = [
   "google-pasta",
   "importlib-metadata>=1.4.0,<7.0",
   "jsonschema",
-  "numpy>=1.9.0,<2.0",
+  "numpy>=1.26.4,<3.0",
   "omegaconf>=2.2,<=2.3",
   "packaging>=20.0",
   "pandas",

requirements/extras/test_requirements.txt

@@ -1,5 +1,5 @@
 tox==3.24.5
-numpy>=1.24.0
+numpy>=1.26.4
 build[virtualenv]==1.2.1
 flake8==4.0.1
 pytest==6.2.5

src/sagemaker/fw_utils.py

@@ -689,7 +689,7 @@ def validate_smdistributed(
         framework_name (str): A string representing the name of framework selected.
         framework_version (str): A string representing the framework version selected.
         py_version (str): A string representing the python version selected.
-        Ex: `py38, py39, py310, py311`
+        Ex: `py38, py39, py310, py311, py312`
         distribution (dict): A dictionary with information to enable distributed training.
             (Defaults to None if distributed training is not enabled.) For example:
 
@@ -762,7 +762,7 @@ def _validate_smdataparallel_args(
         framework_name (str): A string representing the name of framework selected. Ex: `tensorflow`
         framework_version (str): A string representing the framework version selected. Ex: `2.3.1`
         py_version (str): A string representing the python version selected.
-        Ex: `py38, py39, py310, py311`
+        Ex: `py38, py39, py310, py311, py312`
         distribution (dict): A dictionary with information to enable distributed training.
             (Defaults to None if distributed training is not enabled.) Ex:
 
@@ -846,7 +846,7 @@ def validate_distribution(
         framework_name (str): A string representing the name of framework selected.
         framework_version (str): A string representing the framework version selected.
         py_version (str): A string representing the python version selected.
-        Ex: `py38, py39, py310, py311`
+        Ex: `py38, py39, py310, py311, py312`
         image_uri (str): A string representing a Docker image URI.
         kwargs(dict): Additional kwargs passed to this function
 
@@ -1010,7 +1010,7 @@ def validate_torch_distributed_distribution(
                 }
         framework_version (str): A string representing the framework version selected.
         py_version (str): A string representing the python version selected.
-        Ex: `py38, py39, py310, py311`
+        Ex: `py38, py39, py310, py311, py312`
         image_uri (str): A string representing a Docker image URI.
         entry_point (str or PipelineVariable): The absolute or relative path to the local Python
             source file that should be executed as the entry point to
@@ -1162,7 +1162,7 @@ def validate_version_or_image_args(framework_version, py_version, image_uri):
     Args:
         framework_version (str): The version of the framework.
         py_version (str): A string representing the python version selected.
-        Ex: `py38, py39, py310, py311`
+        Ex: `py38, py39, py310, py311, py312`
         image_uri (str): The URI of the image.
 
     Raises:
@@ -1194,7 +1194,7 @@ def create_image_uri(
         instance_type (str): SageMaker instance type. Used to determine device
             type (cpu/gpu/family-specific optimized).
         framework_version (str): The version of the framework.
-        py_version (str): Optional. Python version Ex: `py38, py39, py310, py311`.
+        py_version (str): Optional. Python version Ex: `py38, py39, py310, py311, py312`.
             If not specified, image uri will not include a python component.
         account (str): AWS account that contains the image. (default:
             '520713654638')

src/sagemaker/processing.py

@@ -1465,7 +1465,7 @@ def __init__(
             instance_type (str or PipelineVariable): The type of EC2 instance to use for
                 processing, for example, 'ml.c4.xlarge'.
             py_version (str): Python version you want to use for executing your
-                model training code. Ex `py38, py39, py310, py311`. Value
+                model training code. Ex `py38, py39, py310, py311, py312`. Value
                 is ignored when ``image_uri`` is provided.
             image_uri (str or PipelineVariable): The URI of the Docker image to use for the
                 processing jobs (default: None).

src/sagemaker/serve/model_format/mlflow/constants.py

@@ -19,6 +19,8 @@
     "py39": "1.13.1",
     "py310": "2.2.0",
     "py311": "2.3.0",
+    "py312": "2.5.0",
+
 }
 MODEL_PACKAGE_ARN_REGEX = (
     r"^arn:aws:sagemaker:[a-z0-9\-]+:[0-9]{12}:model-package\/(.*?)(?:/(\d+))?$"

src/sagemaker/serve/utils/conda_in_process.yml

@@ -12,7 +12,7 @@ dependencies:
     - boto3>=1.34.142,<2.0
     - cloudpickle==2.2.1
     - google-pasta
-    - numpy>=1.9.0,<2.0
+    - numpy>=1.26.4,<3.0
     - protobuf>=3.12,<5.0
     - smdebug_rulesconfig==1.0.1
     - importlib-metadata>=1.4.0,<7.0

tests/data/serve_resources/mlflow/pytorch/requirements.txt

@@ -5,7 +5,7 @@ cloudpickle==2.2.1
 defusedxml==0.7.1
 dill==0.3.8
 gmpy2==2.1.2
-numpy==1.24.4
+numpy==1.26.4
 opt-einsum==3.3.0
 packaging==21.3
 pandas==2.2.1

tests/data/serve_resources/mlflow/xgboost/requirements.txt

@@ -1,6 +1,6 @@
 mlflow==2.13.2
 lz4==4.3.2
-numpy==1.24.4
+numpy==1.26.4
 pandas==2.0.3
 psutil==5.9.8
 scikit-learn==1.3.2

tests/unit/sagemaker/jumpstart/constants.py

@@ -14360,7 +14360,7 @@
             "jmespath==1.0.1",
             "jsonschema==4.17.3",
             "multiprocess==0.70.14",
-            "numpy==1.24.3",
+            "numpy==1.26.4",
             "oscrypto==1.3.0",
             "packaging==23.1",
             "pandas==2.0.2",

tox.ini

@@ -5,7 +5,7 @@
 
 [tox]
 isolated_build = true
-envlist = black-format,flake8,pylint,docstyle,sphinx,doc8,twine,py38,py39,py310,py311
+envlist = black-format,flake8,pylint,docstyle,sphinx,doc8,twine,py38,py39,py310,py311,py312
 
 skip_missing_interpreters = False
 
@@ -67,7 +67,7 @@ markers =
 [testenv]
 setenv =
     PYTHONHASHSEED=42
-pip_version = pip==21.3
+pip_version = pip==24.3
 passenv =
     AWS_ACCESS_KEY_ID
     AWS_SECRET_ACCESS_KEY
@@ -90,7 +90,7 @@ commands =
     pytest {posargs}
 deps = .[test]
 depends =
-    {py38,py39,py310,p311}: clean
+    {py38,py39,py310,py311,py312}: clean
 
 [testenv:runcoverage]
 description = run unit tests with coverage
@@ -132,7 +132,7 @@ commands =
     twine check dist/*.tar.gz
 
 [testenv:sphinx]
-pip_version = pip==21.3
+pip_version = pip==24.3
 changedir = doc
 # pip install requirements.txt is separate as RTD does it in separate steps
 # having the requirements.txt installed in deps above results in Double Requirement exception