Merge branch 'master' into fix/minor-jumpstart-dev-ex-improvements

Author: evakravi

.gitignore

@@ -34,3 +34,4 @@ env/
 **/_repack_script_launcher.sh
 tests/data/**/_repack_model.py
 tests/data/experiment/sagemaker-dev-1.0.tar.gz
+src/sagemaker/serve/tmp_workspace

CHANGELOG.md

@@ -1,5 +1,44 @@
 # Changelog
 
+## v2.199.0 (2023-11-30)
+
+### Features
+
+ * Update boto3 version to 1.33.3
+ * Goldfinch InferenceComponent integration
+ * Add Pipeline step decorator, NotebookJobStep, and scheduler
+ * ModelBuilder for simplified model testing and deployment
+
+### Bug Fixes and Other Changes
+
+ * Skip failing integ tests
+ * chore: add jumpstart gated model integration tests
+ * disable integration tests for Inference Component based endpoint for non supported regions
+ * remove unnecessary whl file - Galactus
+ * refactor endpoint type enums, comments, docstrings, method names…
+ * Address SA feedback regarding deployment straight to Endpoint Mode - Galactus
+ * fix HuggingFace GEN2 model deployment arguments
+ * when customer role does not have permission to read logs from CW, default to standard logging - Galactus
+ * Add pagination for ListInferenceComponent API responses, address non-blocking comments
+ * Create CSVSerializerWrapper - Galactus
+ * Model builder Final Fixes
+ * remote function include_local_workdir default value
+ * use copy instead of move in bootstrap script
+ * WaiterError on failed pipeline execution. results()
+ * Add a unit test for consistency between step and remote decorator
+ * merge WorkdirConfig and custom_filter_filter parameters
+ * Add back mixed step type integ test
+ * do not delete temp folder generated by sdist
+ * make collect_parameters decorator as private
+ * HMAC signing for ModelBuilder Triton python backend
+
+### Documentation Changes
+
+ * update docstring for Generation two endpoint and validation message
+ * galactus doc updates
+ * CustomFileFilter doc updates
+ * NotebookJobSteps class parameter severity update
+
 ## v2.198.0 (2023-11-27)
 
 ### Features

MANIFEST.in

@@ -1,6 +1,7 @@
 recursive-include src/sagemaker *.py
 
 include src/sagemaker/image_uri_config/*.json
+include src/sagemaker/serve/requirements.txt
 recursive-include requirements *
 
 include VERSION

VERSION

@@ -1 +1 @@
-2.198.1.dev0
+2.199.1.dev0

doc/api/inference/model_builder.rst

@@ -0,0 +1,16 @@
+Model Builder
+-------------
+
+This module contains classes related to Amazon Sagemaker Model Builder
+
+.. autoclass:: sagemaker.serve.builder.model_builder.ModelBuilder
+
+.. automethod:: sagemaker.serve.builder.model_builder.ModelBuilder.build
+
+.. automethod:: sagemaker.serve.builder.model_builder.ModelBuilder.save
+
+.. autoclass:: sagemaker.serve.spec.inference_spec.InferenceSpec
+
+.. autoclass:: sagemaker.serve.builder.schema_builder.SchemaBuilder
+
+.. autoclass:: sagemaker.serve.marshalling.custom_payload_translator.CustomPayloadTranslator

doc/overview.rst

@@ -24,3 +24,10 @@ Future
 .. automethod:: sagemaker.remote_function.client.list_futures
 
 .. automethod:: sagemaker.remote_function.client.get_future
+
+
+CustomFileFilter
+----------------
+
+.. autoclass:: sagemaker.remote_function.custom_file_filter.CustomFileFilter
+

doc/remote_function/sagemaker.remote_function.rst

@@ -96,6 +96,10 @@ Pipeline Context
 .. autoclass:: sagemaker.workflow.pipeline_context.LocalPipelineSession
     :members:
 
+Pipeline Schedule
+-----------------
+
+.. autoclass:: sagemaker.workflow.triggers.PipelineSchedule
 
 Parallelism Configuration
 -------------------------
@@ -120,7 +124,6 @@ Selective Execution Config
 
 .. autoclass:: sagemaker.workflow.selective_execution_config.SelectiveExecutionConfig
 
-
 Properties
 ----------
 
@@ -162,6 +165,8 @@ Steps
 
 .. autoclass:: sagemaker.workflow.steps.ProcessingStep
 
+.. autoclass:: sagemaker.workflow.notebook_job_step.NotebookJobStep
+
 .. autoclass:: sagemaker.workflow.steps.CreateModelStep
 
 .. autoclass:: sagemaker.workflow.callback_step.CallbackStep
@@ -185,3 +190,14 @@ Steps
 .. autoclass:: sagemaker.workflow.emr_step.EMRStep
 
 .. autoclass:: sagemaker.workflow.automl_step.AutoMLStep
+
+@step decorator
+---------------
+
+.. automethod:: sagemaker.workflow.function_step.step
+
+.. autoclass:: sagemaker.workflow.function_step.DelayedReturn
+
+.. autoclass:: sagemaker.workflow.step_outputs.StepOutput
+
+.. autofunction:: sagemaker.workflow.step_outputs.get_step

doc/workflows/pipelines/sagemaker.workflow.pipelines.rst

@@ -0,0 +1,53 @@
+trap "exit" INT
+
+eval "$(conda shell.zsh hook)"
+
+conda activate $1
+
+echo Installing tox if necessary
+pip install --upgrade tox
+
+echo Running unit testing in Python3.8 Conda Environement
+
+if "$4";
+then
+    echo Clearing .tox cache for Python3.8
+    rm -r .tox/py38
+fi
+
+tox -e py38 -- tests/unit/sagemaker/serve/.
+
+if "$3";
+then
+    echo Running Python3.8 Integration Tests
+    tox -e py38 -- tests/integ/sagemaker/serve/.
+fi
+
+conda deactivate
+
+conda activate $2
+
+echo Installing tox if necessary
+pip install --upgrade tox
+
+echo Running unit testing in Python3.10 Conda Environment
+
+if "$4";
+then
+    echo Clearing .tox cache for Python3.10
+    rm -r .tox/py10
+fi
+
+tox -e py310 -- tests/unit/sagemaker/serve/. 
+
+if "$3";
+then
+    echo Running Python3.10 Integration Tests
+    tox -e py310 -- tests/integ/sagemaker/serve/.
+fi
+
+conda deactivate
+
+echo Coverage report after testing:
+
+coverage report -i --fail-under=75 --include "*/serve/*" --omit '*in_process*,*interceptors*,*__init__*,*build_model*,*function_pointers*'

inference-experience-dev-tester.sh

@@ -29,3 +29,13 @@ docker>=5.0.2,<7.0.0
 PyYAML==6.0
 pyspark==3.3.1
 sagemaker-feature-store-pyspark-3.3
+# TODO find workaround
+xgboost>=1.6.2,<=1.7.6
+pillow>=9.5.0,<=10.0.0
+transformers==4.32.0
+sentencepiece==0.1.99
+# https://github.com/triton-inference-server/server/issues/6246
+tritonclient[http]<2.37.0
+onnx==1.14.1
+# tf2onnx==1.15.1
+nbformat>=5.9,<6

requirements/extras/test_requirements.txt

@@ -15,6 +15,7 @@
 
 import os
 from glob import glob
+import sys
 
 from setuptools import find_packages, setup
 
@@ -48,7 +49,7 @@ def read_requirements(filename):
 # Declare minimal set for installation
 required_packages = [
     "attrs>=23.1.0,<24",
-    "boto3>=1.29.6,<2.0",
+    "boto3>=1.33.3,<2.0",
     "cloudpickle==2.2.1",
     "google-pasta",
     "numpy>=1.9.0,<2.0",
@@ -63,6 +64,13 @@ def read_requirements(filename):
     "jsonschema",
     "platformdirs",
     "tblib==1.7.0",
+    "urllib3<1.27",
+    "uvicorn==0.22.0",
+    "fastapi==0.95.2",
+    "requests",
+    "docker",
+    "tqdm",
+    "psutil",
 ]
 
 # Specific use case dependencies
@@ -77,14 +85,29 @@ def read_requirements(filename):
 # Meta dependency groups
 extras["all"] = [item for group in extras.values() for item in group]
 # Tests specific dependencies (do not need to be included in 'all')
-extras["test"] = (read_requirements("requirements/extras/test_requirements.txt"),)
+test_dependencies = read_requirements("requirements/extras/test_requirements.txt")
+# remove torch and torchvision if python version is not 3.10
+if sys.version_info.minor != 10:
+    test_dependencies = [
+        module
+        for module in test_dependencies
+        if not (
+            module.startswith("transformers")
+            or module.startswith("sentencepiece")
+            or module.startswith("torch")
+            or module.startswith("torchvision")
+        )
+    ]
+
+extras["test"] = (test_dependencies,)
 
 setup(
     name="sagemaker",
     version=read_version(),
     description="Open source library for training and deploying models on Amazon SageMaker.",
     packages=find_packages("src"),
     package_dir={"": "src"},
+    package_data={"": ["*.whl"]},
     py_modules=[os.path.splitext(os.path.basename(path))[0] for path in glob("src/*.py")],
     include_package_data=True,
     long_description=read("README.rst"),
@@ -110,4 +133,7 @@ def read_requirements(filename):
             "sagemaker-upgrade-v2=sagemaker.cli.compatibility.v2.sagemaker_upgrade_v2:main",
         ]
     },
+    scripts=[
+        "src/sagemaker/serve/model_server/triton/pack_conda_env.sh",
+    ],
 )

setup.py

@@ -293,6 +293,7 @@ def __init__(
         sagemaker_session=None,
         serializer=RecordSerializer(),
         deserializer=RecordDeserializer(),
+        component_name=None,
     ):
         """Initialization for FactorizationMachinesPredictor class.
 
@@ -307,12 +308,15 @@ def __init__(
                 serializes input data to x-recordio-protobuf format.
             deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
                 Default parses responses from x-recordio-protobuf format.
+            component_name (str): Optional. Name of the Amazon SageMaker inference
+                component corresponding the predictor.
         """
         super(FactorizationMachinesPredictor, self).__init__(
             endpoint_name,
             sagemaker_session,
             serializer=serializer,
             deserializer=deserializer,
+            component_name=component_name,
         )
 
 

src/sagemaker/amazon/factorization_machines.py

@@ -196,6 +196,7 @@ def __init__(
         sagemaker_session=None,
         serializer=CSVSerializer(),
         deserializer=JSONDeserializer(),
+        component_name=None,
     ):
         """Creates object to be used to get dot product of entity nad IP address.
 
@@ -210,12 +211,15 @@ def __init__(
                 serializes input data to text/csv.
             deserializer (callable): Optional. Default parses JSON responses
                 using ``json.load(...)``.
+            component_name (str): Optional. Name of the Amazon SageMaker inference
+                component corresponding the predictor.
         """
         super(IPInsightsPredictor, self).__init__(
             endpoint_name,
             sagemaker_session,
             serializer=serializer,
             deserializer=deserializer,
+            component_name=component_name,
         )
 
 

src/sagemaker/amazon/ipinsights.py

@@ -222,6 +222,7 @@ def __init__(
         sagemaker_session=None,
         serializer=RecordSerializer(),
         deserializer=RecordDeserializer(),
+        component_name=None,
     ):
         """Initialization for KMeansPredictor class.
 
@@ -236,12 +237,15 @@ def __init__(
                 serializes input data to x-recordio-protobuf format.
             deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
                 Default parses responses from x-recordio-protobuf format.
+            component_name (str): Optional. Name of the Amazon SageMaker inference
+                component corresponding to the predictor.
         """
         super(KMeansPredictor, self).__init__(
             endpoint_name,
             sagemaker_session,
             serializer=serializer,
             deserializer=deserializer,
+            component_name=component_name,
         )
 
 

src/sagemaker/amazon/kmeans.py

@@ -213,6 +213,7 @@ def __init__(
         sagemaker_session=None,
         serializer=RecordSerializer(),
         deserializer=RecordDeserializer(),
+        component_name=None,
     ):
         """Function to initialize KNNPredictor.
 
@@ -227,12 +228,15 @@ def __init__(
                 serializes input data to x-recordio-protobuf format.
             deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
                 Default parses responses from x-recordio-protobuf format.
+            component_name (str): Optional. Name of the Amazon SageMaker inference
+                component corresponding to the predictor.
         """
         super(KNNPredictor, self).__init__(
             endpoint_name,
             sagemaker_session,
             serializer=serializer,
             deserializer=deserializer,
+            component_name=component_name,
         )
 
 

src/sagemaker/amazon/knn.py

@@ -197,6 +197,7 @@ def __init__(
         sagemaker_session=None,
         serializer=RecordSerializer(),
         deserializer=RecordDeserializer(),
+        component_name=None,
     ):
         """Creates "LDAPredictor" object to be used for transforming input vectors.
 
@@ -211,12 +212,15 @@ def __init__(
                 serializes input data to x-recordio-protobuf format.
             deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
                 Default parses responses from x-recordio-protobuf format.
+            component_name (str): Optional. Name of the Amazon SageMaker inference
+                component corresponding to the predictor.
         """
         super(LDAPredictor, self).__init__(
             endpoint_name,
             sagemaker_session,
             serializer=serializer,
             deserializer=deserializer,
+            component_name=component_name,
         )