Merge branch 'master' into P50369404

Author: prkrishnan1

.githooks/pre-push

@@ -0,0 +1,16 @@
+#!/bin/sh
+# this pre-push hook runs style checks and unit tests in python 3.6, 3.7, and 3.8 using tox.
+
+set -e
+
+TOX_PARALLEL_NO_SPINNER=1,
+PY_COLORS=0
+start_time=`date +%s`
+tox -e flake8,pylint,docstyle,black-check,twine --parallel all
+./ci-scripts/displaytime.sh 'flake8,pylint,docstyle,black-check,twine' $start_time
+start_time=`date +%s`
+tox -e sphinx,doc8 --parallel all
+./ci-scripts/displaytime.sh 'sphinx,doc8' $start_time
+start_time=`date +%s`
+tox -e py36,py37,py38 --parallel all -- tests/unit
+./ci-scripts/displaytime.sh 'py36,py37,py38 unit' $start_time

CHANGELOG.md

@@ -1,5 +1,11 @@
 # Changelog
 
+## v2.63.2 (2021-10-18)
+
+### Bug Fixes and Other Changes
+
+ * Update timeouts for integ tests from 20 to 40
+
 ## v2.63.1 (2021-10-14)
 
 ### Bug Fixes and Other Changes

README.rst

@@ -154,6 +154,18 @@ You can also run them in parallel:
     tox -- -n auto tests/integ
 
 
+Git Hooks
+~~~~~~~~~
+
+to enable all git hooks in the .githooks directory, run these commands in the repository directory:
+
+::
+
+    find .git/hooks -type l -exec rm {} \;
+    find .githooks -type f -exec ln -sf ../../{} .git/hooks/ \;
+
+To enable an individual git hook, simply move it from the .githooks/ directory to the .git/hooks/ directory.
+
 Building Sphinx docs
 ~~~~~~~~~~~~~~~~~~~~
 

VERSION

@@ -1 +1 @@
-2.63.2.dev0
+2.63.3.dev0

src/sagemaker/deprecations.py

@@ -50,6 +50,46 @@ def renamed_warning(phrase):
     _warn(f"{phrase} has been renamed")
 
 
+def deprecation_warn(name, date, msg=None):
+    """Raise a warning for soon to be deprecated feature in sagemaker>=2
+
+    Args:
+        name (str): Name of the feature
+        date (str): the date when the feature will be deprecated
+        msg (str): the prefix phrase of the warning message.
+    """
+    _warn(f"{name} will be deprecated on {date}.{msg}")
+
+
+def deprecation_warning(date, msg=None):
+    """Decorator for raising deprecation warning for a feature in sagemaker>=2
+
+    Args:
+        date (str): the date when the feature will be deprecated
+        msg (str): the prefix phrase of the warning message.
+
+    Usage:
+        @deprecation_warning(msg="message", date="date")
+        def sample_function():
+            print("xxxx....")
+
+        @deprecation_warning(msg="message", date="date")
+        class SampleClass():
+            def __init__(self):
+                print("xxxx....")
+
+    """
+
+    def deprecate(obj):
+        def wrapper(*args, **kwargs):
+            deprecation_warn(obj.__name__, date, msg)
+            return obj(*args, **kwargs)
+
+        return wrapper
+
+    return deprecate
+
+
 def renamed_kwargs(old_name, new_name, value, kwargs):
     """Checks if the deprecated argument is in kwargs
 
@@ -106,6 +146,28 @@ def func(*args, **kwargs):  # pylint: disable=W0613
     return func
 
 
+def deprecated(obj):
+    """Decorator for raising deprecated warning for a feature in sagemaker>=2
+
+    Usage:
+        @deprecated
+        def sample_function():
+            print("xxxx....")
+
+        @deprecated
+        class SampleClass():
+            def __init__(self):
+                print("xxxx....")
+
+    """
+
+    def wrapper(*args, **kwargs):
+        removed_warning(obj.__name__)
+        return obj(*args, **kwargs)
+
+    return wrapper
+
+
 def deprecated_function(func, name):
     """Wrap a function with a deprecation warning.
 

src/sagemaker/serverless/model.py

@@ -20,10 +20,15 @@
 import botocore
 
 from sagemaker.model import ModelBase
-
+from sagemaker.deprecations import deprecation_warning
 from .predictor import LambdaPredictor
 
 
+@deprecation_warning(
+    msg="Based on customer experience and feedback an"
+    " alternative support will be added in near future",
+    date="10/27/2021",
+)
 class LambdaModel(ModelBase):
     """A model that can be deployed to Lambda."""
 

src/sagemaker/serverless/predictor.py

@@ -20,8 +20,14 @@
 
 from sagemaker import deserializers, serializers
 from sagemaker.predictor import PredictorBase
+from sagemaker.deprecations import deprecation_warning
 
 
+@deprecation_warning(
+    msg="Based on customer experience and feedback an"
+    " alternative support will be added in near future",
+    date="10/27/2021",
+)
 class LambdaPredictor(PredictorBase):
     """A deployed model hosted on Lambda."""
 

tests/integ/test_marketplace.py

@@ -24,8 +24,7 @@
 from sagemaker import AlgorithmEstimator, ModelPackage
 from sagemaker.serializers import CSVSerializer
 from sagemaker.tuner import IntegerParameter, HyperparameterTuner
-from sagemaker.utils import sagemaker_timestamp
-from sagemaker.utils import _aws_partition
+from sagemaker.utils import sagemaker_timestamp, _aws_partition, unique_name_from_base
 from tests.integ import DATA_DIR
 from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name
 from tests.integ.marketplace_utils import REGION_ACCOUNT_MAP
@@ -117,7 +116,7 @@ def test_marketplace_attach(sagemaker_session, cpu_instance_type):
             instance_count=1,
             instance_type=cpu_instance_type,
             sagemaker_session=sagemaker_session,
-            base_job_name="test-marketplace",
+            base_job_name=unique_name_from_base("test-marketplace"),
         )
 
         train_input = mktplace.sagemaker_session.upload_data(
@@ -205,7 +204,7 @@ def test_marketplace_tuning_job(sagemaker_session, cpu_instance_type):
         instance_count=1,
         instance_type=cpu_instance_type,
         sagemaker_session=sagemaker_session,
-        base_job_name="test-marketplace",
+        base_job_name=unique_name_from_base("test-marketplace"),
     )
 
     train_input = mktplace.sagemaker_session.upload_data(
@@ -218,7 +217,7 @@ def test_marketplace_tuning_job(sagemaker_session, cpu_instance_type):
 
     tuner = HyperparameterTuner(
         estimator=mktplace,
-        base_tuning_job_name="byo",
+        base_tuning_job_name=unique_name_from_base("byo"),
         objective_metric_name="validation:accuracy",
         hyperparameter_ranges=hyperparameter_ranges,
         max_jobs=2,
@@ -248,7 +247,7 @@ def test_marketplace_transform_job(sagemaker_session, cpu_instance_type):
         instance_count=1,
         instance_type=cpu_instance_type,
         sagemaker_session=sagemaker_session,
-        base_job_name="test-marketplace",
+        base_job_name=unique_name_from_base("test-marketplace"),
     )
 
     train_input = algo.sagemaker_session.upload_data(

tests/integ/test_model_monitor.py

@@ -92,7 +92,11 @@ def predictor(sagemaker_session, tensorflow_inference_latest_version):
         key_prefix="tensorflow-serving/models",
     )
     with tests.integ.timeout.timeout_and_delete_endpoint_by_name(
-        endpoint_name=endpoint_name, sagemaker_session=sagemaker_session, hours=2
+        endpoint_name=endpoint_name,
+        sagemaker_session=sagemaker_session,
+        hours=2,
+        sleep_between_cleanup_attempts=20,
+        exponential_sleep=True,
     ):
         model = TensorFlowModel(
             model_data=model_data,

tests/integ/timeout.py

@@ -54,6 +54,7 @@ def timeout_and_delete_endpoint_by_name(
     minutes=45,
     hours=0,
     sleep_between_cleanup_attempts=10,
+    exponential_sleep=False,
 ):
     limit = seconds + 60 * minutes + 3600 * hours
 
@@ -83,7 +84,13 @@ def timeout_and_delete_endpoint_by_name(
                         # avoids the inner exception to be overwritten
                         pass
                 # trying to delete the resource again in 10 seconds
-                sleep(sleep_between_cleanup_attempts)
+                if exponential_sleep:
+                    _sleep_between_cleanup_attempts = sleep_between_cleanup_attempts * (
+                        3 - attempts
+                    )
+                else:
+                    _sleep_between_cleanup_attempts = sleep_between_cleanup_attempts
+                sleep(_sleep_between_cleanup_attempts)
 
 
 @contextmanager
@@ -150,7 +157,9 @@ def _delete_schedules_associated_with_endpoint(sagemaker_session, endpoint_name)
             monitor.delete_monitoring_schedule()
         except Exception as e:
             LOGGER.warning(
-                "Failed to delete monitor {}".format(monitor.monitoring_schedule_name), e
+                "Failed to delete monitor {},\nError: {}".format(
+                    monitor.monitoring_schedule_name, e
+                )
             )