fix: add v2 warning messages

src/sagemaker/__init__.py

@@ -13,6 +13,7 @@
 """Placeholder docstring"""
 from __future__ import absolute_import
 
+import logging
 import importlib_metadata
 
 from sagemaker import estimator, parameter, tuner  # noqa: F401
@@ -61,3 +62,9 @@
 from sagemaker.automl.candidate_estimator import CandidateEstimator, CandidateStep  # noqa: F401
 
 __version__ = importlib_metadata.version("sagemaker")
+
+logging.getLogger("sagemaker").warning(
+    "SageMaker Python SDK v2 will no longer support Python 2. "
+    "Please see https://github.com/aws/sagemaker-python-sdk/issues/1459 "
+    "for more information"
+)

src/sagemaker/amazon/amazon_estimator.py

@@ -616,6 +616,11 @@ def get_image_uri(region_name, repo_name, repo_version=1):
         repo_name:
         repo_version:
     """
+    logger.warning(
+        "'get_image_uri' method will be deprecated in favor of 'ImageURIProvider' class "
+        "in SageMaker Python SDK v2."
+    )
+
     if repo_name == "xgboost":
         if not _is_latest_xgboost_version(repo_version):
             logging.warning(

src/sagemaker/amazon/kmeans.py

@@ -13,6 +13,8 @@
 """Placeholder docstring"""
 from __future__ import absolute_import
 
+import logging
+
 from sagemaker.amazon.amazon_estimator import AmazonAlgorithmEstimatorBase, registry
 from sagemaker.amazon.common import numpy_to_record_serializer, record_deserializer
 from sagemaker.amazon.hyperparameter import Hyperparameter as hp  # noqa
@@ -23,6 +25,9 @@
 from sagemaker.vpc_utils import VPC_CONFIG_DEFAULT
 
 
+logger = logging.getLogger("sagemaker")
+
+
 class KMeans(AmazonAlgorithmEstimatorBase):
     """Placeholder docstring"""
 
@@ -154,6 +159,12 @@ def __init__(
         self.center_factor = center_factor
         self.eval_metrics = eval_metrics
 
+        if eval_metrics is not None:
+            logger.warning(
+                "Parameter 'eval_metrics' hyperparameter will be deprecated for 1P estimators "
+                "in SageMaker Python SDK v2."
+            )
+
     def create_model(self, vpc_config_override=VPC_CONFIG_DEFAULT, **kwargs):
         """Return a :class:`~sagemaker.amazon.kmeans.KMeansModel` referencing
         the latest s3 model data produced by this Estimator.

src/sagemaker/amazon/randomcutforest.py

@@ -13,6 +13,8 @@
 """Placeholder docstring"""
 from __future__ import absolute_import
 
+import logging
+
 from sagemaker.amazon.amazon_estimator import AmazonAlgorithmEstimatorBase, registry
 from sagemaker.amazon.common import numpy_to_record_serializer, record_deserializer
 from sagemaker.amazon.hyperparameter import Hyperparameter as hp  # noqa
@@ -23,6 +25,9 @@
 from sagemaker.vpc_utils import VPC_CONFIG_DEFAULT
 
 
+logger = logging.getLogger("sagemaker")
+
+
 class RandomCutForest(AmazonAlgorithmEstimatorBase):
     """Placeholder docstring"""
 
@@ -119,6 +124,12 @@ def __init__(
         self.num_trees = num_trees
         self.eval_metrics = eval_metrics
 
+        if eval_metrics is not None:
+            logger.warning(
+                "Parameter 'eval_metrics' hyperparameter will be deprecated for 1P estimators "
+                "in SageMaker Python SDK v2."
+            )
+
     def create_model(self, vpc_config_override=VPC_CONFIG_DEFAULT, **kwargs):
         """Return a :class:`~sagemaker.amazon.RandomCutForestModel` referencing
         the latest s3 model data produced by this Estimator.

src/sagemaker/estimator.py

@@ -1273,6 +1273,9 @@ def __init__(
                 https://docs.aws.amazon.com/sagemaker/latest/dg/API_AlgorithmSpecification.html#SageMaker-Type-AlgorithmSpecification-EnableSageMakerMetricsTimeSeries
                 (default: ``None``).
         """
+        warnings.warn(
+            "Parameter 'image_name' will be renamed to 'image_uri' in SageMaker Python SDK v2."
+        )
         self.image_name = image_name
         self.hyperparam_dict = hyperparameters.copy() if hyperparameters else {}
         super(Estimator, self).__init__(
@@ -1635,6 +1638,10 @@ def __init__(
         self.container_log_level = container_log_level
         self.code_location = code_location
         self.image_name = image_name
+        if image_name is not None:
+            warnings.warn(
+                "Parameter 'image_name' will be renamed to 'image_uri' in SageMaker Python SDK v2."
+            )
 
         self.uploaded_code = None
 

src/sagemaker/fw_utils.py

@@ -34,7 +34,10 @@
 instantiated with positional or keyword arguments.
 """
 
-EMPTY_FRAMEWORK_VERSION_WARNING = "No framework_version specified, defaulting to version {}."
+EMPTY_FRAMEWORK_VERSION_WARNING = (
+    "No framework_version specified, defaulting to version {}. "
+    "framework_version will be required in SageMaker Python SDK v2."
+)
 LATER_FRAMEWORK_VERSION_WARNING = (
     "This is not the latest supported version. "
     "If you would like to use version {latest}, "
@@ -52,6 +55,10 @@
     "fully leverage all GPU cores; the parameter server will be configured to run "
     "only one worker per host regardless of the number of GPUs."
 )
+PARAMETER_V2_RENAME_WARNING = (
+    "Parameter {v1_parameter_name} will be renamed to {v2_parameter_name} "
+    "in SageMaker Python SDK v2."
+)
 
 
 EMPTY_FRAMEWORK_VERSION_ERROR = (
@@ -253,6 +260,11 @@ def create_image_uri(
     Returns:
         str: The appropriate image URI based on the given parameters.
     """
+    logger.warning(
+        "'create_image_uri' will be deprecated in favor of 'ImageURIProvider' class "
+        "in SageMaker Python SDK v2."
+    )
+
     optimized_families = optimized_families or []
 
     if py_version and py_version not in VALID_PY_VERSIONS:
@@ -647,6 +659,17 @@ def python_deprecation_warning(framework, latest_supported_version):
     )
 
 
+def parameter_v2_rename_warning(v1_parameter_name, v2_parameter_name):
+    """
+    Args:
+        v1_parameter_name:
+        v2_parameter_name:
+    """
+    return PARAMETER_V2_RENAME_WARNING.format(
+        v1_parameter_name=v1_parameter_name, v2_parameter_name=v2_parameter_name
+    )
+
+
 def _region_supports_debugger(region_name):
     """Returns boolean indicating whether the region supports Amazon SageMaker Debugger.
 

src/sagemaker/inputs.py

@@ -13,9 +13,13 @@
 """Amazon SageMaker channel configurations for S3 data sources and file system data sources"""
 from __future__ import absolute_import, print_function
 
+import logging
+
 FILE_SYSTEM_TYPES = ["FSxLustre", "EFS"]
 FILE_SYSTEM_ACCESS_MODES = ["ro", "rw"]
 
+logger = logging.getLogger("sagemaker")
+
 
 class s3_input(object):
     """Amazon SageMaker channel configurations for S3 data sources.
@@ -76,6 +80,9 @@ def __init__(
                 this channel. See the SageMaker API documentation for more info:
                 https://docs.aws.amazon.com/sagemaker/latest/dg/API_ShuffleConfig.html
         """
+        logger.warning(
+            "'s3_input' class will be renamed to 'TrainingInput' in SageMaker Python SDK v2."
+        )
 
         self.config = {
             "DataSource": {"S3DataSource": {"S3DataType": s3_data_type, "S3Uri": s3_data}}

src/sagemaker/model.py

@@ -108,6 +108,10 @@ def __init__(
             model_kms_key (str): KMS key ARN used to encrypt the repacked
                 model archive file if the model is repacked
         """
+        LOGGER.warning(
+            "Parameter 'image' will be renamed to 'image_uri' in SageMaker Python SDK v2."
+        )
+
         self.model_data = model_data
         self.image = image
         self.role = role

src/sagemaker/mxnet/estimator.py

@@ -21,6 +21,7 @@
     framework_version_from_tag,
     empty_framework_version_warning,
     python_deprecation_warning,
+    parameter_v2_rename_warning,
     is_version_equal_or_higher,
     warn_if_parameter_server_with_multi_gpu,
 )
@@ -128,6 +129,7 @@ def __init__(
             )
 
         if distributions is not None:
+            logger.warning(parameter_v2_rename_warning("distributions", "distribution"))
             train_instance_type = kwargs.get("train_instance_type")
             warn_if_parameter_server_with_multi_gpu(
                 training_instance_type=train_instance_type, distributions=distributions

src/sagemaker/s3.py

@@ -13,11 +13,27 @@
 """This module contains Enums and helper methods related to S3."""
 from __future__ import print_function, absolute_import
 
+import logging
 import os
 
 from six.moves.urllib.parse import urlparse
 from sagemaker.session import Session
 
+logger = logging.getLogger("sagemaker")
+
+SESSION_V2_RENAME_MESSAGE = (
+    "Parameter 'session' will be renamed to 'sagemaker_session' in SageMaker Python SDK v2."
+)
+
+
+def _session_v2_rename_warning(session):
+    """
+    Args:
+        session (sagemaker.session.Session):
+    """
+    if session is not None:
+        logger.warning(SESSION_V2_RENAME_MESSAGE)
+
 
 def parse_s3_url(url):
     """Returns an (s3 bucket, key name/prefix) tuple from a url with an s3
@@ -54,6 +70,7 @@ def upload(local_path, desired_s3_uri, kms_key=None, session=None):
             The S3 uri of the uploaded file(s).
 
         """
+        _session_v2_rename_warning(session)
         sagemaker_session = session or Session()
         bucket, key_prefix = parse_s3_url(url=desired_s3_uri)
         if kms_key is not None:
@@ -80,6 +97,7 @@ def upload_string_as_file_body(body, desired_s3_uri=None, kms_key=None, session=
             str: The S3 uri of the uploaded file(s).
 
         """
+        _session_v2_rename_warning(session)
         sagemaker_session = session or Session()
         bucket, key = parse_s3_url(desired_s3_uri)
 
@@ -107,6 +125,7 @@ def download(s3_uri, local_path, kms_key=None, session=None):
                 using the default AWS configuration chain.
 
         """
+        _session_v2_rename_warning(session)
         sagemaker_session = session or Session()
         bucket, key_prefix = parse_s3_url(url=s3_uri)
         if kms_key is not None:
@@ -131,6 +150,7 @@ def read_file(s3_uri, session=None):
             str: The body of the file.
 
         """
+        _session_v2_rename_warning(session)
         sagemaker_session = session or Session()
         bucket, key_prefix = parse_s3_url(url=s3_uri)
 
@@ -149,6 +169,7 @@ def list(s3_uri, session=None):
             [str]: The list of S3 URIs in the given S3 base uri.
 
         """
+        _session_v2_rename_warning(session)
         sagemaker_session = session or Session()
         bucket, key_prefix = parse_s3_url(url=s3_uri)
 

src/sagemaker/session.py

@@ -181,6 +181,11 @@ def upload_data(self, path, bucket=None, key_prefix="data", extra_args=None):
                 ``s3://{bucket name}/{key_prefix}``.
         """
         # Generate a tuple for each file that we want to upload of the form (local_path, s3_key).
+        LOGGER.warning(
+            "'upload_data' method will be deprecated in favor of 'S3Uploader' class "
+            "in SageMaker Python SDK v2."
+        )
+
         files = []
         key_suffix = None
         if os.path.isdir(path):
@@ -230,6 +235,11 @@ def upload_string_as_file_body(self, body, bucket, key, kms_key=None):
             str: The S3 URI of the uploaded file.
                 The URI format is: ``s3://{bucket name}/{key}``.
         """
+        LOGGER.warning(
+            "'upload_string_as_file_body' method will be deprecated in favor of 'S3Uploader' class "
+            "in SageMaker Python SDK v2."
+        )
+
         if self.s3_resource is None:
             s3 = self.boto_session.resource("s3", region_name=self.boto_region_name)
         else:
@@ -3311,6 +3321,11 @@ def get_execution_role(sagemaker_session=None):
     Returns:
         (str): The role ARN
     """
+    LOGGER.warning(
+        "'get_execution_role' will be renamed to 'notebook_execution_role' "
+        "in SageMaker Python SDK v2."
+    )
+
     if not sagemaker_session:
         sagemaker_session = Session()
     arn = sagemaker_session.get_caller_identity_arn()

src/sagemaker/tensorflow/estimator.py

@@ -311,6 +311,7 @@ def __init__(
             )
 
         if distributions is not None:
+            logger.warning(fw.parameter_v2_rename_warning("distribution", distributions))
             train_instance_type = kwargs.get("train_instance_type")
             fw.warn_if_parameter_server_with_multi_gpu(
                 training_instance_type=train_instance_type, distributions=distributions
@@ -385,7 +386,9 @@ def _validate_args(
 
         if (not self._script_mode_enabled()) and self._only_script_mode_supported():
             logger.warning(
-                "Legacy mode is deprecated in versions 1.13 and higher. Using script mode instead."
+                "Legacy mode is deprecated in versions 1.13 and higher. Using script mode instead. "
+                "Legacy mode and its training parameters will be deprecated in "
+                "SageMaker Python SDK v2. Please use TF 1.13 or higher and script mode."
             )
             self.script_mode = True
 

tests/unit/test_amazon_estimator.py

@@ -486,3 +486,12 @@ def test_is_latest_xgboost_version():
     assert _is_latest_xgboost_version("0.90-1-cpu-py3") is False
 
     assert _is_latest_xgboost_version(XGBOOST_LATEST_VERSION) is True
+
+
+def test_get_image_uri_warn(caplog):
+    warning_message = (
+        "'get_image_uri' method will be deprecated in favor of 'ImageURIProvider' class "
+        "in SageMaker Python SDK v2."
+    )
+    get_image_uri("us-west-2", "kmeans", "latest")
+    assert warning_message in caplog.text

tests/unit/test_inputs.py

@@ -18,7 +18,7 @@
 from sagemaker.inputs import FileSystemInput
 
 
-def test_s3_input_all_defaults():
+def test_s3_input_all_defaults(caplog):
     prefix = "pre"
     actual = s3_input(s3_data=prefix)
     expected = {
@@ -32,6 +32,11 @@ def test_s3_input_all_defaults():
     }
     assert actual.config == expected
 
+    warning_message = (
+        "'s3_input' class will be renamed to 'TrainingInput' in SageMaker Python SDK v2."
+    )
+    assert warning_message in caplog.text
+
 
 def test_s3_input_all_arguments():
     prefix = "pre"

tests/unit/test_kmeans.py

@@ -82,7 +82,7 @@ def test_init_required_named(sagemaker_session):
     assert kmeans.k == ALL_REQ_ARGS["k"]
 
 
-def test_all_hyperparameters(sagemaker_session):
+def test_all_hyperparameters(sagemaker_session, caplog):
     kmeans = KMeans(
         sagemaker_session=sagemaker_session,
         init_method="random",
@@ -110,6 +110,12 @@ def test_all_hyperparameters(sagemaker_session):
         force_dense="True",
     )
 
+    warning_message = (
+        "Parameter 'eval_metrics' hyperparameter will be deprecated for 1P estimators "
+        "in SageMaker Python SDK v2."
+    )
+    assert warning_message in caplog.text
+
 
 def test_image(sagemaker_session):
     kmeans = KMeans(sagemaker_session=sagemaker_session, **ALL_REQ_ARGS)