Codestyle

Author: jinyoung-lim

src/sagemaker/image_uris.py

@@ -54,6 +54,7 @@
     "vw",
 ]
 
+
 @override_pipeline_parameter_var
 def retrieve(
     framework,
@@ -199,7 +200,7 @@ def retrieve(
         deprecation_warn(
             "SageMaker-hosted RL images no longer accept new pull requests and",
             "April 2024",
-            " Please pass in `image_uri` to use RLEstimator"
+            " Please pass in `image_uri` to use RLEstimator",
         )
 
     py_version = _validate_py_version_and_set_if_needed(py_version, version_config, framework)

src/sagemaker/rl/estimator.py

@@ -115,21 +115,21 @@ def __init__(
                 executing your model training code.
 
                 .. warning::
-                    This ``toolkit`` argument discontinued support for new RL users on April 2024. To use
-                    RLEstimator, please pass in ``image_uri``.
+                    This ``toolkit`` argument discontinued support for new RL users on April 2024.
+                    To use RLEstimator, pass in ``image_uri``.
             toolkit_version (str): RL toolkit version you want to be use for executing your
                 model training code.
 
                 .. warning::
-                    This ``toolkit_version`` argument discontinued support for new RL users on April 2024.
-                    To use RLEstimator, please pass in ``image_uri``.
+                    This ``toolkit_version`` argument discontinued support for new RL users on
+                    April 2024. To use RLEstimator, pass in ``image_uri``.
             framework (sagemaker.rl.RLFramework): Framework (MXNet or
                 TensorFlow) you want to be used as a toolkit backed for
                 reinforcement learning training.
 
                 .. warning::
-                    This ``framework`` argument discontinued support for new RL users on April 2024. To
-                    use RLEstimator, please pass in ``image_uri``.
+                    This ``framework`` argument discontinued support for new RL users on April
+                    2024. To use RLEstimator, pass in ``image_uri``.
             source_dir (str or PipelineVariable): Path (absolute, relative or an S3 URI)
                 to a directory with any other training source code dependencies aside from
                 the entry point file (default: None). If ``source_dir`` is an S3 URI, it must
@@ -141,11 +141,12 @@ def __init__(
                 SageMaker. For convenience, this accepts other types for keys
                 and values.
             image_uri (str or PipelineVariable): An ECR url for an image the estimator would use
-                for training and hosting. Example: 123.dkr.ecr.us-west-2.amazonaws.com/my-custom-image:1.0
+                for training and hosting.
+                Example: 123.dkr.ecr.us-west-2.amazonaws.com/my-custom-image:1.0
             metric_definitions (list[dict[str, str] or list[dict[str, PipelineVariable]]):
                 A list of dictionaries that defines the metric(s) used to evaluate the
-                training jobs. Each dictionary contains two keys: 'Name' for the name of the metric,
-                and 'Regex' for the regular expression used to extract the
+                training jobs. Each dictionary contains two keys: 'Name' for the name of the
+                 metric, and 'Regex' for the regular expression used to extract the
                 metric from the logs. This should be defined only for jobs that
                 don't use an Amazon algorithm.
             **kwargs: Additional kwargs passed to the
@@ -167,11 +168,23 @@ def __init__(
         self._validate_images_args(toolkit, toolkit_version, framework, image_uri)
 
         if toolkit:
-            deprecation_warn("The argument `toolkit`", "April 2024", " Please pass in `image_uri` to use RLEstimator")
+            deprecation_warn(
+                "The argument `toolkit`",
+                "April 2024",
+                " Pass in `image_uri` to use RLEstimator",
+            )
         if toolkit_version:
-            deprecation_warn("The argument `toolkit_version`", "April 2024", " Please pass in `image_uri` to use RLEstimator")
+            deprecation_warn(
+                "The argument `toolkit_version`",
+                "April 2024",
+                " Pass in `image_uri` to use RLEstimator",
+            )
         if framework:
-            deprecation_warn("The argument `framework`", "April 2024", " Please pass in `image_uri` to use RLEstimator")
+            deprecation_warn(
+                "The argument `framework`",
+                "April 2024",
+                " Pass in `image_uri` to use RLEstimator",
+            )
 
         if not image_uri:
             self._validate_toolkit_support(toolkit.value, toolkit_version, framework.value)
@@ -260,7 +273,7 @@ def create_model(
         base_args["name"] = self._get_or_create_name(kwargs.get("name"))
 
         if not entry_point and (source_dir or dependencies):
-            raise AttributeError("Please provide an `entry_point`.")
+            raise AttributeError("Provide an `entry_point`.")
 
         entry_point = entry_point or self._model_entry_point()
         source_dir = source_dir or self._model_source_dir()
@@ -291,7 +304,7 @@ def create_model(
                 framework_version=self.framework_version, py_version=PYTHON_VERSION, **extended_args
             )
         raise ValueError(
-            "An unknown RLFramework enum was passed in. framework: {}".format(self.framework)
+            f"An unknown RLFramework enum was passed in. framework: {self.framework}"
         )
 
     def training_image_uri(self):
@@ -349,10 +362,9 @@ def _prepare_init_params_from_job_description(cls, job_details, model_channel_na
         toolkit, toolkit_version = cls._toolkit_and_version_from_tag(tag)
 
         if not cls._is_combination_supported(toolkit, toolkit_version, framework):
+            training_job_name = job_details["TrainingJobName"]
             raise ValueError(
-                "Training job: {} didn't use image for requested framework".format(
-                    job_details["TrainingJobName"]
-                )
+                f"Training job: {training_job_name} didn't use image for requested framework"
             )
 
         init_params["toolkit"] = RLToolkit(toolkit)
@@ -392,17 +404,15 @@ def _validate_framework_format(cls, framework):
         """Placeholder docstring."""
         if framework and framework not in list(RLFramework):
             raise ValueError(
-                "Invalid type: {}, valid RL frameworks types are: {}".format(
-                    framework, list(RLFramework)
-                )
+                f"Invalid type: {framework}, valid RL frameworks types are: {list(RLFramework)}"
             )
 
     @classmethod
     def _validate_toolkit_format(cls, toolkit):
         """Placeholder docstring."""
         if toolkit and toolkit not in list(RLToolkit):
             raise ValueError(
-                "Invalid type: {}, valid RL toolkits types are: {}".format(toolkit, list(RLToolkit))
+                f"Invalid type: {toolkit}, valid RL toolkits types are: {list(RLToolkit)}"
             )
 
     @classmethod
@@ -420,10 +430,9 @@ def _validate_images_args(cls, toolkit, toolkit_version, framework, image_uri):
             if not framework:
                 not_found_args.append("framework")
             if not_found_args:
+                not_found_args_joined = "`, `".join(not_found_args)
                 raise AttributeError(
-                    "Please provide `{}` or `image_uri` parameter.".format(
-                        "`, `".join(not_found_args)
-                    )
+                    f"Provide `{not_found_args_joined}` or `image_uri` parameter."
                 )
         else:
             found_args = []
@@ -455,9 +464,8 @@ def _validate_toolkit_support(cls, toolkit, toolkit_version, framework):
         """Placeholder docstring."""
         if not cls._is_combination_supported(toolkit, toolkit_version, framework):
             raise AttributeError(
-                "Provided `{}-{}` and `{}` combination is not supported.".format(
-                    toolkit, toolkit_version, framework
-                )
+                f"Provided `{toolkit}-{toolkit_version}` and `{framework}` combination is"
+                " not supported."
             )
 
     def _image_framework(self):
@@ -487,7 +495,7 @@ def default_metric_definitions(cls, toolkit):
             float_regex = "[-+]?[0-9]*[.]?[0-9]+([eE][-+]?[0-9]+)?"  # noqa: W605, E501
 
             return [
-                {"Name": "episode_reward_mean", "Regex": "episode_reward_mean: (%s)" % float_regex},
-                {"Name": "episode_reward_max", "Regex": "episode_reward_max: (%s)" % float_regex},
+                {"Name": "episode_reward_mean", "Regex": f"episode_reward_mean: ({float_regex})"},
+                {"Name": "episode_reward_max", "Regex": f"episode_reward_max: ({float_regex})"},
             ]
-        raise ValueError("An unknown RLToolkit enum was passed in. toolkit: {}".format(toolkit))
+        raise ValueError(f"An unknown RLToolkit enum was passed in. toolkit: {toolkit}")

tests/unit/test_rl.py

@@ -601,7 +601,7 @@ def test_missing_required_parameters(sagemaker_session):
             instance_type=INSTANCE_TYPE,
         )
     assert (
-        "Please provide `toolkit`, `toolkit_version`, `framework`" + " or `image_uri` parameter."
+        "Provide `toolkit`, `toolkit_version`, `framework`" + " or `image_uri` parameter."
         in str(e.value)
     )