doc: update docstrings to comply with PEP257

Author: ahsan-z-khan

src/sagemaker/session.py

@@ -462,8 +462,6 @@ def train(  # noqa: C901
         debugger_hook_config=None,
         tensorboard_output_config=None,
         enable_sagemaker_metrics=None,
-        profiler_rule_configs=None,
-        profiler_config=None,
     ):
         """Create an Amazon SageMaker training job.
 
@@ -533,9 +531,6 @@ def train(  # noqa: C901
                 Series. For more information see:
                 https://docs.aws.amazon.com/sagemaker/latest/dg/API_AlgorithmSpecification.html#SageMaker-Type-AlgorithmSpecification-EnableSageMakerMetricsTimeSeries
                 (default: ``None``).
-            profiler_rule_configs (list[dict]): A list of profiler rule configurations.
-            profiler_config (dict): Configuration for how profiling information is emitted
-                with SageMaker Profiler. (default: ``None``).
 
         Returns:
             str: ARN of the training job, if it is created.
@@ -565,8 +560,6 @@ def train(  # noqa: C901
             debugger_hook_config=debugger_hook_config,
             tensorboard_output_config=tensorboard_output_config,
             enable_sagemaker_metrics=enable_sagemaker_metrics,
-            profiler_rule_configs=profiler_rule_configs,
-            profiler_config=profiler_config,
         )
         LOGGER.info("Creating training-job with name: %s", job_name)
         LOGGER.debug("train request: %s", json.dumps(train_request, indent=4))
@@ -597,8 +590,6 @@ def _get_train_request(  # noqa: C901
         debugger_hook_config=None,
         tensorboard_output_config=None,
         enable_sagemaker_metrics=None,
-        profiler_rule_configs=None,
-        profiler_config=None,
     ):
         """Constructs a request compatible for creating an Amazon SageMaker training job.
 
@@ -668,9 +659,6 @@ def _get_train_request(  # noqa: C901
                 Series. For more information see:
                 https://docs.aws.amazon.com/sagemaker/latest/dg/API_AlgorithmSpecification.html#SageMaker-Type-AlgorithmSpecification-EnableSageMakerMetricsTimeSeries
                 (default: ``None``).
-            profiler_rule_configs (list[dict]): A list of profiler rule configurations.
-            profiler_config(dict): Configuration for how profiling information is emitted with
-                SageMaker Profiler. (default: ``None``).
 
         Returns:
             Dict: a training request dict
@@ -746,66 +734,8 @@ def _get_train_request(  # noqa: C901
         if tensorboard_output_config is not None:
             train_request["TensorBoardOutputConfig"] = tensorboard_output_config
 
-        if profiler_rule_configs is not None:
-            train_request["ProfilerRuleConfigurations"] = profiler_rule_configs
-
-        if profiler_config is not None:
-            train_request["ProfilerConfig"] = profiler_config
-
         return train_request
 
-    def update_training_job(
-        self,
-        job_name,
-        profiler_rule_configs=None,
-        profiler_config=None,
-    ):
-        """Calls the UpdateTrainingJob API for the given job name and returns the response.
-
-        Args:
-            job_name (str): Name of the training job being updated.
-            profiler_rule_configs (list): List of profiler rule configurations. (default: ``None``).
-            profiler_config(dict): Configuration for how profiling information is emitted with
-                SageMaker Profiler. (default: ``None``).
-        """
-        update_training_job_request = self._get_update_training_job_request(
-            job_name=job_name,
-            profiler_rule_configs=profiler_rule_configs,
-            profiler_config=profiler_config,
-        )
-        LOGGER.info("Updating training job with name %s", job_name)
-        LOGGER.debug("Update request: %s", json.dumps(update_training_job_request, indent=4))
-        self.sagemaker_client.update_training_job(**update_training_job_request)
-
-    def _get_update_training_job_request(
-        self,
-        job_name,
-        profiler_rule_configs=None,
-        profiler_config=None,
-    ):
-        """Constructs a request compatible for updateing an Amazon SageMaker training job.
-
-        Args:
-            job_name (str): Name of the training job being updated.
-            profiler_rule_configs (list): List of profiler rule configurations. (default: ``None``).
-            profiler_config(dict): Configuration for how profiling information is emitted with
-                SageMaker Profiler. (default: ``None``).
-
-        Returns:
-            Dict: an update training request dict
-        """
-        update_training_job_request = {
-            "TrainingJobName": job_name,
-        }
-
-        if profiler_rule_configs is not None:
-            update_training_job_request["ProfilerRuleConfigurations"] = profiler_rule_configs
-
-        if profiler_config is not None:
-            update_training_job_request["ProfilerConfig"] = profiler_config
-
-        return update_training_job_request
-
     def process(
         self,
         inputs,
@@ -1802,48 +1732,6 @@ def compile_model(
         LOGGER.info("Creating compilation-job with name: %s", job_name)
         self.sagemaker_client.create_compilation_job(**compilation_job_request)
 
-    def package_model_for_edge(
-        self,
-        output_model_config,
-        role,
-        job_name,
-        compilation_job_name,
-        model_name,
-        model_version,
-        resource_key,
-        tags,
-    ):
-        """Create an Amazon SageMaker Edge packaging job.
-
-        Args:
-            output_model_config (dict): Identifies the Amazon S3 location where you want Amazon
-                SageMaker Edge to save the results of edge packaging job
-            role (str): An AWS IAM role (either name or full ARN). The Amazon SageMaker Edge
-                edge packaging jobs use this role to access model artifacts. You must grant
-                sufficient permissions to this role.
-            job_name (str): Name of the edge packaging job being created.
-            compilation_job_name (str): Name of the compilation job being created.
-            resource_key (str): KMS key to encrypt the disk used to package the job
-            tags (list[dict]): List of tags for labeling a compile model job. For more, see
-                https://docs.aws.amazon.com/sagemaker/latest/dg/API_Tag.html.
-        """
-        edge_packaging_job_request = {
-            "OutputConfig": output_model_config,
-            "RoleArn": role,
-            "ModelName": model_name,
-            "ModelVersion": model_version,
-            "EdgePackagingJobName": job_name,
-            "CompilationJobName": compilation_job_name,
-        }
-
-        if tags is not None:
-            edge_packaging_job_request["Tags"] = tags
-        if resource_key is not None:
-            edge_packaging_job_request["ResourceKey"] = (resource_key,)
-
-        LOGGER.info("Creating edge-packaging-job with name: %s", job_name)
-        self.sagemaker_client.create_edge_packaging_job(**edge_packaging_job_request)
-
     def tune(  # noqa: C901
         self,
         job_name,
@@ -3150,23 +3038,6 @@ def wait_for_compilation_job(self, job, poll=5):
         self._check_job_status(job, desc, "CompilationJobStatus")
         return desc
 
-    def wait_for_edge_packaging_job(self, job, poll=5):
-        """Wait for an Amazon SageMaker Edge packaging job to complete.
-
-        Args:
-            job (str): Name of the edge packaging job to wait for.
-            poll (int): Polling interval in seconds (default: 5).
-
-        Returns:
-            (dict): Return value from the ``DescribeEdgePackagingJob`` API.
-
-        Raises:
-            exceptions.UnexpectedStatusException: If the compilation job fails.
-        """
-        desc = _wait_until(lambda: _edge_packaging_job_status(self.sagemaker_client, job), poll)
-        self._check_job_status(job, desc, "EdgePackagingJobStatus")
-        return desc
-
     def wait_for_tuning_job(self, job, poll=5):
         """Wait for an Amazon SageMaker hyperparameter tuning job to complete.
 
@@ -3250,13 +3121,7 @@ def _check_job_status(self, job, desc, status_key_name):
         # If the status is capital case, then convert it to Camel case
         status = _STATUS_CODE_TABLE.get(status, status)
 
-        if status == "Stopped":
-            LOGGER.warning(
-                "Job ended with status 'Stopped' rather than 'Completed'. "
-                "This could mean the job timed out or stopped early for some other reason: "
-                "Consider checking whether it completed as you expect."
-            )
-        elif status != "Completed":
+        if status not in ("Completed", "Stopped"):
             reason = desc.get("FailureReason", "(No reason provided)")
             job_type = status_key_name.replace("JobStatus", " job")
             raise exceptions.UnexpectedStatusException(
@@ -3618,7 +3483,6 @@ def logs_for_job(  # noqa: C901 - suppress complexity warning for this method
         last_describe_job_call = time.time()
         last_description = description
         last_debug_rule_statuses = None
-        last_profiler_rule_statuses = None
 
         while True:
             _flush_log_streams(
@@ -3657,32 +3521,22 @@ def logs_for_job(  # noqa: C901 - suppress complexity warning for this method
                 debug_rule_statuses = description.get("DebugRuleEvaluationStatuses", {})
                 if (
                     debug_rule_statuses
-                    and _rule_statuses_changed(debug_rule_statuses, last_debug_rule_statuses)
+                    and _debug_rule_statuses_changed(debug_rule_statuses, last_debug_rule_statuses)
                     and (log_type in {"All", "Rules"})
                 ):
+                    print()
+                    print("********* Debugger Rule Status *********")
+                    print("*")
                     for status in debug_rule_statuses:
-                        rule_log = (
-                            f"{status['RuleConfigurationName']}: {status['RuleEvaluationStatus']}"
+                        rule_log = "* {:>18}: {:<18}".format(
+                            status["RuleConfigurationName"], status["RuleEvaluationStatus"]
                         )
                         print(rule_log)
+                    print("*")
+                    print("*" * 40)
 
                     last_debug_rule_statuses = debug_rule_statuses
 
-                # Print prettified logs related to the status of SageMaker Profiler rules.
-                profiler_rule_statuses = description.get("ProfilerRuleEvaluationStatuses", {})
-                if (
-                    profiler_rule_statuses
-                    and _rule_statuses_changed(profiler_rule_statuses, last_profiler_rule_statuses)
-                    and (log_type in {"All", "Rules"})
-                ):
-                    for status in profiler_rule_statuses:
-                        rule_log = (
-                            f"{status['RuleConfigurationName']}: {status['RuleEvaluationStatus']}"
-                        )
-                        print(rule_log)
-
-                    last_profiler_rule_statuses = profiler_rule_statuses
-
         if wait:
             self._check_job_status(job_name, description, "TrainingJobStatus")
             if dot:
@@ -4245,38 +4099,6 @@ def _processing_job_status(sagemaker_client, job_name):
     return desc
 
 
-def _edge_packaging_job_status(sagemaker_client, job_name):
-    """Process the current status of a packaging job
-
-    Args:
-        sagemaker_client (boto3.client.sagemaker): a sagemaker client
-        job_name (str): the name of the job to inspec
-
-    Returns:
-        Dict: the status of the edge packaging job
-    """
-    package_status_codes = {
-        "Completed": "!",
-        "InProgress": ".",
-        "Failed": "*",
-        "Stopped": "s",
-        "Stopping": "_",
-    }
-    in_progress_statuses = ["InProgress", "Stopping", "Starting"]
-
-    desc = sagemaker_client.describe_edge_packaging_job(EdgePackagingJobName=job_name)
-    status = desc["EdgePackagingJobStatus"]
-
-    status = _STATUS_CODE_TABLE.get(status, status)
-    print(package_status_codes.get(status, "?"), end="")
-    sys.stdout.flush()
-
-    if status in in_progress_statuses:
-        return None
-
-    return desc
-
-
 def _compilation_job_status(sagemaker_client, job_name):
     """Placeholder docstring"""
     compile_status_codes = {
@@ -4454,8 +4276,8 @@ def _get_initial_job_state(description, status_key, wait):
     return LogState.TAILING if wait and not job_already_completed else LogState.COMPLETE
 
 
-def _rule_statuses_changed(current_statuses, last_statuses):
-    """Checks the rule evaluation statuses for SageMaker Debugger and Profiler rules."""
+def _debug_rule_statuses_changed(current_statuses, last_statuses):
+    """Checks the rule evaluation statuses for SageMaker Debugger rules."""
     if not last_statuses:
         return True