Address PR feedback

Author: Dipankar Patro

doc/overview.rst

@@ -2027,15 +2027,15 @@ set default values for. For the full schema, see ``sagemaker.config.config_schem
             Dependencies: 'path/to/requirements.txt'
             EnableInterContainerTrafficEncryption: true
             EnvironmentVariables: {'EnvVarKey': 'EnvVarValue'}
-            ImageUri: '366666666666.dkr.ecr.us-west-2.amazonaws.com/my-image:latest'
+            ImageUri: '555555555555.dkr.ecr.us-west-2.amazonaws.com/my-image:latest'
             IncludeLocalWorkDir: true
             InstanceType: 'ml.m5.large'
             JobCondaEnvironment: 'your_conda_env'
             PreExecutionCommands:
               - 'command_1'
               - 'command_2'
             PreExecutionScript: 'path/to/script.sh'
-            RoleArn: 'arn:aws:iam::366666666666:role/MyRole'
+            RoleArn: 'arn:aws:iam::555555555555:role/MyRole'
             S3KmsKeyId: 'yourkmskeyid'
             S3RootUri: 's3://my-bucket/my-project'
             VpcConfig:
@@ -2044,7 +2044,8 @@ set default values for. For the full schema, see ``sagemaker.config.config_schem
               Subnets:
                 - 'subnet-1234'
             Tags:
-              - {'Key': 'yourTagKey', 'Value': 'yourTagValue'}
+              - Key: 'tag_key'
+                Value: 'tag_value'
             VolumeKmsKeyId: 'yourkmskeyid'
 
 Configuration file locations
@@ -2440,7 +2441,7 @@ specifically the contents of ``'body': b'{...}`` .
 
    <TIMESTAMP> botocore.endpoint [DEBUG] Making request for OperationModel(name=<OPERATION_NAME>) with params: {'url_path': ...,
    'query_string': ..., 'method': 'POST', 'headers': {...}, 'body': b'{...}', 'url': 'https://api.sagemaker.us-west-2.amazonaws.com/',
-   'context': {...}}cd
+   'context': {...}}
 
 
 ************************************************************

src/sagemaker/remote_function/client.py

@@ -84,7 +84,7 @@ def remote(
 ):
     """Decorator for running the annotated function as a SageMaker training job.
 
-    This decorator wraps the annotated code and runs it is a new SageMaker job synchronously
+    This decorator wraps the annotated code and runs it as a new SageMaker job synchronously
     with the provided runtime settings.
 
     Unless mentioned otherwise, the decorator first looks up the value from the SageMaker
@@ -187,8 +187,7 @@ def remote(
         instance_count (int): The number of instance to use. Defaults to 1.
 
         instance_type (str): The Amazon Elastic Compute Cloud (EC2) instance type to use to run
-          the SageMaker job. Valid values include ml.c4.xlarge. If not provided, ValueError is
-          thrown.
+          the SageMaker job. e.g. ml.c4.xlarge. If not provided, ValueError is thrown.
 
         job_conda_env (str): The name of the conda environment to activate during job's runtime.
           Defaults to ``None``.
@@ -204,12 +203,12 @@ def remote(
           latency than over using SageMaker managed warm pools alone by caching the package source
           downloaded in the previous runs.
 
-        max_retry_attempts (int): The max number of times the job is retried after an on
-          ```InternalServerFailure``` Error. Defaults to 1.
+        max_retry_attempts (int): The max number of times the job is retried on
+          ```InternalServerFailure``` Error from SageMaker service. Defaults to 1.
 
         max_runtime_in_seconds (int): The upper limit in seconds to be used for training. After
           this specified amount of time, SageMaker terminates the job regardless of its current
-          status. The max_run_duration time defaults to 1 day or (86400 seconds).
+          status. Defaults to 1 day or (86400 seconds).
 
         role (str): The IAM role (either name or full ARN) used to run your SageMaker training
           job. Defaults to:
@@ -220,7 +219,7 @@ def remote(
 
         s3_kms_key (str): The key used to encrypt the input and output data. Default to ``None``.
 
-        s3_root_uri (str): The root S3 folder to which where the code archives and data are
+        s3_root_uri (str): The root S3 folder to which the code archives and data are
           uploaded to. Defaults to ``s3://<sagemaker-default-bucket>``.
 
         sagemaker_session (sagemaker.session.Session): The underlying SageMaker session to which
@@ -577,8 +576,7 @@ def __init__(
             instance_count (int): The number of instance to use. Defaults to 1.
 
             instance_type (str): The Amazon Elastic Compute Cloud (EC2) instance type to use to run
-              the SageMaker job. Valid values include ml.c4.xlarge. If not provided, ValueError is
-              thrown.
+              the SageMaker job. e.g. ml.c4.xlarge. If not provided, ValueError is thrown.
 
             job_conda_env (str): The name of the conda environment to activate during job's runtime.
               Defaults to ``None``.
@@ -596,12 +594,12 @@ def __init__(
 
             max_parallel_jobs (int): Maximum number of jobs that run in parallel. Defaults to 1.
 
-            max_retry_attempts (int): The max number of times the job is retried after an on
-              ```InternalServerFailure``` Error. Defaults to 1.
+            max_retry_attempts (int): The max number of times the job is retried on
+              ```InternalServerFailure``` Error from SageMaker service. Defaults to 1.
 
             max_runtime_in_seconds (int): The upper limit in seconds to be used for training. After
               this specified amount of time, SageMaker terminates the job regardless of its current
-              status. The max_run_duration time defaults to 1 day or (86400 seconds).
+              status. Defaults to 1 day or (86400 seconds).
 
             role (str): The IAM role (either name or full ARN) used to run your SageMaker training
               job. Defaults to:
@@ -613,7 +611,7 @@ def __init__(
             s3_kms_key (str): The key used to encrypt the input and output data.
               Default to ``None``.
 
-            s3_root_uri (str): The root S3 folder to which where the code archives and data are
+            s3_root_uri (str): The root S3 folder to which the code archives and data are
               uploaded to. Defaults to ``s3://<sagemaker-default-bucket>``.
 
             sagemaker_session (sagemaker.session.Session): The underlying SageMaker session to which
@@ -1011,7 +1009,7 @@ def wait(
         will block until the job is completed.
 
         Args:
-            timeout (int): Timeout in seconds to wait for until the job is to completed before it is
+            timeout (int): Timeout in seconds to wait for until the job is completed before it is
               stopped. Defaults to ``None``.
 
         Returns: None