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Dipankar Patrodpatro
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Address PR feedback
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doc/overview.rst

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

src/sagemaker/remote_function/client.py

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

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