class_docstr: Configuration object passed in when deploying models to Amazon SageMaker Endpoints.
  
  This object specifies configuration related to serverless endpoint. Use this configuration
  when trying to create serverless endpoint and make serverless inference
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docstr: Initialize a ServerlessInferenceConfig object for serverless inference configuration.
  
  Args:
      memory_size_in_mb (int): Optional. The memory size of your serverless endpoint.
          Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB,
          5120 MB, or 6144 MB. If no value is provided, Amazon SageMaker will choose
          the default value for you. (Default: 2048)
      max_concurrency (int): Optional. The maximum number of concurrent invocations
          your serverless endpoint can process. If no value is provided, Amazon
          SageMaker will choose the default value for you. (Default: 5)
      provisioned_concurrency (int): Optional. The provisioned concurrency of your
          serverless endpoint. If no value is provided, Amazon SageMaker will not
          apply provisioned concucrrency to your Serverless endpoint. (Default: None)
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code: def __init__(
      self,
      memory_size_in_mb: int = 2048,
      max_concurrency: int = 5,
      provisioned_concurrency: Optional[int] = None,
  ):
      """Initialize a ServerlessInferenceConfig object for serverless inference configuration.
  
      Args:
          memory_size_in_mb (int): Optional. The memory size of your serverless endpoint.
              Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB,
              5120 MB, or 6144 MB. If no value is provided, Amazon SageMaker will choose
              the default value for you. (Default: 2048)
          max_concurrency (int): Optional. The maximum number of concurrent invocations
              your serverless endpoint can process. If no value is provided, Amazon
              SageMaker will choose the default value for you. (Default: 5)
          provisioned_concurrency (int): Optional. The provisioned concurrency of your
              serverless endpoint. If no value is provided, Amazon SageMaker will not
              apply provisioned concucrrency to your Serverless endpoint. (Default: None)
      """
      self.memory_size_in_mb = memory_size_in_mb
      self.max_concurrency = max_concurrency
      self.provisioned_concurrency = provisioned_concurrency
  
imports: from __future__ import print_function, absolute_import
  from typing import Optional
label_desc: Use image node_id 1 to create a new ServerlessInferenceConfig object from inherited base classes: object with example: obj = ServerlessInferenceConfig(memory_size_in_mb, max_concurrency, provisioned_concurrency)