Source code for sagemaker.core.inference_config
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# Licensed under the Apache License, Version 2.0 (the "License"). You
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# the License is located at
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"""Configuration classes for SageMaker inference endpoints.
This module provides configuration classes for different types of SageMaker
inference endpoints including async, serverless, and resource requirements.
"""
from __future__ import print_function, absolute_import
from typing import Optional
[docs]
class AsyncInferenceConfig(object):
"""Configuration object for async inference endpoints.
This object specifies configuration related to async endpoint. Use this configuration
when trying to create async endpoint and make async inference.
"""
def __init__(
self,
output_path=None,
max_concurrent_invocations_per_instance=None,
kms_key_id=None,
notification_config=None,
failure_path=None,
):
"""Initialize an AsyncInferenceConfig object for async inference configuration.
Args:
output_path (str): Optional. The Amazon S3 location that endpoints upload
inference responses to. If no value is provided, Amazon SageMaker will
use default Amazon S3 Async Inference output path. (Default: None)
max_concurrent_invocations_per_instance (int): Optional. The maximum number of
concurrent requests sent by the SageMaker client to the model container. If
no value is provided, Amazon SageMaker will choose an optimal value for you.
(Default: None)
kms_key_id (str): Optional. The Amazon Web Services Key Management Service
(Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the
asynchronous inference output in Amazon S3. (Default: None)
failure_path (str): Optional. The Amazon S3 location that endpoints upload model
responses for failed requests. If no value is provided, Amazon SageMaker will
use default Amazon S3 Async Inference failure path. (Default: None)
notification_config (dict): Optional. Specifies the configuration for notifications
of inference results for asynchronous inference. Only one notification is generated
per invocation request (Default: None):
* success_topic (str): Amazon SNS topic to post a notification to when inference
completes successfully. If no topic is provided, no notification is sent on success.
The key in notification_config is 'SuccessTopic'.
* error_topic (str): Amazon SNS topic to post a notification to when inference
fails. If no topic is provided, no notification is sent on failure.
The key in notification_config is 'ErrorTopic'.
* include_inference_response_in (list): Optional. When provided the inference
response will be included in the notification topics. If not provided,
a notification will still be generated on success/error, but will not
contain the inference response.
Valid options are SUCCESS_NOTIFICATION_TOPIC, ERROR_NOTIFICATION_TOPIC
"""
self.output_path = output_path
self.max_concurrent_invocations_per_instance = max_concurrent_invocations_per_instance
self.kms_key_id = kms_key_id
self.notification_config = notification_config
self.failure_path = failure_path
def _to_request_dict(self):
"""Generates a request dictionary using the parameters provided to the class."""
request_dict = {
"OutputConfig": {
"S3OutputPath": self.output_path,
"S3FailurePath": self.failure_path,
},
}
if self.max_concurrent_invocations_per_instance:
request_dict["ClientConfig"] = {
"MaxConcurrentInvocationsPerInstance": self.max_concurrent_invocations_per_instance
}
if self.kms_key_id:
request_dict["OutputConfig"]["KmsKeyId"] = self.kms_key_id
if self.notification_config:
request_dict["OutputConfig"]["NotificationConfig"] = self.notification_config
return request_dict
[docs]
class ServerlessInferenceConfig(object):
"""Configuration object for serverless inference endpoints.
This object specifies configuration related to serverless endpoint. Use this configuration
when trying to create serverless endpoint and make serverless inference.
"""
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 concurrency 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
def _to_request_dict(self):
"""Generates a request dictionary using the parameters provided to the class."""
request_dict = {
"MemorySizeInMB": self.memory_size_in_mb,
"MaxConcurrency": self.max_concurrency,
}
if self.provisioned_concurrency is not None:
request_dict["ProvisionedConcurrency"] = self.provisioned_concurrency
return request_dict
# Re-export ResourceRequirements from its existing location in core
from sagemaker.core.resource_requirements import ResourceRequirements # noqa: F401, E402
__all__ = ["AsyncInferenceConfig", "ServerlessInferenceConfig", "ResourceRequirements"]