From 6aa242c63cc92dfeca55902b8a641d4d919708ba Mon Sep 17 00:00:00 2001 From: aws-sdk-python-automation Date: Thu, 7 Nov 2024 19:24:23 +0000 Subject: [PATCH 1/3] Update to latest models --- .../api-change-autoscaling-52998.json | 5 + .../api-change-bedrockagent-80823.json | 5 + .../api-change-bedrockruntime-93186.json | 5 + .../api-change-cleanrooms-18465.json | 5 + .../api-change-cleanroomsml-37452.json | 5 + .../api-change-quicksight-96534.json | 5 + .../api-change-resourceexplorer2-90529.json | 5 + .../api-change-synthetics-53205.json | 5 + .../autoscaling/2011-01-01/service-2.json | 29 + .../bedrock-agent/2023-06-05/service-2.json | 800 ++- .../bedrock-runtime/2023-09-30/service-2.json | 77 +- .../data/cleanrooms/2022-02-17/service-2.json | 125 +- .../cleanroomsml/2023-09-06/paginators-1.json | 60 + .../cleanroomsml/2023-09-06/service-2.json | 5124 ++++++++++++++--- .../data/quicksight/2018-04-01/service-2.json | 71 + .../2022-07-28/paginators-1.json | 6 + .../2022-07-28/service-2.json | 158 +- .../data/synthetics/2017-10-11/service-2.json | 23 +- 18 files changed, 5815 insertions(+), 698 deletions(-) create mode 100644 .changes/next-release/api-change-autoscaling-52998.json create mode 100644 .changes/next-release/api-change-bedrockagent-80823.json create mode 100644 .changes/next-release/api-change-bedrockruntime-93186.json create mode 100644 .changes/next-release/api-change-cleanrooms-18465.json create mode 100644 .changes/next-release/api-change-cleanroomsml-37452.json create mode 100644 .changes/next-release/api-change-quicksight-96534.json create mode 100644 .changes/next-release/api-change-resourceexplorer2-90529.json create mode 100644 .changes/next-release/api-change-synthetics-53205.json diff --git a/.changes/next-release/api-change-autoscaling-52998.json b/.changes/next-release/api-change-autoscaling-52998.json new file mode 100644 index 0000000000..1560b4a7f1 --- /dev/null +++ b/.changes/next-release/api-change-autoscaling-52998.json @@ -0,0 +1,5 @@ +{ + "type": "api-change", + "category": "``autoscaling``", + "description": "Auto Scaling groups now support the ability to strictly balance instances across Availability Zones by configuring the AvailabilityZoneDistribution parameter. If balanced-only is configured for a group, launches will always be attempted in the under scaled Availability Zone even if it is unhealthy." +} diff --git a/.changes/next-release/api-change-bedrockagent-80823.json b/.changes/next-release/api-change-bedrockagent-80823.json new file mode 100644 index 0000000000..d0775ea205 --- /dev/null +++ b/.changes/next-release/api-change-bedrockagent-80823.json @@ -0,0 +1,5 @@ +{ + "type": "api-change", + "category": "``bedrock-agent``", + "description": "Add prompt support for chat template configuration and agent generative AI resource. Add support for configuring an optional guardrail in Prompt and Knowledge Base nodes in Prompt Flows. Add API to validate flow definition" +} diff --git a/.changes/next-release/api-change-bedrockruntime-93186.json b/.changes/next-release/api-change-bedrockruntime-93186.json new file mode 100644 index 0000000000..12bce9d7f6 --- /dev/null +++ b/.changes/next-release/api-change-bedrockruntime-93186.json @@ -0,0 +1,5 @@ +{ + "type": "api-change", + "category": "``bedrock-runtime``", + "description": "Add Prompt management support to Bedrock runtime APIs: Converse, ConverseStream, InvokeModel, InvokeModelWithStreamingResponse" +} diff --git a/.changes/next-release/api-change-cleanrooms-18465.json b/.changes/next-release/api-change-cleanrooms-18465.json new file mode 100644 index 0000000000..3fba7345b7 --- /dev/null +++ b/.changes/next-release/api-change-cleanrooms-18465.json @@ -0,0 +1,5 @@ +{ + "type": "api-change", + "category": "``cleanrooms``", + "description": "This release introduces support for Custom Models in AWS Clean Rooms ML." +} diff --git a/.changes/next-release/api-change-cleanroomsml-37452.json b/.changes/next-release/api-change-cleanroomsml-37452.json new file mode 100644 index 0000000000..e9c4ecd5bd --- /dev/null +++ b/.changes/next-release/api-change-cleanroomsml-37452.json @@ -0,0 +1,5 @@ +{ + "type": "api-change", + "category": "``cleanroomsml``", + "description": "This release introduces support for Custom Models in AWS Clean Rooms ML." +} diff --git a/.changes/next-release/api-change-quicksight-96534.json b/.changes/next-release/api-change-quicksight-96534.json new file mode 100644 index 0000000000..6d42d27e7b --- /dev/null +++ b/.changes/next-release/api-change-quicksight-96534.json @@ -0,0 +1,5 @@ +{ + "type": "api-change", + "category": "``quicksight``", + "description": "Add Client Credentials based OAuth support for Snowflake and Starburst" +} diff --git a/.changes/next-release/api-change-resourceexplorer2-90529.json b/.changes/next-release/api-change-resourceexplorer2-90529.json new file mode 100644 index 0000000000..86681e10cb --- /dev/null +++ b/.changes/next-release/api-change-resourceexplorer2-90529.json @@ -0,0 +1,5 @@ +{ + "type": "api-change", + "category": "``resource-explorer-2``", + "description": "Add GetManagedView, ListManagedViews APIs." +} diff --git a/.changes/next-release/api-change-synthetics-53205.json b/.changes/next-release/api-change-synthetics-53205.json new file mode 100644 index 0000000000..b5e96027f7 --- /dev/null +++ b/.changes/next-release/api-change-synthetics-53205.json @@ -0,0 +1,5 @@ +{ + "type": "api-change", + "category": "``synthetics``", + "description": "Add support to toggle if a canary will automatically delete provisioned canary resources such as Lambda functions and layers when a canary is deleted. This behavior can be controlled via the new ProvisionedResourceCleanup property exposed in the CreateCanary and UpdateCanary APIs." +} diff --git a/botocore/data/autoscaling/2011-01-01/service-2.json b/botocore/data/autoscaling/2011-01-01/service-2.json index 63edfab60a..21dca1bd31 100644 --- a/botocore/data/autoscaling/2011-01-01/service-2.json +++ b/botocore/data/autoscaling/2011-01-01/service-2.json @@ -1521,6 +1521,10 @@ "InstanceMaintenancePolicy":{ "shape":"InstanceMaintenancePolicy", "documentation":"

An instance maintenance policy.

" + }, + "AvailabilityZoneDistribution":{ + "shape":"AvailabilityZoneDistribution", + "documentation":"

The instance capacity distribution across Availability Zones.

" } }, "documentation":"

Describes an Auto Scaling group.

" @@ -1652,6 +1656,16 @@ "type":"list", "member":{"shape":"XmlStringMaxLen255"} }, + "AvailabilityZoneDistribution":{ + "type":"structure", + "members":{ + "CapacityDistributionStrategy":{ + "shape":"CapacityDistributionStrategy", + "documentation":"

If launches fail in an Availability Zone, the following strategies are available. The default is balanced-best-effort.

" + } + }, + "documentation":"

Describes an Availability Zone distribution.

" + }, "AvailabilityZones":{ "type":"list", "member":{"shape":"XmlStringMaxLen255"} @@ -1811,6 +1825,13 @@ } } }, + "CapacityDistributionStrategy":{ + "type":"string", + "enum":[ + "balanced-only", + "balanced-best-effort" + ] + }, "CapacityForecast":{ "type":"structure", "required":[ @@ -2011,6 +2032,10 @@ "InstanceMaintenancePolicy":{ "shape":"InstanceMaintenancePolicy", "documentation":"

An instance maintenance policy. For more information, see Set instance maintenance policy in the Amazon EC2 Auto Scaling User Guide.

" + }, + "AvailabilityZoneDistribution":{ + "shape":"AvailabilityZoneDistribution", + "documentation":"

The instance capacity distribution across Availability Zones.

" } } }, @@ -5657,6 +5682,10 @@ "InstanceMaintenancePolicy":{ "shape":"InstanceMaintenancePolicy", "documentation":"

An instance maintenance policy. For more information, see Set instance maintenance policy in the Amazon EC2 Auto Scaling User Guide.

" + }, + "AvailabilityZoneDistribution":{ + "shape":"AvailabilityZoneDistribution", + "documentation":"

The instance capacity distribution across Availability Zones.

" } } }, diff --git a/botocore/data/bedrock-agent/2023-06-05/service-2.json b/botocore/data/bedrock-agent/2023-06-05/service-2.json index c819c6330a..6a6ea6793e 100644 --- a/botocore/data/bedrock-agent/2023-06-05/service-2.json +++ b/botocore/data/bedrock-agent/2023-06-05/service-2.json @@ -1211,6 +1211,23 @@ ], "documentation":"

Modifies a prompt in your prompt library. Include both fields that you want to keep and fields that you want to replace. For more information, see Prompt management in Amazon Bedrock and Edit prompts in your prompt library in the Amazon Bedrock User Guide.

", "idempotent":true + }, + "ValidateFlowDefinition":{ + "name":"ValidateFlowDefinition", + "http":{ + "method":"POST", + "requestUri":"/flows/validate-definition", + "responseCode":200 + }, + "input":{"shape":"ValidateFlowDefinitionRequest"}, + "output":{"shape":"ValidateFlowDefinitionResponse"}, + "errors":[ + {"shape":"ThrottlingException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ValidationException"}, + {"shape":"InternalServerException"} + ], + "documentation":"

Validates the definition of a flow.

" } }, "shapes":{ @@ -1943,6 +1960,12 @@ }, "documentation":"

Contains details about a version of an agent.

" }, + "AnyToolChoice":{ + "type":"structure", + "members":{ + }, + "documentation":"

Defines tools, at least one of which must be requested by the model. No text is generated but the results of tool use are sent back to the model to help generate a response. For more information, see Use a tool to complete an Amazon Bedrock model response.

" + }, "AssociateAgentKnowledgeBaseRequest":{ "type":"structure", "required":[ @@ -1988,6 +2011,12 @@ } } }, + "AutoToolChoice":{ + "type":"structure", + "members":{ + }, + "documentation":"

Defines tools. The model automatically decides whether to call a tool or to generate text instead. For more information, see Use a tool to complete an Amazon Bedrock model response.

" + }, "BasePromptTemplate":{ "type":"string", "max":100000, @@ -2041,6 +2070,30 @@ "min":12, "pattern":"^[0-9]{12}$" }, + "ChatPromptTemplateConfiguration":{ + "type":"structure", + "required":["messages"], + "members":{ + "inputVariables":{ + "shape":"PromptInputVariablesList", + "documentation":"

An array of the variables in the prompt template.

" + }, + "messages":{ + "shape":"Messages", + "documentation":"

Contains messages in the chat for the prompt.

" + }, + "system":{ + "shape":"SystemContentBlocks", + "documentation":"

Contains system prompts to provide context to the model or to describe how it should behave.

" + }, + "toolConfiguration":{ + "shape":"ToolConfiguration", + "documentation":"

Configuration information for the tools that the model can use when generating a response.

" + } + }, + "documentation":"

Contains configurations to use a prompt in a conversational format. For more information, see Create a prompt using Prompt management.

", + "sensitive":true + }, "ChunkingConfiguration":{ "type":"structure", "required":["chunkingStrategy"], @@ -2178,6 +2231,29 @@ }, "documentation":"

The endpoint information to connect to your Confluence data source.

" }, + "ContentBlock":{ + "type":"structure", + "members":{ + "text":{ + "shape":"String", + "documentation":"

The text in the message.

" + } + }, + "documentation":"

Contains the content for the message you pass to, or receive from a model. For more information, see Create a prompt using Prompt management.

", + "sensitive":true, + "union":true + }, + "ContentBlocks":{ + "type":"list", + "member":{"shape":"ContentBlock"} + }, + "ConversationRole":{ + "type":"string", + "enum":[ + "user", + "assistant" + ] + }, "CrawlFilterConfiguration":{ "type":"structure", "required":["type"], @@ -2928,6 +3004,17 @@ }, "documentation":"

Settings for customizing steps in the data source content ingestion pipeline.

You can configure the data source to process documents with a Lambda function after they are parsed and converted into chunks. When you add a post-chunking transformation, the service stores chunked documents in an S3 bucket and invokes a Lambda function to process them.

To process chunked documents with a Lambda function, define an S3 bucket path for input and output objects, and a transformation that specifies the Lambda function to invoke. You can use the Lambda function to customize how chunks are split, and the metadata for each chunk.

" }, + "CyclicConnectionFlowValidationDetails":{ + "type":"structure", + "required":["connection"], + "members":{ + "connection":{ + "shape":"FlowConnectionName", + "documentation":"

The name of the connection that causes the cycle in the flow.

" + } + }, + "documentation":"

Details about a cyclic connection detected in the flow.

" + }, "DataDeletionPolicy":{ "type":"string", "enum":[ @@ -3528,6 +3615,42 @@ "min":5, "pattern":"^DRAFT$" }, + "DuplicateConditionExpressionFlowValidationDetails":{ + "type":"structure", + "required":[ + "expression", + "node" + ], + "members":{ + "expression":{ + "shape":"FlowConditionExpression", + "documentation":"

The duplicated condition expression.

" + }, + "node":{ + "shape":"FlowNodeName", + "documentation":"

The name of the node containing the duplicate condition expressions.

" + } + }, + "documentation":"

Details about duplicate condition expressions found in a condition node.

" + }, + "DuplicateConnectionsFlowValidationDetails":{ + "type":"structure", + "required":[ + "source", + "target" + ], + "members":{ + "source":{ + "shape":"FlowNodeName", + "documentation":"

The name of the source node where the duplicate connection starts.

" + }, + "target":{ + "shape":"FlowNodeName", + "documentation":"

The name of the target node where the duplicate connection ends.

" + } + }, + "documentation":"

Details about duplicate connections found between two nodes in the flow.

" + }, "EmbeddingModelConfiguration":{ "type":"structure", "members":{ @@ -3544,6 +3667,11 @@ "max":1, "min":1 }, + "ErrorMessage":{ + "type":"string", + "max":2048, + "min":0 + }, "FailureReason":{ "type":"string", "max":2048, @@ -4114,6 +4242,10 @@ "severity" ], "members":{ + "details":{ + "shape":"FlowValidationDetails", + "documentation":"

Specific details about the validation issue encountered in the flow.

" + }, "message":{ "shape":"NonBlankString", "documentation":"

A message describing the validation error.

" @@ -4121,10 +4253,121 @@ "severity":{ "shape":"FlowValidationSeverity", "documentation":"

The severity of the issue described in the message.

" + }, + "type":{ + "shape":"FlowValidationType", + "documentation":"

The type of validation issue encountered in the flow.

" } }, "documentation":"

Contains information about validation of the flow.

This data type is used in the following API operations:

" }, + "FlowValidationDetails":{ + "type":"structure", + "members":{ + "cyclicConnection":{ + "shape":"CyclicConnectionFlowValidationDetails", + "documentation":"

Details about a cyclic connection in the flow.

" + }, + "duplicateConditionExpression":{ + "shape":"DuplicateConditionExpressionFlowValidationDetails", + "documentation":"

Details about duplicate condition expressions in a node.

" + }, + "duplicateConnections":{ + "shape":"DuplicateConnectionsFlowValidationDetails", + "documentation":"

Details about duplicate connections between nodes.

" + }, + "incompatibleConnectionDataType":{ + "shape":"IncompatibleConnectionDataTypeFlowValidationDetails", + "documentation":"

Details about incompatible data types in a connection.

" + }, + "malformedConditionExpression":{ + "shape":"MalformedConditionExpressionFlowValidationDetails", + "documentation":"

Details about a malformed condition expression in a node.

" + }, + "malformedNodeInputExpression":{ + "shape":"MalformedNodeInputExpressionFlowValidationDetails", + "documentation":"

Details about a malformed input expression in a node.

" + }, + "mismatchedNodeInputType":{ + "shape":"MismatchedNodeInputTypeFlowValidationDetails", + "documentation":"

Details about mismatched input data types in a node.

" + }, + "mismatchedNodeOutputType":{ + "shape":"MismatchedNodeOutputTypeFlowValidationDetails", + "documentation":"

Details about mismatched output data types in a node.

" + }, + "missingConnectionConfiguration":{ + "shape":"MissingConnectionConfigurationFlowValidationDetails", + "documentation":"

Details about missing configuration for a connection.

" + }, + "missingDefaultCondition":{ + "shape":"MissingDefaultConditionFlowValidationDetails", + "documentation":"

Details about a missing default condition in a conditional node.

" + }, + "missingEndingNodes":{ + "shape":"MissingEndingNodesFlowValidationDetails", + "documentation":"

Details about missing ending nodes in the flow.

" + }, + "missingNodeConfiguration":{ + "shape":"MissingNodeConfigurationFlowValidationDetails", + "documentation":"

Details about missing configuration for a node.

" + }, + "missingNodeInput":{ + "shape":"MissingNodeInputFlowValidationDetails", + "documentation":"

Details about a missing required input in a node.

" + }, + "missingNodeOutput":{ + "shape":"MissingNodeOutputFlowValidationDetails", + "documentation":"

Details about a missing required output in a node.

" + }, + "missingStartingNodes":{ + "shape":"MissingStartingNodesFlowValidationDetails", + "documentation":"

Details about missing starting nodes in the flow.

" + }, + "multipleNodeInputConnections":{ + "shape":"MultipleNodeInputConnectionsFlowValidationDetails", + "documentation":"

Details about multiple connections to a single node input.

" + }, + "unfulfilledNodeInput":{ + "shape":"UnfulfilledNodeInputFlowValidationDetails", + "documentation":"

Details about an unfulfilled node input with no valid connections.

" + }, + "unknownConnectionCondition":{ + "shape":"UnknownConnectionConditionFlowValidationDetails", + "documentation":"

Details about an unknown condition for a connection.

" + }, + "unknownConnectionSource":{ + "shape":"UnknownConnectionSourceFlowValidationDetails", + "documentation":"

Details about an unknown source node for a connection.

" + }, + "unknownConnectionSourceOutput":{ + "shape":"UnknownConnectionSourceOutputFlowValidationDetails", + "documentation":"

Details about an unknown source output for a connection.

" + }, + "unknownConnectionTarget":{ + "shape":"UnknownConnectionTargetFlowValidationDetails", + "documentation":"

Details about an unknown target node for a connection.

" + }, + "unknownConnectionTargetInput":{ + "shape":"UnknownConnectionTargetInputFlowValidationDetails", + "documentation":"

Details about an unknown target input for a connection.

" + }, + "unreachableNode":{ + "shape":"UnreachableNodeFlowValidationDetails", + "documentation":"

Details about an unreachable node in the flow.

" + }, + "unsatisfiedConnectionConditions":{ + "shape":"UnsatisfiedConnectionConditionsFlowValidationDetails", + "documentation":"

Details about unsatisfied conditions for a connection.

" + }, + "unspecified":{ + "shape":"UnspecifiedFlowValidationDetails", + "documentation":"

Details about an unspecified validation.

" + } + }, + "documentation":"

A union type containing various possible validation issues in the flow.

", + "union":true + }, "FlowValidationSeverity":{ "type":"string", "enum":[ @@ -4132,6 +4375,36 @@ "Error" ] }, + "FlowValidationType":{ + "type":"string", + "enum":[ + "CyclicConnection", + "DuplicateConnections", + "DuplicateConditionExpression", + "UnreachableNode", + "UnknownConnectionSource", + "UnknownConnectionSourceOutput", + "UnknownConnectionTarget", + "UnknownConnectionTargetInput", + "UnknownConnectionCondition", + "MalformedConditionExpression", + "MalformedNodeInputExpression", + "MismatchedNodeInputType", + "MismatchedNodeOutputType", + "IncompatibleConnectionDataType", + "MissingConnectionConfiguration", + "MissingDefaultCondition", + "MissingEndingNodes", + "MissingNodeConfiguration", + "MissingNodeInput", + "MissingNodeOutput", + "MissingStartingNodes", + "MultipleNodeInputConnections", + "UnfulfilledNodeInput", + "UnsatisfiedConnectionConditions", + "Unspecified" + ] + }, "FlowValidations":{ "type":"list", "member":{"shape":"FlowValidation"}, @@ -4771,7 +5044,7 @@ "documentation":"

The version of the guardrail.

" } }, - "documentation":"

Details about the guardrail associated with an agent.

" + "documentation":"

Details about a guardrail associated with a resource.

" }, "GuardrailIdentifier":{ "type":"string", @@ -4837,6 +5110,17 @@ "type":"string", "pattern":"^[0-9a-zA-Z]{10}$" }, + "IncompatibleConnectionDataTypeFlowValidationDetails":{ + "type":"structure", + "required":["connection"], + "members":{ + "connection":{ + "shape":"FlowConnectionName", + "documentation":"

The name of the connection with incompatible data types.

" + } + }, + "documentation":"

Details about incompatible data types in a connection between nodes.

" + }, "InferenceConfiguration":{ "type":"structure", "members":{ @@ -5213,6 +5497,10 @@ "type":"structure", "required":["knowledgeBaseId"], "members":{ + "guardrailConfiguration":{ + "shape":"GuardrailConfiguration", + "documentation":"

Contains configurations for a guardrail to apply during query and response generation for the knowledge base in this configuration.

" + }, "knowledgeBaseId":{ "shape":"KnowledgeBaseId", "documentation":"

The unique identifier of the knowledge base to query.

" @@ -5232,10 +5520,9 @@ }, "KnowledgeBaseModelIdentifier":{ "type":"string", - "documentation":"

ARN or Id of a Bedrock Foundational Model or Inference Profile, or the ARN of a jumpstart model or imported model, or a provisioned throughput ARN for custom models.

", "max":2048, "min":1, - "pattern":"^(arn:aws(-[^:]+)?:bedrock:[a-z0-9-]{1,20}:(([0-9]{12}:custom-model/[a-z0-9-]{1,63}[.]{1}[a-z0-9-]{1,63}/[a-z0-9]{12})|(:foundation-model/[a-z0-9-]{1,63}[.]{1}[a-z0-9-]{1,63}([.:]?[a-z0-9-]{1,63}))|([0-9]{12}:imported-model/[a-z0-9]{12})|([0-9]{12}:provisioned-model/[a-z0-9]{12})))|([a-z0-9-]{1,63}[.]{1}[a-z0-9-]{1,63}([.:]?[a-z0-9-]{1,63}))|(([0-9a-zA-Z][_-]?)+)|(arn:aws(|-us-gov|-cn|-iso|-iso-b):bedrock:(|[0-9a-z-]{1,20}):(|[0-9]{12}):(inference-profile|application-inference-profile)/[a-zA-Z0-9-:.]+)|([a-zA-Z0-9-:.]+)$" + "pattern":"^(arn:aws(-[^:]{1,12})?:(bedrock|sagemaker):[a-z0-9-]{1,20}:([0-9]{12})?:([a-z-]+/)?)?([a-zA-Z0-9.-]{1,63}){0,2}(([:][a-z0-9-]{1,63}){0,2})?(/[a-z0-9]{1,12})?$" }, "KnowledgeBaseRoleArn":{ "type":"string", @@ -5815,6 +6102,52 @@ } } }, + "MalformedConditionExpressionFlowValidationDetails":{ + "type":"structure", + "required":[ + "cause", + "condition", + "node" + ], + "members":{ + "cause":{ + "shape":"ErrorMessage", + "documentation":"

The error message describing why the condition expression is malformed.

" + }, + "condition":{ + "shape":"FlowConditionName", + "documentation":"

The name of the malformed condition.

" + }, + "node":{ + "shape":"FlowNodeName", + "documentation":"

The name of the node containing the malformed condition expression.

" + } + }, + "documentation":"

Details about a malformed condition expression in a node.

" + }, + "MalformedNodeInputExpressionFlowValidationDetails":{ + "type":"structure", + "required":[ + "cause", + "input", + "node" + ], + "members":{ + "cause":{ + "shape":"ErrorMessage", + "documentation":"

The error message describing why the input expression is malformed.

" + }, + "input":{ + "shape":"FlowNodeInputName", + "documentation":"

The name of the input with the malformed expression.

" + }, + "node":{ + "shape":"FlowNodeName", + "documentation":"

The name of the node containing the malformed input expression.

" + } + }, + "documentation":"

Details about a malformed input expression in a node.

" + }, "MaxResults":{ "type":"integer", "box":true, @@ -5846,15 +6179,163 @@ "type":"string", "enum":["SESSION_SUMMARY"] }, + "Message":{ + "type":"structure", + "required":[ + "content", + "role" + ], + "members":{ + "content":{ + "shape":"ContentBlocks", + "documentation":"

The content in the message.

" + }, + "role":{ + "shape":"ConversationRole", + "documentation":"

The role that the message belongs to.

" + } + }, + "documentation":"

A message input or response from a model. For more information, see Create a prompt using Prompt management.

" + }, + "Messages":{ + "type":"list", + "member":{"shape":"Message"} + }, "Microsoft365TenantId":{ "type":"string", "max":36, "min":36, "pattern":"^[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}$" }, + "MismatchedNodeInputTypeFlowValidationDetails":{ + "type":"structure", + "required":[ + "expectedType", + "input", + "node" + ], + "members":{ + "expectedType":{ + "shape":"FlowNodeIODataType", + "documentation":"

The expected data type for the node input.

" + }, + "input":{ + "shape":"FlowNodeInputName", + "documentation":"

The name of the input with the mismatched data type.

" + }, + "node":{ + "shape":"FlowNodeName", + "documentation":"

The name of the node containing the input with the mismatched data type.

" + } + }, + "documentation":"

Details about mismatched input data types in a node.

" + }, + "MismatchedNodeOutputTypeFlowValidationDetails":{ + "type":"structure", + "required":[ + "expectedType", + "node", + "output" + ], + "members":{ + "expectedType":{ + "shape":"FlowNodeIODataType", + "documentation":"

The expected data type for the node output.

" + }, + "node":{ + "shape":"FlowNodeName", + "documentation":"

The name of the node containing the output with the mismatched data type.

" + }, + "output":{ + "shape":"FlowNodeOutputName", + "documentation":"

The name of the output with the mismatched data type.

" + } + }, + "documentation":"

Details about mismatched output data types in a node.

" + }, + "MissingConnectionConfigurationFlowValidationDetails":{ + "type":"structure", + "required":["connection"], + "members":{ + "connection":{ + "shape":"FlowConnectionName", + "documentation":"

The name of the connection missing configuration.

" + } + }, + "documentation":"

Details about a connection missing required configuration.

" + }, + "MissingDefaultConditionFlowValidationDetails":{ + "type":"structure", + "required":["node"], + "members":{ + "node":{ + "shape":"FlowNodeName", + "documentation":"

The name of the node missing the default condition.

" + } + }, + "documentation":"

Details about a missing default condition in a conditional node.

" + }, + "MissingEndingNodesFlowValidationDetails":{ + "type":"structure", + "members":{ + }, + "documentation":"

Details about missing ending nodes (such as FlowOutputNode) in the flow.

" + }, + "MissingNodeConfigurationFlowValidationDetails":{ + "type":"structure", + "required":["node"], + "members":{ + "node":{ + "shape":"FlowNodeName", + "documentation":"

The name of the node missing configuration.

" + } + }, + "documentation":"

Details about a node missing required configuration.

" + }, + "MissingNodeInputFlowValidationDetails":{ + "type":"structure", + "required":[ + "input", + "node" + ], + "members":{ + "input":{ + "shape":"FlowNodeInputName", + "documentation":"

The name of the missing input.

" + }, + "node":{ + "shape":"FlowNodeName", + "documentation":"

The name of the node missing the required input.

" + } + }, + "documentation":"

Details about a missing required input in a node.

" + }, + "MissingNodeOutputFlowValidationDetails":{ + "type":"structure", + "required":[ + "node", + "output" + ], + "members":{ + "node":{ + "shape":"FlowNodeName", + "documentation":"

The name of the node missing the required output.

" + }, + "output":{ + "shape":"FlowNodeOutputName", + "documentation":"

The name of the missing output.

" + } + }, + "documentation":"

Details about a missing required output in a node.

" + }, + "MissingStartingNodesFlowValidationDetails":{ + "type":"structure", + "members":{ + }, + "documentation":"

Details about missing starting nodes (such as FlowInputNode) in the flow.

" + }, "ModelIdentifier":{ "type":"string", - "documentation":"

ARN or Id of a Bedrock Foundational Model or Inference Profile, or the ARN of a jumpstart model or imported model, or a provisioned throughput ARN for custom models.

", "max":2048, "min":1, "pattern":"^(arn:aws(-[^:]{1,12})?:(bedrock|sagemaker):[a-z0-9-]{1,20}:([0-9]{12})?:([a-z-]+/)?)?([a-zA-Z0-9.-]{1,63}){0,2}(([:][a-z0-9-]{1,63}){0,2})?(/[a-z0-9]{1,12})?$" @@ -5954,6 +6435,24 @@ "min":0, "pattern":"^.*$" }, + "MultipleNodeInputConnectionsFlowValidationDetails":{ + "type":"structure", + "required":[ + "input", + "node" + ], + "members":{ + "input":{ + "shape":"FlowNodeInputName", + "documentation":"

The name of the input with multiple connections to it.

" + }, + "node":{ + "shape":"FlowNodeName", + "documentation":"

The name of the node containing the input with multiple connections.

" + } + }, + "documentation":"

Details about multiple connections to a single node input.

" + }, "Name":{ "type":"string", "pattern":"^([0-9a-zA-Z][_-]?){1,100}$" @@ -5968,6 +6467,10 @@ "type":"string", "pattern":"^[\\s\\S]+$" }, + "NonEmptyString":{ + "type":"string", + "min":1 + }, "NumericalVersion":{ "type":"string", "pattern":"^[0-9]{1,5}$" @@ -6267,6 +6770,18 @@ } }, "PrimitiveLong":{"type":"long"}, + "PromptAgentResource":{ + "type":"structure", + "required":["agentIdentifier"], + "members":{ + "agentIdentifier":{ + "shape":"AgentAliasArn", + "documentation":"

The ARN of the agent with which to use the prompt.

" + } + }, + "documentation":"

Contains specifications for an Amazon Bedrock agent with which to use the prompt. For more information, see Create a prompt using Prompt management and Automate tasks in your application using conversational agents.

", + "sensitive":true + }, "PromptArn":{ "type":"string", "pattern":"^(arn:aws:bedrock:[a-z0-9-]{1,20}:[0-9]{12}:prompt/[0-9a-zA-Z]{10}(?::[0-9]{1,5})?)$" @@ -6316,6 +6831,10 @@ "type":"structure", "required":["sourceConfiguration"], "members":{ + "guardrailConfiguration":{ + "shape":"GuardrailConfiguration", + "documentation":"

Contains configurations for a guardrail to apply to the prompt in this node and the response generated from it.

" + }, "sourceConfiguration":{ "shape":"PromptFlowNodeSourceConfiguration", "documentation":"

Specifies whether the prompt is from Prompt management or defined inline.

" @@ -6333,7 +6852,7 @@ "members":{ "additionalModelRequestFields":{ "shape":"Document", - "documentation":"

Contains model-specific inference configurations that aren't in the inferenceConfiguration field. To see model-specific inference parameters, see Inference request parameters and response fields for foundation models.

" + "documentation":"

Additional fields to be included in the model request for the Prompt node.

" }, "inferenceConfiguration":{ "shape":"PromptInferenceConfiguration", @@ -6380,6 +6899,18 @@ "documentation":"

Contains configurations for a prompt and whether it is from Prompt management or defined inline.

", "union":true }, + "PromptGenAiResource":{ + "type":"structure", + "members":{ + "agent":{ + "shape":"PromptAgentResource", + "documentation":"

Specifies an Amazon Bedrock agent with which to use the prompt.

" + } + }, + "documentation":"

Contains specifications for a generative AI resource with which to use the prompt. For more information, see Create a prompt using Prompt management.

", + "sensitive":true, + "union":true + }, "PromptId":{ "type":"string", "pattern":"^[0-9a-zA-Z]{10}$" @@ -6462,10 +6993,9 @@ }, "PromptModelIdentifier":{ "type":"string", - "documentation":"

ARN or Id of a Bedrock Foundational Model or Inference Profile, or the ARN of a jumpstart model or imported model, or a provisioned throughput ARN for custom models.

", "max":2048, "min":1, - "pattern":"^(arn:aws(-[^:]+)?:bedrock:[a-z0-9-]{1,20}:(([0-9]{12}:custom-model/[a-z0-9-]{1,63}[.]{1}[a-z0-9-]{1,63}/[a-z0-9]{12})|(:foundation-model/[a-z0-9-]{1,63}[.]{1}[a-z0-9-]{1,63}([.:]?[a-z0-9-]{1,63}))|([0-9]{12}:imported-model/[a-z0-9]{12})|([0-9]{12}:provisioned-model/[a-z0-9]{12})))|([a-z0-9-]{1,63}[.]{1}[a-z0-9-]{1,63}([.:]?[a-z0-9-]{1,63}))|(([0-9a-zA-Z][_-]?)+)|(arn:aws(|-us-gov|-cn|-iso|-iso-b):bedrock:(|[0-9a-z-]{1,20}):(|[0-9]{12}):(inference-profile|application-inference-profile)/[a-zA-Z0-9-:.]+)|([a-zA-Z0-9-:.]+)$" + "pattern":"^(arn:aws(-[^:]{1,12})?:(bedrock|sagemaker):[a-z0-9-]{1,20}:([0-9]{12})?:([a-z-]+/)?)?([a-zA-Z0-9.-]{1,63}){0,2}(([:][a-z0-9-]{1,63}){0,2})?(/[a-z0-9]{1,12})?$" }, "PromptModelInferenceConfiguration":{ "type":"structure", @@ -6567,17 +7097,24 @@ "PromptTemplateConfiguration":{ "type":"structure", "members":{ + "chat":{ + "shape":"ChatPromptTemplateConfiguration", + "documentation":"

Contains configurations to use the prompt in a conversational format.

" + }, "text":{ "shape":"TextPromptTemplateConfiguration", "documentation":"

Contains configurations for the text in a message for a prompt.

" } }, - "documentation":"

Contains the message for a prompt. For more information, see Prompt management in Amazon Bedrock.

", + "documentation":"

Contains the message for a prompt. For more information, see Construct and store reusable prompts with Prompt management in Amazon Bedrock.

", "union":true }, "PromptTemplateType":{ "type":"string", - "enum":["TEXT"] + "enum":[ + "TEXT", + "CHAT" + ] }, "PromptType":{ "type":"string", @@ -6600,13 +7137,17 @@ "shape":"Document", "documentation":"

Contains model-specific inference configurations that aren't in the inferenceConfiguration field. To see model-specific inference parameters, see Inference request parameters and response fields for foundation models.

" }, + "genAiResource":{ + "shape":"PromptGenAiResource", + "documentation":"

Specifies a generative AI resource with which to use the prompt.

" + }, "inferenceConfiguration":{ "shape":"PromptInferenceConfiguration", "documentation":"

Contains inference configurations for the prompt variant.

" }, "metadata":{ "shape":"PromptMetadataList", - "documentation":"

An array of objects, each containing a key-value pair that defines a metadata tag and value to attach to a prompt variant. For more information, see Create a prompt using Prompt management.

" + "documentation":"

An array of objects, each containing a key-value pair that defines a metadata tag and value to attach to a prompt variant.

" }, "modelId":{ "shape":"PromptModelIdentifier", @@ -7157,6 +7698,17 @@ "DESCENDING" ] }, + "SpecificToolChoice":{ + "type":"structure", + "required":["name"], + "members":{ + "name":{ + "shape":"ToolName", + "documentation":"

The name of the tool.

" + } + }, + "documentation":"

Defines a specific tool that the model must request. No text is generated but the results of tool use are sent back to the model to help generate a response. For more information, see Use a tool to complete an Amazon Bedrock model response.

" + }, "StartIngestionJobRequest":{ "type":"structure", "required":[ @@ -7316,6 +7868,22 @@ "union":true }, "String":{"type":"string"}, + "SystemContentBlock":{ + "type":"structure", + "members":{ + "text":{ + "shape":"NonEmptyString", + "documentation":"

The text in the system prompt.

" + } + }, + "documentation":"

Contains a system prompt to provide context to the model or to describe how it should behave. For more information, see Create a prompt using Prompt management.

", + "sensitive":true, + "union":true + }, + "SystemContentBlocks":{ + "type":"list", + "member":{"shape":"SystemContentBlock"} + }, "TagKey":{ "type":"string", "max":128, @@ -7409,6 +7977,97 @@ }, "exception":true }, + "Tool":{ + "type":"structure", + "members":{ + "toolSpec":{ + "shape":"ToolSpecification", + "documentation":"

The specification for the tool.

" + } + }, + "documentation":"

Contains configurations for a tool that a model can use when generating a response. For more information, see Use a tool to complete an Amazon Bedrock model response.

", + "union":true + }, + "ToolChoice":{ + "type":"structure", + "members":{ + "any":{ + "shape":"AnyToolChoice", + "documentation":"

Defines tools, at least one of which must be requested by the model. No text is generated but the results of tool use are sent back to the model to help generate a response.

" + }, + "auto":{ + "shape":"AutoToolChoice", + "documentation":"

Defines tools. The model automatically decides whether to call a tool or to generate text instead.

" + }, + "tool":{ + "shape":"SpecificToolChoice", + "documentation":"

Defines a specific tool that the model must request. No text is generated but the results of tool use are sent back to the model to help generate a response.

" + } + }, + "documentation":"

Defines which tools the model should request when invoked. For more information, see Use a tool to complete an Amazon Bedrock model response.

", + "sensitive":true, + "union":true + }, + "ToolConfiguration":{ + "type":"structure", + "required":["tools"], + "members":{ + "toolChoice":{ + "shape":"ToolChoice", + "documentation":"

Defines which tools the model should request when invoked.

" + }, + "tools":{ + "shape":"ToolConfigurationToolsList", + "documentation":"

An array of tools to pass to a model.

" + } + }, + "documentation":"

Configuration information for the tools that the model can use when generating a response. For more information, see Use a tool to complete an Amazon Bedrock model response.

" + }, + "ToolConfigurationToolsList":{ + "type":"list", + "member":{"shape":"Tool"}, + "min":1, + "sensitive":true + }, + "ToolInputSchema":{ + "type":"structure", + "members":{ + "json":{ + "shape":"Document", + "documentation":"

A JSON object defining the input schema for the tool.

" + } + }, + "documentation":"

The input schema for the tool. For more information, see Use a tool to complete an Amazon Bedrock model response.

", + "union":true + }, + "ToolName":{ + "type":"string", + "max":64, + "min":1, + "pattern":"^[a-zA-Z][a-zA-Z0-9_]*$" + }, + "ToolSpecification":{ + "type":"structure", + "required":[ + "inputSchema", + "name" + ], + "members":{ + "description":{ + "shape":"NonEmptyString", + "documentation":"

The description of the tool.

" + }, + "inputSchema":{ + "shape":"ToolInputSchema", + "documentation":"

The input schema for the tool.

" + }, + "name":{ + "shape":"ToolName", + "documentation":"

The name of the tool.

" + } + }, + "documentation":"

Contains a specification for a tool. For more information, see Use a tool to complete an Amazon Bedrock model response.

" + }, "TopK":{ "type":"integer", "box":true, @@ -7477,6 +8136,107 @@ "array" ] }, + "UnfulfilledNodeInputFlowValidationDetails":{ + "type":"structure", + "required":[ + "input", + "node" + ], + "members":{ + "input":{ + "shape":"FlowNodeInputName", + "documentation":"

The name of the unfulfilled input. An input is unfulfilled if there are no data connections to it.

" + }, + "node":{ + "shape":"FlowNodeName", + "documentation":"

The name of the node containing the unfulfilled input.

" + } + }, + "documentation":"

Details about an unfulfilled node input with no valid connections.

" + }, + "UnknownConnectionConditionFlowValidationDetails":{ + "type":"structure", + "required":["connection"], + "members":{ + "connection":{ + "shape":"FlowConnectionName", + "documentation":"

The name of the connection with the unknown condition.

" + } + }, + "documentation":"

Details about an unknown condition for a connection.

" + }, + "UnknownConnectionSourceFlowValidationDetails":{ + "type":"structure", + "required":["connection"], + "members":{ + "connection":{ + "shape":"FlowConnectionName", + "documentation":"

The name of the connection with the unknown source.

" + } + }, + "documentation":"

Details about an unknown source node for a connection.

" + }, + "UnknownConnectionSourceOutputFlowValidationDetails":{ + "type":"structure", + "required":["connection"], + "members":{ + "connection":{ + "shape":"FlowConnectionName", + "documentation":"

The name of the connection with the unknown source output.

" + } + }, + "documentation":"

Details about an unknown source output for a connection.

" + }, + "UnknownConnectionTargetFlowValidationDetails":{ + "type":"structure", + "required":["connection"], + "members":{ + "connection":{ + "shape":"FlowConnectionName", + "documentation":"

The name of the connection with the unknown target.

" + } + }, + "documentation":"

Details about an unknown target node for a connection.

" + }, + "UnknownConnectionTargetInputFlowValidationDetails":{ + "type":"structure", + "required":["connection"], + "members":{ + "connection":{ + "shape":"FlowConnectionName", + "documentation":"

The name of the connection with the unknown target input.

" + } + }, + "documentation":"

Details about an unknown target input for a connection.

" + }, + "UnreachableNodeFlowValidationDetails":{ + "type":"structure", + "required":["node"], + "members":{ + "node":{ + "shape":"FlowNodeName", + "documentation":"

The name of the unreachable node.

" + } + }, + "documentation":"

Details about an unreachable node in the flow. A node is unreachable when there are no paths to it from any starting node.

" + }, + "UnsatisfiedConnectionConditionsFlowValidationDetails":{ + "type":"structure", + "required":["connection"], + "members":{ + "connection":{ + "shape":"FlowConnectionName", + "documentation":"

The name of the connection with unsatisfied conditions.

" + } + }, + "documentation":"

Details about unsatisfied conditions for a connection. A condition is unsatisfied if it can never be true, for example two branches of condition node cannot be simultaneously true.

" + }, + "UnspecifiedFlowValidationDetails":{ + "type":"structure", + "members":{ + }, + "documentation":"

Details about an unspecified validation that doesn't fit other categories.

" + }, "UntagResourceRequest":{ "type":"structure", "required":[ @@ -8110,6 +8870,26 @@ }, "documentation":"

The configuration of web URLs that you want to crawl. You should be authorized to crawl the URLs.

" }, + "ValidateFlowDefinitionRequest":{ + "type":"structure", + "required":["definition"], + "members":{ + "definition":{ + "shape":"FlowDefinition", + "documentation":"

The definition of a flow to validate.

" + } + } + }, + "ValidateFlowDefinitionResponse":{ + "type":"structure", + "required":["validations"], + "members":{ + "validations":{ + "shape":"FlowValidations", + "documentation":"

Contains an array of objects, each of which contains an error identified by validation.

" + } + } + }, "ValidationException":{ "type":"structure", "members":{ diff --git a/botocore/data/bedrock-runtime/2023-09-30/service-2.json b/botocore/data/bedrock-runtime/2023-09-30/service-2.json index 5a6e8cce24..c866a01cad 100644 --- a/botocore/data/bedrock-runtime/2023-09-30/service-2.json +++ b/botocore/data/bedrock-runtime/2023-09-30/service-2.json @@ -52,7 +52,7 @@ {"shape":"ModelNotReadyException"}, {"shape":"ModelErrorException"} ], - "documentation":"

Sends messages to the specified Amazon Bedrock model. Converse provides a consistent interface that works with all models that support messages. This allows you to write code once and use it with different models. If a model has unique inference parameters, you can also pass those unique parameters to the model.

Amazon Bedrock doesn't store any text, images, or documents that you provide as content. The data is only used to generate the response.

For information about the Converse API, see Use the Converse API in the Amazon Bedrock User Guide. To use a guardrail, see Use a guardrail with the Converse API in the Amazon Bedrock User Guide. To use a tool with a model, see Tool use (Function calling) in the Amazon Bedrock User Guide

For example code, see Converse API examples in the Amazon Bedrock User Guide.

This operation requires permission for the bedrock:InvokeModel action.

" + "documentation":"

Sends messages to the specified Amazon Bedrock model. Converse provides a consistent interface that works with all models that support messages. This allows you to write code once and use it with different models. If a model has unique inference parameters, you can also pass those unique parameters to the model.

Amazon Bedrock doesn't store any text, images, or documents that you provide as content. The data is only used to generate the response.

You can submit a prompt by including it in the messages field, specifying the modelId of a foundation model or inference profile to run inference on it, and including any other fields that are relevant to your use case.

You can also submit a prompt from Prompt management by specifying the ARN of the prompt version and including a map of variables to values in the promptVariables field. You can append more messages to the prompt by using the messages field. If you use a prompt from Prompt management, you can't include the following fields in the request: additionalModelRequestFields, inferenceConfig, system, or toolConfig. Instead, these fields must be defined through Prompt management. For more information, see Use a prompt from Prompt management.

For information about the Converse API, see Use the Converse API in the Amazon Bedrock User Guide. To use a guardrail, see Use a guardrail with the Converse API in the Amazon Bedrock User Guide. To use a tool with a model, see Tool use (Function calling) in the Amazon Bedrock User Guide

For example code, see Converse API examples in the Amazon Bedrock User Guide.

This operation requires permission for the bedrock:InvokeModel action.

" }, "ConverseStream":{ "name":"ConverseStream", @@ -74,7 +74,7 @@ {"shape":"ModelNotReadyException"}, {"shape":"ModelErrorException"} ], - "documentation":"

Sends messages to the specified Amazon Bedrock model and returns the response in a stream. ConverseStream provides a consistent API that works with all Amazon Bedrock models that support messages. This allows you to write code once and use it with different models. Should a model have unique inference parameters, you can also pass those unique parameters to the model.

To find out if a model supports streaming, call GetFoundationModel and check the responseStreamingSupported field in the response.

The CLI doesn't support streaming operations in Amazon Bedrock, including ConverseStream.

Amazon Bedrock doesn't store any text, images, or documents that you provide as content. The data is only used to generate the response.

For information about the Converse API, see Use the Converse API in the Amazon Bedrock User Guide. To use a guardrail, see Use a guardrail with the Converse API in the Amazon Bedrock User Guide. To use a tool with a model, see Tool use (Function calling) in the Amazon Bedrock User Guide

For example code, see Conversation streaming example in the Amazon Bedrock User Guide.

This operation requires permission for the bedrock:InvokeModelWithResponseStream action.

" + "documentation":"

Sends messages to the specified Amazon Bedrock model and returns the response in a stream. ConverseStream provides a consistent API that works with all Amazon Bedrock models that support messages. This allows you to write code once and use it with different models. Should a model have unique inference parameters, you can also pass those unique parameters to the model.

To find out if a model supports streaming, call GetFoundationModel and check the responseStreamingSupported field in the response.

The CLI doesn't support streaming operations in Amazon Bedrock, including ConverseStream.

Amazon Bedrock doesn't store any text, images, or documents that you provide as content. The data is only used to generate the response.

You can submit a prompt by including it in the messages field, specifying the modelId of a foundation model or inference profile to run inference on it, and including any other fields that are relevant to your use case.

You can also submit a prompt from Prompt management by specifying the ARN of the prompt version and including a map of variables to values in the promptVariables field. You can append more messages to the prompt by using the messages field. If you use a prompt from Prompt management, you can't include the following fields in the request: additionalModelRequestFields, inferenceConfig, system, or toolConfig. Instead, these fields must be defined through Prompt management. For more information, see Use a prompt from Prompt management.

For information about the Converse API, see Use the Converse API in the Amazon Bedrock User Guide. To use a guardrail, see Use a guardrail with the Converse API in the Amazon Bedrock User Guide. To use a tool with a model, see Tool use (Function calling) in the Amazon Bedrock User Guide

For example code, see Conversation streaming example in the Amazon Bedrock User Guide.

This operation requires permission for the bedrock:InvokeModelWithResponseStream action.

" }, "InvokeModel":{ "name":"InvokeModel", @@ -339,7 +339,7 @@ "type":"string", "max":2048, "min":1, - "pattern":"(arn:aws(-[^:]+)?:bedrock:[a-z0-9-]{1,20}:(([0-9]{12}:custom-model/[a-z0-9-]{1,63}[.]{1}[a-z0-9-]{1,63}/[a-z0-9]{12})|(:foundation-model/[a-z0-9-]{1,63}[.]{1}[a-z0-9-]{1,63}([.:]?[a-z0-9-]{1,63}))|([0-9]{12}:imported-model/[a-z0-9]{12})|([0-9]{12}:provisioned-model/[a-z0-9]{12})|([0-9]{12}:(inference-profile|application-inference-profile)/[a-zA-Z0-9-:.]+)))|([a-z0-9-]{1,63}[.]{1}[a-z0-9-]{1,63}([.:]?[a-z0-9-]{1,63}))|(([0-9a-zA-Z][_-]?)+)|([a-zA-Z0-9-:.]+)" + "pattern":"(arn:aws(-[^:]+)?:bedrock:[a-z0-9-]{1,20}:(([0-9]{12}:custom-model/[a-z0-9-]{1,63}[.]{1}[a-z0-9-]{1,63}/[a-z0-9]{12})|(:foundation-model/[a-z0-9-]{1,63}[.]{1}[a-z0-9-]{1,63}([.:]?[a-z0-9-]{1,63}))|([0-9]{12}:imported-model/[a-z0-9]{12})|([0-9]{12}:provisioned-model/[a-z0-9]{12})|([0-9]{12}:(inference-profile|application-inference-profile)/[a-zA-Z0-9-:.]+)))|([a-z0-9-]{1,63}[.]{1}[a-z0-9-]{1,63}([.:]?[a-z0-9-]{1,63}))|(([0-9a-zA-Z][_-]?)+)|([a-zA-Z0-9-:.]+)|(^(arn:aws(-[^:]+)?:bedrock:[a-z0-9-]{1,20}:[0-9]{12}:prompt/[0-9a-zA-Z]{10}(?::[0-9]{1,5})?))" }, "ConverseMetrics":{ "type":"structure", @@ -365,14 +365,11 @@ }, "ConverseRequest":{ "type":"structure", - "required":[ - "modelId", - "messages" - ], + "required":["modelId"], "members":{ "modelId":{ "shape":"ConversationalModelId", - "documentation":"

The identifier for the model that you want to call.

The modelId to provide depends on the type of model or throughput that you use:

The Converse API doesn't support imported models.

", + "documentation":"

Specifies the model or throughput with which to run inference, or the prompt resource to use in inference. The value depends on the resource that you use:

The Converse API doesn't support imported models.

", "location":"uri", "locationName":"modelId" }, @@ -382,11 +379,11 @@ }, "system":{ "shape":"SystemContentBlocks", - "documentation":"

A system prompt to pass to the model.

" + "documentation":"

A prompt that provides instructions or context to the model about the task it should perform, or the persona it should adopt during the conversation.

" }, "inferenceConfig":{ "shape":"InferenceConfiguration", - "documentation":"

Inference parameters to pass to the model. Converse supports a base set of inference parameters. If you need to pass additional parameters that the model supports, use the additionalModelRequestFields request field.

" + "documentation":"

Inference parameters to pass to the model. Converse and ConverseStream support a base set of inference parameters. If you need to pass additional parameters that the model supports, use the additionalModelRequestFields request field.

" }, "toolConfig":{ "shape":"ToolConfiguration", @@ -394,15 +391,19 @@ }, "guardrailConfig":{ "shape":"GuardrailConfiguration", - "documentation":"

Configuration information for a guardrail that you want to use in the request.

" + "documentation":"

Configuration information for a guardrail that you want to use in the request. If you include guardContent blocks in the content field in the messages field, the guardrail operates only on those messages. If you include no guardContent blocks, the guardrail operates on all messages in the request body and in any included prompt resource.

" }, "additionalModelRequestFields":{ "shape":"Document", - "documentation":"

Additional inference parameters that the model supports, beyond the base set of inference parameters that Converse supports in the inferenceConfig field. For more information, see Model parameters.

" + "documentation":"

Additional inference parameters that the model supports, beyond the base set of inference parameters that Converse and ConverseStream support in the inferenceConfig field. For more information, see Model parameters.

" + }, + "promptVariables":{ + "shape":"PromptVariableMap", + "documentation":"

Contains a map of variables in a prompt from Prompt management to objects containing the values to fill in for them when running model invocation. This field is ignored if you don't specify a prompt resource in the modelId field.

" }, "additionalModelResponseFieldPaths":{ "shape":"ConverseRequestAdditionalModelResponseFieldPathsList", - "documentation":"

Additional model parameters field paths to return in the response. Converse returns the requested fields as a JSON Pointer object in the additionalModelResponseFields field. The following is example JSON for additionalModelResponseFieldPaths.

[ \"/stop_sequence\" ]

For information about the JSON Pointer syntax, see the Internet Engineering Task Force (IETF) documentation.

Converse rejects an empty JSON Pointer or incorrectly structured JSON Pointer with a 400 error code. if the JSON Pointer is valid, but the requested field is not in the model response, it is ignored by Converse.

" + "documentation":"

Additional model parameters field paths to return in the response. Converse and ConverseStream return the requested fields as a JSON Pointer object in the additionalModelResponseFields field. The following is example JSON for additionalModelResponseFieldPaths.

[ \"/stop_sequence\" ]

For information about the JSON Pointer syntax, see the Internet Engineering Task Force (IETF) documentation.

Converse and ConverseStream reject an empty JSON Pointer or incorrectly structured JSON Pointer with a 400 error code. if the JSON Pointer is valid, but the requested field is not in the model response, it is ignored by Converse.

" } } }, @@ -539,14 +540,11 @@ }, "ConverseStreamRequest":{ "type":"structure", - "required":[ - "modelId", - "messages" - ], + "required":["modelId"], "members":{ "modelId":{ "shape":"ConversationalModelId", - "documentation":"

The ID for the model.

The modelId to provide depends on the type of model or throughput that you use:

The Converse API doesn't support imported models.

", + "documentation":"

Specifies the model or throughput with which to run inference, or the prompt resource to use in inference. The value depends on the resource that you use:

The Converse API doesn't support imported models.

", "location":"uri", "locationName":"modelId" }, @@ -556,11 +554,11 @@ }, "system":{ "shape":"SystemContentBlocks", - "documentation":"

A system prompt to send to the model.

" + "documentation":"

A prompt that provides instructions or context to the model about the task it should perform, or the persona it should adopt during the conversation.

" }, "inferenceConfig":{ "shape":"InferenceConfiguration", - "documentation":"

Inference parameters to pass to the model. ConverseStream supports a base set of inference parameters. If you need to pass additional parameters that the model supports, use the additionalModelRequestFields request field.

" + "documentation":"

Inference parameters to pass to the model. Converse and ConverseStream support a base set of inference parameters. If you need to pass additional parameters that the model supports, use the additionalModelRequestFields request field.

" }, "toolConfig":{ "shape":"ToolConfiguration", @@ -568,15 +566,19 @@ }, "guardrailConfig":{ "shape":"GuardrailStreamConfiguration", - "documentation":"

Configuration information for a guardrail that you want to use in the request.

" + "documentation":"

Configuration information for a guardrail that you want to use in the request. If you include guardContent blocks in the content field in the messages field, the guardrail operates only on those messages. If you include no guardContent blocks, the guardrail operates on all messages in the request body and in any included prompt resource.

" }, "additionalModelRequestFields":{ "shape":"Document", - "documentation":"

Additional inference parameters that the model supports, beyond the base set of inference parameters that ConverseStream supports in the inferenceConfig field.

" + "documentation":"

Additional inference parameters that the model supports, beyond the base set of inference parameters that Converse and ConverseStream support in the inferenceConfig field. For more information, see Model parameters.

" + }, + "promptVariables":{ + "shape":"PromptVariableMap", + "documentation":"

Contains a map of variables in a prompt from Prompt management to objects containing the values to fill in for them when running model invocation. This field is ignored if you don't specify a prompt resource in the modelId field.

" }, "additionalModelResponseFieldPaths":{ "shape":"ConverseStreamRequestAdditionalModelResponseFieldPathsList", - "documentation":"

Additional model parameters field paths to return in the response. ConverseStream returns the requested fields as a JSON Pointer object in the additionalModelResponseFields field. The following is example JSON for additionalModelResponseFieldPaths.

[ \"/stop_sequence\" ]

For information about the JSON Pointer syntax, see the Internet Engineering Task Force (IETF) documentation.

ConverseStream rejects an empty JSON Pointer or incorrectly structured JSON Pointer with a 400 error code. if the JSON Pointer is valid, but the requested field is not in the model response, it is ignored by ConverseStream.

" + "documentation":"

Additional model parameters field paths to return in the response. Converse and ConverseStream return the requested fields as a JSON Pointer object in the additionalModelResponseFields field. The following is example JSON for additionalModelResponseFieldPaths.

[ \"/stop_sequence\" ]

For information about the JSON Pointer syntax, see the Internet Engineering Task Force (IETF) documentation.

Converse and ConverseStream reject an empty JSON Pointer or incorrectly structured JSON Pointer with a 400 error code. if the JSON Pointer is valid, but the requested field is not in the model response, it is ignored by Converse.

" } } }, @@ -1515,14 +1517,11 @@ "type":"string", "max":2048, "min":1, - "pattern":"(arn:aws(-[^:]+)?:bedrock:[a-z0-9-]{1,20}:(([0-9]{12}:custom-model/[a-z0-9-]{1,63}[.]{1}[a-z0-9-]{1,63}/[a-z0-9]{12})|(:foundation-model/[a-z0-9-]{1,63}[.]{1}[a-z0-9-]{1,63}([.:]?[a-z0-9-]{1,63}))|([0-9]{12}:imported-model/[a-z0-9]{12})|([0-9]{12}:provisioned-model/[a-z0-9]{12})|([0-9]{12}:(inference-profile|application-inference-profile)/[a-zA-Z0-9-:.]+)))|([a-z0-9-]{1,63}[.]{1}[a-z0-9-]{1,63}([.:]?[a-z0-9-]{1,63}))|(([0-9a-zA-Z][_-]?)+)|([a-zA-Z0-9-:.]+)" + "pattern":"(arn:aws(-[^:]+)?:bedrock:[a-z0-9-]{1,20}:(([0-9]{12}:custom-model/[a-z0-9-]{1,63}[.]{1}[a-z0-9-]{1,63}/[a-z0-9]{12})|(:foundation-model/[a-z0-9-]{1,63}[.]{1}[a-z0-9-]{1,63}([.:]?[a-z0-9-]{1,63}))|([0-9]{12}:imported-model/[a-z0-9]{12})|([0-9]{12}:provisioned-model/[a-z0-9]{12})|([0-9]{12}:(inference-profile|application-inference-profile)/[a-zA-Z0-9-:.]+)))|([a-z0-9-]{1,63}[.]{1}[a-z0-9-]{1,63}([.:]?[a-z0-9-]{1,63}))|(([0-9a-zA-Z][_-]?)+)|([a-zA-Z0-9-:.]+)$|(^(arn:aws(-[^:]+)?:bedrock:[a-z0-9-]{1,20}:[0-9]{12}:prompt/[0-9a-zA-Z]{10}(?::[0-9]{1,5})?))" }, "InvokeModelRequest":{ "type":"structure", - "required":[ - "body", - "modelId" - ], + "required":["modelId"], "members":{ "body":{ "shape":"Body", @@ -1589,10 +1588,7 @@ }, "InvokeModelWithResponseStreamRequest":{ "type":"structure", - "required":[ - "body", - "modelId" - ], + "required":["modelId"], "members":{ "body":{ "shape":"Body", @@ -1812,6 +1808,23 @@ "event":true, "sensitive":true }, + "PromptVariableMap":{ + "type":"map", + "key":{"shape":"String"}, + "value":{"shape":"PromptVariableValues"}, + "sensitive":true + }, + "PromptVariableValues":{ + "type":"structure", + "members":{ + "text":{ + "shape":"String", + "documentation":"

The text value that the variable maps to.

" + } + }, + "documentation":"

Contains a map of variables in a prompt from Prompt management to an object containing the values to fill in for them when running model invocation. For more information, see How Prompt management works.

", + "union":true + }, "ResourceNotFoundException":{ "type":"structure", "members":{ diff --git a/botocore/data/cleanrooms/2022-02-17/service-2.json b/botocore/data/cleanrooms/2022-02-17/service-2.json index d90a3bac7b..319fb09771 100644 --- a/botocore/data/cleanrooms/2022-02-17/service-2.json +++ b/botocore/data/cleanrooms/2022-02-17/service-2.json @@ -1527,7 +1527,7 @@ "type":"string", "max":256, "min":0, - "pattern":"arn:aws:cleanrooms:[\\w]{2}-[\\w]{4,9}-[\\d]:([\\d]{12}|\\*):membership/[\\*\\d\\w-]+/configuredaudiencemodelassociation/[\\*\\d\\w-]+" + "pattern":"arn:aws:cleanrooms:[\\w]{2}-[\\w]{4,9}-[\\d]:([\\d]{12}|\\*):membership\\/[\\*\\d\\w-]+\\/configuredaudiencemodelassociation\\/[\\*\\d\\w-]+$|^arn:aws[-a-z]*:cleanrooms-ml:[-a-z0-9]+:([0-9]{12}|\\*):membership\\/[\\*\\d\\w-]+\\/configured-model-algorithm-association\\/([-a-zA-Z0-9_\\/.]+|\\*)" }, "AggregateColumn":{ "type":"structure", @@ -3869,6 +3869,10 @@ "shape":"MemberAbilities", "documentation":"

The abilities granted to the collaboration creator.

" }, + "creatorMLMemberAbilities":{ + "shape":"MLMemberAbilities", + "documentation":"

The ML abilities granted to the collaboration creator.

Custom ML modeling is in beta release and is subject to change. For beta terms and conditions, see Betas and Previews in the Amazon Web Services Service Terms.

" + }, "creatorDisplayName":{ "shape":"DisplayName", "documentation":"

The display name of the collaboration creator.

" @@ -4293,6 +4297,18 @@ } } }, + "CustomMLMemberAbilities":{ + "type":"list", + "member":{"shape":"CustomMLMemberAbility"}, + "min":1 + }, + "CustomMLMemberAbility":{ + "type":"string", + "enum":[ + "CAN_RECEIVE_MODEL_OUTPUT", + "CAN_RECEIVE_INFERENCE_OUTPUT" + ] + }, "DataEncryptionMetadata":{ "type":"structure", "required":[ @@ -6705,6 +6721,31 @@ "type":"long", "box":true }, + "MLMemberAbilities":{ + "type":"structure", + "required":["customMLMemberAbilities"], + "members":{ + "customMLMemberAbilities":{ + "shape":"CustomMLMemberAbilities", + "documentation":"

The custom ML member abilities for a collaboration member. The inference feature is not available in the custom ML modeling beta.

Custom ML modeling is in beta release and is subject to change. For beta terms and conditions, see Betas and Previews in the Amazon Web Services Service Terms.

" + } + }, + "documentation":"

The ML member abilities for a collaboration member.

Custom ML modeling is in beta release and is subject to change. For beta terms and conditions, see Betas and Previews in the Amazon Web Services Service Terms.

" + }, + "MLPaymentConfig":{ + "type":"structure", + "members":{ + "modelTraining":{ + "shape":"ModelTrainingPaymentConfig", + "documentation":"

The payment responsibilities accepted by the member for model training.

" + }, + "modelInference":{ + "shape":"ModelInferencePaymentConfig", + "documentation":"

The payment responsibilities accepted by the member for model inference.

" + } + }, + "documentation":"

An object representing the collaboration member's machine learning payment responsibilities set by the collaboration creator.

" + }, "MaxResults":{ "type":"integer", "box":true, @@ -6744,6 +6785,10 @@ "shape":"MemberAbilities", "documentation":"

The abilities granted to the collaboration member.

" }, + "mlMemberAbilities":{ + "shape":"MLMemberAbilities", + "documentation":"

The ML abilities granted to the collaboration member.

Custom ML modeling is in beta release and is subject to change. For beta terms and conditions, see Betas and Previews in the Amazon Web Services Service Terms.

" + }, "displayName":{ "shape":"DisplayName", "documentation":"

The member's display name.

" @@ -6792,6 +6837,10 @@ "shape":"MemberAbilities", "documentation":"

The abilities granted to the collaboration member.

" }, + "mlAbilities":{ + "shape":"MLMemberAbilities", + "documentation":"

Provides a summary of the ML abilities for the collaboration member.

Custom ML modeling is in beta release and is subject to change. For beta terms and conditions, see Betas and Previews in the Amazon Web Services Service Terms.

" + }, "createTime":{ "shape":"Timestamp", "documentation":"

The time when the member was created.

" @@ -6881,6 +6930,10 @@ "shape":"MemberAbilities", "documentation":"

The abilities granted to the collaboration member.

" }, + "mlMemberAbilities":{ + "shape":"MLMemberAbilities", + "documentation":"

Specifies the ML member abilities that are granted to a collaboration member.

Custom ML modeling is in beta release and is subject to change. For beta terms and conditions, see Betas and Previews in the Amazon Web Services Service Terms.

" + }, "queryLogStatus":{ "shape":"MembershipQueryLogStatus", "documentation":"

An indicator as to whether query logging has been enabled or disabled for the membership.

" @@ -6908,6 +6961,42 @@ "min":36, "pattern":"[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}" }, + "MembershipMLPaymentConfig":{ + "type":"structure", + "members":{ + "modelTraining":{ + "shape":"MembershipModelTrainingPaymentConfig", + "documentation":"

The payment responsibilities accepted by the member for model training.

" + }, + "modelInference":{ + "shape":"MembershipModelInferencePaymentConfig", + "documentation":"

The payment responsibilities accepted by the member for model inference.

" + } + }, + "documentation":"

An object representing the collaboration member's machine learning payment responsibilities set by the collaboration creator.

" + }, + "MembershipModelInferencePaymentConfig":{ + "type":"structure", + "required":["isResponsible"], + "members":{ + "isResponsible":{ + "shape":"Boolean", + "documentation":"

Indicates whether the collaboration member has accepted to pay for model inference costs (TRUE) or has not accepted to pay for model inference costs (FALSE).

If the collaboration creator has not specified anyone to pay for model inference costs, then the member who can query is the default payer.

An error message is returned for the following reasons:

" + } + }, + "documentation":"

An object representing the collaboration member's model inference payment responsibilities set by the collaboration creator.

" + }, + "MembershipModelTrainingPaymentConfig":{ + "type":"structure", + "required":["isResponsible"], + "members":{ + "isResponsible":{ + "shape":"Boolean", + "documentation":"

Indicates whether the collaboration member has accepted to pay for model training costs (TRUE) or has not accepted to pay for model training costs (FALSE).

If the collaboration creator has not specified anyone to pay for model training costs, then the member who can query is the default payer.

An error message is returned for the following reasons:

" + } + }, + "documentation":"

An object representing the collaboration member's model training payment responsibilities set by the collaboration creator.

" + }, "MembershipPaymentConfiguration":{ "type":"structure", "required":["queryCompute"], @@ -6915,6 +7004,10 @@ "queryCompute":{ "shape":"MembershipQueryComputePaymentConfig", "documentation":"

The payment responsibilities accepted by the collaboration member for query compute costs.

" + }, + "machineLearning":{ + "shape":"MembershipMLPaymentConfig", + "documentation":"

The payment responsibilities accepted by the collaboration member for machine learning costs.

" } }, "documentation":"

An object representing the payment responsibilities accepted by the collaboration member.

" @@ -7029,6 +7122,10 @@ "shape":"MemberAbilities", "documentation":"

The abilities granted to the collaboration member.

" }, + "mlMemberAbilities":{ + "shape":"MLMemberAbilities", + "documentation":"

Provides a summary of the ML abilities for the collaboration member.

Custom ML modeling is in beta release and is subject to change. For beta terms and conditions, see Betas and Previews in the Amazon Web Services Service Terms.

" + }, "paymentConfiguration":{ "shape":"MembershipPaymentConfiguration", "documentation":"

The payment responsibilities accepted by the collaboration member.

" @@ -7040,6 +7137,28 @@ "type":"list", "member":{"shape":"MembershipSummary"} }, + "ModelInferencePaymentConfig":{ + "type":"structure", + "required":["isResponsible"], + "members":{ + "isResponsible":{ + "shape":"Boolean", + "documentation":"

Indicates whether the collaboration creator has configured the collaboration member to pay for model inference costs (TRUE) or has not configured the collaboration member to pay for model inference costs (FALSE).

Exactly one member can be configured to pay for model inference costs. An error is returned if the collaboration creator sets a TRUE value for more than one member in the collaboration.

If the collaboration creator hasn't specified anyone as the member paying for model inference costs, then the member who can query is the default payer. An error is returned if the collaboration creator sets a FALSE value for the member who can query.

" + } + }, + "documentation":"

An object representing the collaboration member's model inference payment responsibilities set by the collaboration creator.

" + }, + "ModelTrainingPaymentConfig":{ + "type":"structure", + "required":["isResponsible"], + "members":{ + "isResponsible":{ + "shape":"Boolean", + "documentation":"

Indicates whether the collaboration creator has configured the collaboration member to pay for model training costs (TRUE) or has not configured the collaboration member to pay for model training costs (FALSE).

Exactly one member can be configured to pay for model training costs. An error is returned if the collaboration creator sets a TRUE value for more than one member in the collaboration.

If the collaboration creator hasn't specified anyone as the member paying for model training costs, then the member who can query is the default payer. An error is returned if the collaboration creator sets a FALSE value for the member who can query.

" + } + }, + "documentation":"

An object representing the collaboration member's model training payment responsibilities set by the collaboration creator.

" + }, "PaginationToken":{ "type":"string", "max":10240, @@ -7101,6 +7220,10 @@ "queryCompute":{ "shape":"QueryComputePaymentConfig", "documentation":"

The collaboration member's payment responsibilities set by the collaboration creator for query compute costs.

" + }, + "machineLearning":{ + "shape":"MLPaymentConfig", + "documentation":"

An object representing the collaboration member's machine learning payment responsibilities set by the collaboration creator.

" } }, "documentation":"

An object representing the collaboration member's payment responsibilities set by the collaboration creator.

" diff --git a/botocore/data/cleanroomsml/2023-09-06/paginators-1.json b/botocore/data/cleanroomsml/2023-09-06/paginators-1.json index c3394f11c6..79215c552e 100644 --- a/botocore/data/cleanroomsml/2023-09-06/paginators-1.json +++ b/botocore/data/cleanroomsml/2023-09-06/paginators-1.json @@ -29,6 +29,66 @@ "output_token": "nextToken", "limit_key": "maxResults", "result_key": "trainingDatasets" + }, + "ListCollaborationConfiguredModelAlgorithmAssociations": { + "input_token": "nextToken", + "output_token": "nextToken", + "limit_key": "maxResults", + "result_key": "collaborationConfiguredModelAlgorithmAssociations" + }, + "ListCollaborationMLInputChannels": { + "input_token": "nextToken", + "output_token": "nextToken", + "limit_key": "maxResults", + "result_key": "collaborationMLInputChannelsList" + }, + "ListCollaborationTrainedModelExportJobs": { + "input_token": "nextToken", + "output_token": "nextToken", + "limit_key": "maxResults", + "result_key": "collaborationTrainedModelExportJobs" + }, + "ListCollaborationTrainedModelInferenceJobs": { + "input_token": "nextToken", + "output_token": "nextToken", + "limit_key": "maxResults", + "result_key": "collaborationTrainedModelInferenceJobs" + }, + "ListCollaborationTrainedModels": { + "input_token": "nextToken", + "output_token": "nextToken", + "limit_key": "maxResults", + "result_key": "collaborationTrainedModels" + }, + "ListConfiguredModelAlgorithmAssociations": { + "input_token": "nextToken", + "output_token": "nextToken", + "limit_key": "maxResults", + "result_key": "configuredModelAlgorithmAssociations" + }, + "ListConfiguredModelAlgorithms": { + "input_token": "nextToken", + "output_token": "nextToken", + "limit_key": "maxResults", + "result_key": "configuredModelAlgorithms" + }, + "ListMLInputChannels": { + "input_token": "nextToken", + "output_token": "nextToken", + "limit_key": "maxResults", + "result_key": "mlInputChannelsList" + }, + "ListTrainedModelInferenceJobs": { + "input_token": "nextToken", + "output_token": "nextToken", + "limit_key": "maxResults", + "result_key": "trainedModelInferenceJobs" + }, + "ListTrainedModels": { + "input_token": "nextToken", + "output_token": "nextToken", + "limit_key": "maxResults", + "result_key": "trainedModels" } } } diff --git a/botocore/data/cleanroomsml/2023-09-06/service-2.json b/botocore/data/cleanroomsml/2023-09-06/service-2.json index 7a9e69e30b..f0878885bc 100644 --- a/botocore/data/cleanroomsml/2023-09-06/service-2.json +++ b/botocore/data/cleanroomsml/2023-09-06/service-2.json @@ -13,6 +13,40 @@ "uid":"cleanroomsml-2023-09-06" }, "operations":{ + "CancelTrainedModel":{ + "name":"CancelTrainedModel", + "http":{ + "method":"PATCH", + "requestUri":"/memberships/{membershipIdentifier}/trained-models/{trainedModelArn}", + "responseCode":200 + }, + "input":{"shape":"CancelTrainedModelRequest"}, + "errors":[ + {"shape":"ConflictException"}, + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ResourceNotFoundException"} + ], + "documentation":"

Submits a request to cancel the trained model job.

", + "idempotent":true + }, + "CancelTrainedModelInferenceJob":{ + "name":"CancelTrainedModelInferenceJob", + "http":{ + "method":"PATCH", + "requestUri":"/memberships/{membershipIdentifier}/trained-model-inference-jobs/{trainedModelInferenceJobArn}", + "responseCode":200 + }, + "input":{"shape":"CancelTrainedModelInferenceJobRequest"}, + "errors":[ + {"shape":"ConflictException"}, + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ResourceNotFoundException"} + ], + "documentation":"

Submits a request to cancel a trained model inference job.

", + "idempotent":true + }, "CreateAudienceModel":{ "name":"CreateAudienceModel", "http":{ @@ -51,6 +85,81 @@ "documentation":"

Defines the information necessary to create a configured audience model.

", "idempotent":true }, + "CreateConfiguredModelAlgorithm":{ + "name":"CreateConfiguredModelAlgorithm", + "http":{ + "method":"POST", + "requestUri":"/configured-model-algorithms", + "responseCode":200 + }, + "input":{"shape":"CreateConfiguredModelAlgorithmRequest"}, + "output":{"shape":"CreateConfiguredModelAlgorithmResponse"}, + "errors":[ + {"shape":"ConflictException"}, + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ServiceQuotaExceededException"} + ], + "documentation":"

Creates a configured model algorithm using a container image stored in an ECR repository.

", + "idempotent":true + }, + "CreateConfiguredModelAlgorithmAssociation":{ + "name":"CreateConfiguredModelAlgorithmAssociation", + "http":{ + "method":"POST", + "requestUri":"/memberships/{membershipIdentifier}/configured-model-algorithm-associations", + "responseCode":200 + }, + "input":{"shape":"CreateConfiguredModelAlgorithmAssociationRequest"}, + "output":{"shape":"CreateConfiguredModelAlgorithmAssociationResponse"}, + "errors":[ + {"shape":"ConflictException"}, + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ResourceNotFoundException"}, + {"shape":"ServiceQuotaExceededException"} + ], + "documentation":"

Associates a configured model algorithm to a collaboration for use by any member of the collaboration.

", + "idempotent":true + }, + "CreateMLInputChannel":{ + "name":"CreateMLInputChannel", + "http":{ + "method":"POST", + "requestUri":"/memberships/{membershipIdentifier}/ml-input-channels", + "responseCode":200 + }, + "input":{"shape":"CreateMLInputChannelRequest"}, + "output":{"shape":"CreateMLInputChannelResponse"}, + "errors":[ + {"shape":"ConflictException"}, + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ResourceNotFoundException"}, + {"shape":"ServiceQuotaExceededException"} + ], + "documentation":"

Provides the information to create an ML input channel. An ML input channel is the result of a query that can be used for ML modeling.

", + "idempotent":true + }, + "CreateTrainedModel":{ + "name":"CreateTrainedModel", + "http":{ + "method":"POST", + "requestUri":"/memberships/{membershipIdentifier}/trained-models", + "responseCode":200 + }, + "input":{"shape":"CreateTrainedModelRequest"}, + "output":{"shape":"CreateTrainedModelResponse"}, + "errors":[ + {"shape":"ConflictException"}, + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ResourceNotFoundException"}, + {"shape":"ServiceQuotaExceededException"} + ], + "documentation":"

Creates a trained model from an associated configured model algorithm using data from any member of the collaboration.

", + "idempotent":true + }, "CreateTrainingDataset":{ "name":"CreateTrainingDataset", "http":{ @@ -135,6 +244,90 @@ "documentation":"

Deletes the specified configured audience model policy.

", "idempotent":true }, + "DeleteConfiguredModelAlgorithm":{ + "name":"DeleteConfiguredModelAlgorithm", + "http":{ + "method":"DELETE", + "requestUri":"/configured-model-algorithms/{configuredModelAlgorithmArn}", + "responseCode":200 + }, + "input":{"shape":"DeleteConfiguredModelAlgorithmRequest"}, + "errors":[ + {"shape":"ConflictException"}, + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ResourceNotFoundException"} + ], + "documentation":"

Deletes a configured model algorithm.

", + "idempotent":true + }, + "DeleteConfiguredModelAlgorithmAssociation":{ + "name":"DeleteConfiguredModelAlgorithmAssociation", + "http":{ + "method":"DELETE", + "requestUri":"/memberships/{membershipIdentifier}/configured-model-algorithm-associations/{configuredModelAlgorithmAssociationArn}", + "responseCode":200 + }, + "input":{"shape":"DeleteConfiguredModelAlgorithmAssociationRequest"}, + "errors":[ + {"shape":"ConflictException"}, + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ResourceNotFoundException"} + ], + "documentation":"

Deletes a configured model algorithm association.

", + "idempotent":true + }, + "DeleteMLConfiguration":{ + "name":"DeleteMLConfiguration", + "http":{ + "method":"DELETE", + "requestUri":"/memberships/{membershipIdentifier}/ml-configurations", + "responseCode":200 + }, + "input":{"shape":"DeleteMLConfigurationRequest"}, + "errors":[ + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ResourceNotFoundException"} + ], + "documentation":"

Deletes a ML modeling configuration.

", + "idempotent":true + }, + "DeleteMLInputChannelData":{ + "name":"DeleteMLInputChannelData", + "http":{ + "method":"DELETE", + "requestUri":"/memberships/{membershipIdentifier}/ml-input-channels/{mlInputChannelArn}", + "responseCode":200 + }, + "input":{"shape":"DeleteMLInputChannelDataRequest"}, + "errors":[ + {"shape":"ConflictException"}, + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ResourceNotFoundException"} + ], + "documentation":"

Provides the information necessary to delete an ML input channel.

", + "idempotent":true + }, + "DeleteTrainedModelOutput":{ + "name":"DeleteTrainedModelOutput", + "http":{ + "method":"DELETE", + "requestUri":"/memberships/{membershipIdentifier}/trained-models/{trainedModelArn}", + "responseCode":200 + }, + "input":{"shape":"DeleteTrainedModelOutputRequest"}, + "errors":[ + {"shape":"ConflictException"}, + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ResourceNotFoundException"} + ], + "documentation":"

Deletes the output of a trained model.

", + "idempotent":true + }, "DeleteTrainingDataset":{ "name":"DeleteTrainingDataset", "http":{ @@ -184,6 +377,54 @@ ], "documentation":"

Returns information about an audience model

" }, + "GetCollaborationConfiguredModelAlgorithmAssociation":{ + "name":"GetCollaborationConfiguredModelAlgorithmAssociation", + "http":{ + "method":"GET", + "requestUri":"/collaborations/{collaborationIdentifier}/configured-model-algorithm-associations/{configuredModelAlgorithmAssociationArn}", + "responseCode":200 + }, + "input":{"shape":"GetCollaborationConfiguredModelAlgorithmAssociationRequest"}, + "output":{"shape":"GetCollaborationConfiguredModelAlgorithmAssociationResponse"}, + "errors":[ + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ResourceNotFoundException"} + ], + "documentation":"

Returns information about the configured model algorithm association in a collaboration.

" + }, + "GetCollaborationMLInputChannel":{ + "name":"GetCollaborationMLInputChannel", + "http":{ + "method":"GET", + "requestUri":"/collaborations/{collaborationIdentifier}/ml-input-channels/{mlInputChannelArn}", + "responseCode":200 + }, + "input":{"shape":"GetCollaborationMLInputChannelRequest"}, + "output":{"shape":"GetCollaborationMLInputChannelResponse"}, + "errors":[ + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ResourceNotFoundException"} + ], + "documentation":"

Returns information about a specific ML input channel in a collaboration.

" + }, + "GetCollaborationTrainedModel":{ + "name":"GetCollaborationTrainedModel", + "http":{ + "method":"GET", + "requestUri":"/collaborations/{collaborationIdentifier}/trained-models/{trainedModelArn}", + "responseCode":200 + }, + "input":{"shape":"GetCollaborationTrainedModelRequest"}, + "output":{"shape":"GetCollaborationTrainedModelResponse"}, + "errors":[ + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ResourceNotFoundException"} + ], + "documentation":"

Returns information about a trained model in a collaboration.

" + }, "GetConfiguredAudienceModel":{ "name":"GetConfiguredAudienceModel", "http":{ @@ -216,6 +457,102 @@ ], "documentation":"

Returns information about a configured audience model policy.

" }, + "GetConfiguredModelAlgorithm":{ + "name":"GetConfiguredModelAlgorithm", + "http":{ + "method":"GET", + "requestUri":"/configured-model-algorithms/{configuredModelAlgorithmArn}", + "responseCode":200 + }, + "input":{"shape":"GetConfiguredModelAlgorithmRequest"}, + "output":{"shape":"GetConfiguredModelAlgorithmResponse"}, + "errors":[ + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ResourceNotFoundException"} + ], + "documentation":"

Returns information about a configured model algorithm.

" + }, + "GetConfiguredModelAlgorithmAssociation":{ + "name":"GetConfiguredModelAlgorithmAssociation", + "http":{ + "method":"GET", + "requestUri":"/memberships/{membershipIdentifier}/configured-model-algorithm-associations/{configuredModelAlgorithmAssociationArn}", + "responseCode":200 + }, + "input":{"shape":"GetConfiguredModelAlgorithmAssociationRequest"}, + "output":{"shape":"GetConfiguredModelAlgorithmAssociationResponse"}, + "errors":[ + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ResourceNotFoundException"} + ], + "documentation":"

Returns information about a configured model algorithm association.

" + }, + "GetMLConfiguration":{ + "name":"GetMLConfiguration", + "http":{ + "method":"GET", + "requestUri":"/memberships/{membershipIdentifier}/ml-configurations", + "responseCode":200 + }, + "input":{"shape":"GetMLConfigurationRequest"}, + "output":{"shape":"GetMLConfigurationResponse"}, + "errors":[ + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ResourceNotFoundException"} + ], + "documentation":"

Returns information about a specific ML configuration.

" + }, + "GetMLInputChannel":{ + "name":"GetMLInputChannel", + "http":{ + "method":"GET", + "requestUri":"/memberships/{membershipIdentifier}/ml-input-channels/{mlInputChannelArn}", + "responseCode":200 + }, + "input":{"shape":"GetMLInputChannelRequest"}, + "output":{"shape":"GetMLInputChannelResponse"}, + "errors":[ + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ResourceNotFoundException"} + ], + "documentation":"

Returns information about an ML input channel.

" + }, + "GetTrainedModel":{ + "name":"GetTrainedModel", + "http":{ + "method":"GET", + "requestUri":"/memberships/{membershipIdentifier}/trained-models/{trainedModelArn}", + "responseCode":200 + }, + "input":{"shape":"GetTrainedModelRequest"}, + "output":{"shape":"GetTrainedModelResponse"}, + "errors":[ + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ResourceNotFoundException"} + ], + "documentation":"

Returns information about a trained model.

" + }, + "GetTrainedModelInferenceJob":{ + "name":"GetTrainedModelInferenceJob", + "http":{ + "method":"GET", + "requestUri":"/memberships/{membershipIdentifier}/trained-model-inference-jobs/{trainedModelInferenceJobArn}", + "responseCode":200 + }, + "input":{"shape":"GetTrainedModelInferenceJobRequest"}, + "output":{"shape":"GetTrainedModelInferenceJobResponse"}, + "errors":[ + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ResourceNotFoundException"} + ], + "documentation":"

Returns information about a trained model inference job.

" + }, "GetTrainingDataset":{ "name":"GetTrainingDataset", "http":{ @@ -277,67 +614,232 @@ ], "documentation":"

Returns a list of audience models.

" }, - "ListConfiguredAudienceModels":{ - "name":"ListConfiguredAudienceModels", + "ListCollaborationConfiguredModelAlgorithmAssociations":{ + "name":"ListCollaborationConfiguredModelAlgorithmAssociations", "http":{ "method":"GET", - "requestUri":"/configured-audience-model", + "requestUri":"/collaborations/{collaborationIdentifier}/configured-model-algorithm-associations", "responseCode":200 }, - "input":{"shape":"ListConfiguredAudienceModelsRequest"}, - "output":{"shape":"ListConfiguredAudienceModelsResponse"}, + "input":{"shape":"ListCollaborationConfiguredModelAlgorithmAssociationsRequest"}, + "output":{"shape":"ListCollaborationConfiguredModelAlgorithmAssociationsResponse"}, "errors":[ {"shape":"ValidationException"}, {"shape":"AccessDeniedException"} ], - "documentation":"

Returns a list of the configured audience models.

" + "documentation":"

Returns a list of the configured model algorithm associations in a collaboration.

" }, - "ListTagsForResource":{ - "name":"ListTagsForResource", + "ListCollaborationMLInputChannels":{ + "name":"ListCollaborationMLInputChannels", "http":{ "method":"GET", - "requestUri":"/tags/{resourceArn}", + "requestUri":"/collaborations/{collaborationIdentifier}/ml-input-channels", "responseCode":200 }, - "input":{"shape":"ListTagsForResourceRequest"}, - "output":{"shape":"ListTagsForResourceResponse"}, + "input":{"shape":"ListCollaborationMLInputChannelsRequest"}, + "output":{"shape":"ListCollaborationMLInputChannelsResponse"}, "errors":[ {"shape":"ValidationException"}, - {"shape":"AccessDeniedException"}, - {"shape":"ResourceNotFoundException"} + {"shape":"AccessDeniedException"} ], - "documentation":"

Returns a list of tags for a provided resource.

" + "documentation":"

Returns a list of the ML input channels in a collaboration.

" }, - "ListTrainingDatasets":{ - "name":"ListTrainingDatasets", + "ListCollaborationTrainedModelExportJobs":{ + "name":"ListCollaborationTrainedModelExportJobs", "http":{ "method":"GET", - "requestUri":"/training-dataset", + "requestUri":"/collaborations/{collaborationIdentifier}/trained-models/{trainedModelArn}/export-jobs", "responseCode":200 }, - "input":{"shape":"ListTrainingDatasetsRequest"}, - "output":{"shape":"ListTrainingDatasetsResponse"}, + "input":{"shape":"ListCollaborationTrainedModelExportJobsRequest"}, + "output":{"shape":"ListCollaborationTrainedModelExportJobsResponse"}, "errors":[ {"shape":"ValidationException"}, {"shape":"AccessDeniedException"} ], - "documentation":"

Returns a list of training datasets.

" + "documentation":"

Returns a list of the export jobs for a trained model in a collaboration.

" }, - "PutConfiguredAudienceModelPolicy":{ - "name":"PutConfiguredAudienceModelPolicy", + "ListCollaborationTrainedModelInferenceJobs":{ + "name":"ListCollaborationTrainedModelInferenceJobs", "http":{ - "method":"PUT", - "requestUri":"/configured-audience-model/{configuredAudienceModelArn}/policy", + "method":"GET", + "requestUri":"/collaborations/{collaborationIdentifier}/trained-model-inference-jobs", "responseCode":200 }, - "input":{"shape":"PutConfiguredAudienceModelPolicyRequest"}, - "output":{"shape":"PutConfiguredAudienceModelPolicyResponse"}, + "input":{"shape":"ListCollaborationTrainedModelInferenceJobsRequest"}, + "output":{"shape":"ListCollaborationTrainedModelInferenceJobsResponse"}, "errors":[ {"shape":"ValidationException"}, - {"shape":"AccessDeniedException"}, - {"shape":"ResourceNotFoundException"} + {"shape":"AccessDeniedException"} ], - "documentation":"

Create or update the resource policy for a configured audience model.

", + "documentation":"

Returns a list of trained model inference jobs in a specified collaboration.

" + }, + "ListCollaborationTrainedModels":{ + "name":"ListCollaborationTrainedModels", + "http":{ + "method":"GET", + "requestUri":"/collaborations/{collaborationIdentifier}/trained-models", + "responseCode":200 + }, + "input":{"shape":"ListCollaborationTrainedModelsRequest"}, + "output":{"shape":"ListCollaborationTrainedModelsResponse"}, + "errors":[ + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"} + ], + "documentation":"

Returns a list of the trained models in a collaboration.

" + }, + "ListConfiguredAudienceModels":{ + "name":"ListConfiguredAudienceModels", + "http":{ + "method":"GET", + "requestUri":"/configured-audience-model", + "responseCode":200 + }, + "input":{"shape":"ListConfiguredAudienceModelsRequest"}, + "output":{"shape":"ListConfiguredAudienceModelsResponse"}, + "errors":[ + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"} + ], + "documentation":"

Returns a list of the configured audience models.

" + }, + "ListConfiguredModelAlgorithmAssociations":{ + "name":"ListConfiguredModelAlgorithmAssociations", + "http":{ + "method":"GET", + "requestUri":"/memberships/{membershipIdentifier}/configured-model-algorithm-associations", + "responseCode":200 + }, + "input":{"shape":"ListConfiguredModelAlgorithmAssociationsRequest"}, + "output":{"shape":"ListConfiguredModelAlgorithmAssociationsResponse"}, + "errors":[ + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"} + ], + "documentation":"

Returns a list of configured model algorithm associations.

" + }, + "ListConfiguredModelAlgorithms":{ + "name":"ListConfiguredModelAlgorithms", + "http":{ + "method":"GET", + "requestUri":"/configured-model-algorithms", + "responseCode":200 + }, + "input":{"shape":"ListConfiguredModelAlgorithmsRequest"}, + "output":{"shape":"ListConfiguredModelAlgorithmsResponse"}, + "errors":[ + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"} + ], + "documentation":"

Returns a list of configured model algorithms.

" + }, + "ListMLInputChannels":{ + "name":"ListMLInputChannels", + "http":{ + "method":"GET", + "requestUri":"/memberships/{membershipIdentifier}/ml-input-channels", + "responseCode":200 + }, + "input":{"shape":"ListMLInputChannelsRequest"}, + "output":{"shape":"ListMLInputChannelsResponse"}, + "errors":[ + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"} + ], + "documentation":"

Returns a list of ML input channels.

" + }, + "ListTagsForResource":{ + "name":"ListTagsForResource", + "http":{ + "method":"GET", + "requestUri":"/tags/{resourceArn}", + "responseCode":200 + }, + "input":{"shape":"ListTagsForResourceRequest"}, + "output":{"shape":"ListTagsForResourceResponse"}, + "errors":[ + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ResourceNotFoundException"} + ], + "documentation":"

Returns a list of tags for a provided resource.

" + }, + "ListTrainedModelInferenceJobs":{ + "name":"ListTrainedModelInferenceJobs", + "http":{ + "method":"GET", + "requestUri":"/memberships/{membershipIdentifier}/trained-model-inference-jobs", + "responseCode":200 + }, + "input":{"shape":"ListTrainedModelInferenceJobsRequest"}, + "output":{"shape":"ListTrainedModelInferenceJobsResponse"}, + "errors":[ + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"} + ], + "documentation":"

Returns a list of trained model inference jobs that match the request parameters.

" + }, + "ListTrainedModels":{ + "name":"ListTrainedModels", + "http":{ + "method":"GET", + "requestUri":"/memberships/{membershipIdentifier}/trained-models", + "responseCode":200 + }, + "input":{"shape":"ListTrainedModelsRequest"}, + "output":{"shape":"ListTrainedModelsResponse"}, + "errors":[ + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"} + ], + "documentation":"

Returns a list of trained models.

" + }, + "ListTrainingDatasets":{ + "name":"ListTrainingDatasets", + "http":{ + "method":"GET", + "requestUri":"/training-dataset", + "responseCode":200 + }, + "input":{"shape":"ListTrainingDatasetsRequest"}, + "output":{"shape":"ListTrainingDatasetsResponse"}, + "errors":[ + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"} + ], + "documentation":"

Returns a list of training datasets.

" + }, + "PutConfiguredAudienceModelPolicy":{ + "name":"PutConfiguredAudienceModelPolicy", + "http":{ + "method":"PUT", + "requestUri":"/configured-audience-model/{configuredAudienceModelArn}/policy", + "responseCode":200 + }, + "input":{"shape":"PutConfiguredAudienceModelPolicyRequest"}, + "output":{"shape":"PutConfiguredAudienceModelPolicyResponse"}, + "errors":[ + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ResourceNotFoundException"} + ], + "documentation":"

Create or update the resource policy for a configured audience model.

", + "idempotent":true + }, + "PutMLConfiguration":{ + "name":"PutMLConfiguration", + "http":{ + "method":"PUT", + "requestUri":"/memberships/{membershipIdentifier}/ml-configurations", + "responseCode":200 + }, + "input":{"shape":"PutMLConfigurationRequest"}, + "errors":[ + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"} + ], + "documentation":"

Assigns information about an ML configuration.

", "idempotent":true }, "StartAudienceExportJob":{ @@ -377,6 +879,42 @@ "documentation":"

Information necessary to start the audience generation job.

", "idempotent":true }, + "StartTrainedModelExportJob":{ + "name":"StartTrainedModelExportJob", + "http":{ + "method":"POST", + "requestUri":"/memberships/{membershipIdentifier}/trained-models/{trainedModelArn}/export-jobs", + "responseCode":200 + }, + "input":{"shape":"StartTrainedModelExportJobRequest"}, + "errors":[ + {"shape":"ConflictException"}, + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ResourceNotFoundException"} + ], + "documentation":"

Provides the information necessary to start a trained model export job.

", + "idempotent":true + }, + "StartTrainedModelInferenceJob":{ + "name":"StartTrainedModelInferenceJob", + "http":{ + "method":"POST", + "requestUri":"/memberships/{membershipIdentifier}/trained-model-inference-jobs", + "responseCode":200 + }, + "input":{"shape":"StartTrainedModelInferenceJobRequest"}, + "output":{"shape":"StartTrainedModelInferenceJobResponse"}, + "errors":[ + {"shape":"ConflictException"}, + {"shape":"ValidationException"}, + {"shape":"AccessDeniedException"}, + {"shape":"ResourceNotFoundException"}, + {"shape":"ServiceQuotaExceededException"} + ], + "documentation":"

Defines the information necessary to begin a trained model inference job.

", + "idempotent":true + }, "TagResource":{ "name":"TagResource", "http":{ @@ -449,6 +987,18 @@ "min":12, "pattern":"[0-9]{12}" }, + "AccountIdList":{ + "type":"list", + "member":{"shape":"String"}, + "max":5, + "min":1 + }, + "AlgorithmImage":{ + "type":"string", + "max":255, + "min":1, + "pattern":".*" + }, "AnalysisTemplateArn":{ "type":"string", "max":200, @@ -687,12 +1237,18 @@ "documentation":"

The relevance scores of the generated audience.

" }, "recallMetric":{ - "shape":"Double", + "shape":"AudienceQualityMetricsRecallMetricDouble", "documentation":"

The recall score of the generated audience. Recall is the percentage of the most similar users (by default, the most similar 20%) from a sample of the training data that are included in the seed audience by the audience generation job. Values range from 0-1, larger values indicate a better audience. A recall value approximately equal to the maximum bin size indicates that the audience model is equivalent to random selection.

" } }, "documentation":"

Metrics that describe the quality of the generated audience.

" }, + "AudienceQualityMetricsRecallMetricDouble":{ + "type":"double", + "box":true, + "max":1.0, + "min":0.0 + }, "AudienceSize":{ "type":"structure", "required":[ @@ -752,796 +1308,3166 @@ "type":"boolean", "box":true }, - "ColumnName":{ - "type":"string", - "max":128, - "min":1, - "pattern":"[a-zA-Z0-9_](([a-zA-Z0-9_ ]+-)*([a-zA-Z0-9_ ]+))?" - }, - "ColumnSchema":{ + "CancelTrainedModelInferenceJobRequest":{ "type":"structure", "required":[ - "columnName", - "columnTypes" + "membershipIdentifier", + "trainedModelInferenceJobArn" ], "members":{ - "columnName":{ - "shape":"ColumnName", - "documentation":"

The name of a column.

" + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the trained model inference job that you want to cancel.

", + "location":"uri", + "locationName":"membershipIdentifier" }, - "columnTypes":{ - "shape":"ColumnTypeList", - "documentation":"

The data type of column.

" + "trainedModelInferenceJobArn":{ + "shape":"TrainedModelInferenceJobArn", + "documentation":"

The Amazon Resource Name (ARN) of the trained model inference job that you want to cancel.

", + "location":"uri", + "locationName":"trainedModelInferenceJobArn" } - }, - "documentation":"

Metadata for a column.

" - }, - "ColumnType":{ - "type":"string", - "enum":[ - "USER_ID", - "ITEM_ID", - "TIMESTAMP", - "CATEGORICAL_FEATURE", - "NUMERICAL_FEATURE" - ] - }, - "ColumnTypeList":{ - "type":"list", - "member":{"shape":"ColumnType"}, - "max":1, - "min":1 - }, - "ConfiguredAudienceModelArn":{ - "type":"string", - "max":2048, - "min":20, - "pattern":"arn:aws[-a-z]*:cleanrooms-ml:[-a-z0-9]+:[0-9]{12}:configured-audience-model/[-a-zA-Z0-9_/.]+" - }, - "ConfiguredAudienceModelList":{ - "type":"list", - "member":{"shape":"ConfiguredAudienceModelSummary"} + } }, - "ConfiguredAudienceModelOutputConfig":{ + "CancelTrainedModelRequest":{ "type":"structure", "required":[ - "destination", - "roleArn" + "membershipIdentifier", + "trainedModelArn" ], "members":{ - "destination":{"shape":"AudienceDestination"}, - "roleArn":{ - "shape":"IamRoleArn", - "documentation":"

The ARN of the IAM role that can write the Amazon S3 bucket.

" + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the trained model job that you want to cancel.

", + "location":"uri", + "locationName":"membershipIdentifier" + }, + "trainedModelArn":{ + "shape":"TrainedModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the trained model job that you want to cancel.

", + "location":"uri", + "locationName":"trainedModelArn" } - }, - "documentation":"

Configuration information necessary for the configure audience model output.

" + } }, - "ConfiguredAudienceModelStatus":{ - "type":"string", - "enum":["ACTIVE"] + "CollaborationConfiguredModelAlgorithmAssociationList":{ + "type":"list", + "member":{"shape":"CollaborationConfiguredModelAlgorithmAssociationSummary"} }, - "ConfiguredAudienceModelSummary":{ + "CollaborationConfiguredModelAlgorithmAssociationSummary":{ "type":"structure", "required":[ "createTime", "updateTime", + "configuredModelAlgorithmAssociationArn", "name", - "audienceModelArn", - "outputConfig", - "configuredAudienceModelArn", - "status" + "membershipIdentifier", + "collaborationIdentifier", + "configuredModelAlgorithmArn", + "creatorAccountId" ], "members":{ "createTime":{ "shape":"SyntheticTimestamp_date_time", - "documentation":"

The time at which the configured audience model was created.

" + "documentation":"

The time at which the configured model algorithm association was created.

" }, "updateTime":{ "shape":"SyntheticTimestamp_date_time", - "documentation":"

The most recent time at which the configured audience model was updated.

" + "documentation":"

The most recent time at which the configured model algorithm association was updated.

" + }, + "configuredModelAlgorithmAssociationArn":{ + "shape":"ConfiguredModelAlgorithmAssociationArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured model algorithm association.

" }, "name":{ "shape":"NameString", - "documentation":"

The name of the configured audience model.

" - }, - "audienceModelArn":{ - "shape":"AudienceModelArn", - "documentation":"

The Amazon Resource Name (ARN) of the audience model that was used to create the configured audience model.

" - }, - "outputConfig":{ - "shape":"ConfiguredAudienceModelOutputConfig", - "documentation":"

The output configuration of the configured audience model.

" + "documentation":"

The name of the configured model algorithm association.

" }, "description":{ "shape":"ResourceDescription", - "documentation":"

The description of the configured audience model.

" + "documentation":"

The description of the configured model algorithm association.

" }, - "configuredAudienceModelArn":{ - "shape":"ConfiguredAudienceModelArn", - "documentation":"

The Amazon Resource Name (ARN) of the configured audience model that you are interested in.

" + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the member that created the configured model algorithm association.

" }, - "status":{ - "shape":"ConfiguredAudienceModelStatus", - "documentation":"

The status of the configured audience model.

" + "collaborationIdentifier":{ + "shape":"UUID", + "documentation":"

The collaboration ID of the collaboration that contains the configured model algorithm association.

" + }, + "configuredModelAlgorithmArn":{ + "shape":"ConfiguredModelAlgorithmArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured model algorithm that is associated to the collaboration.

" + }, + "creatorAccountId":{ + "shape":"AccountId", + "documentation":"

The account ID of the member that created the configured model algorithm association.

" } }, - "documentation":"

Information about the configured audience model.

" + "documentation":"

Provides summary information about a configured model algorithm in a collaboration.

" }, - "ConflictException":{ - "type":"structure", - "required":["message"], - "members":{ - "message":{"shape":"String"} - }, - "documentation":"

You can't complete this action because another resource depends on this resource.

", - "error":{ - "httpStatusCode":409, - "senderFault":true - }, - "exception":true - }, - "CreateAudienceModelRequest":{ + "CollaborationMLInputChannelSummary":{ "type":"structure", "required":[ + "createTime", + "updateTime", + "membershipIdentifier", + "collaborationIdentifier", "name", - "trainingDatasetArn" + "configuredModelAlgorithmAssociations", + "mlInputChannelArn", + "status", + "creatorAccountId" ], "members":{ - "trainingDataStartTime":{ + "createTime":{ "shape":"SyntheticTimestamp_date_time", - "documentation":"

The start date and time of the training window.

" + "documentation":"

The time at which the ML input channel was created.

" }, - "trainingDataEndTime":{ + "updateTime":{ "shape":"SyntheticTimestamp_date_time", - "documentation":"

The end date and time of the training window.

" + "documentation":"

The most recent time at which the ML input channel was updated.

" + }, + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the membership that contains the ML input channel.

" + }, + "collaborationIdentifier":{ + "shape":"UUID", + "documentation":"

The collaboration ID of the collaboration that contains the ML input channel.

" }, "name":{ "shape":"NameString", - "documentation":"

The name of the audience model resource.

" + "documentation":"

The name of the ML input channel.

" }, - "trainingDatasetArn":{ - "shape":"TrainingDatasetArn", - "documentation":"

The Amazon Resource Name (ARN) of the training dataset for this audience model.

" + "configuredModelAlgorithmAssociations":{ + "shape":"CollaborationMLInputChannelSummaryConfiguredModelAlgorithmAssociationsList", + "documentation":"

The associated configured model algorithms used to create the ML input channel.

" }, - "kmsKeyArn":{ - "shape":"KmsKeyArn", - "documentation":"

The Amazon Resource Name (ARN) of the KMS key. This key is used to encrypt and decrypt customer-owned data in the trained ML model and the associated data.

" + "mlInputChannelArn":{ + "shape":"MLInputChannelArn", + "documentation":"

The Amazon Resource Name (ARN) of the ML input channel.

" }, - "tags":{ - "shape":"TagMap", - "documentation":"

The optional metadata that you apply to the resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

The following basic restrictions apply to tags:

" + "status":{ + "shape":"MLInputChannelStatus", + "documentation":"

The status of the ML input channel.

" + }, + "creatorAccountId":{ + "shape":"AccountId", + "documentation":"

The account ID of the member who created the ML input channel.

" }, "description":{ "shape":"ResourceDescription", - "documentation":"

The description of the audience model.

" + "documentation":"

The description of the ML input channel.

" } - } + }, + "documentation":"

Provides summary information about an ML input channel in a collaboration.

" }, - "CreateAudienceModelResponse":{ - "type":"structure", - "required":["audienceModelArn"], - "members":{ - "audienceModelArn":{ - "shape":"AudienceModelArn", - "documentation":"

The Amazon Resource Name (ARN) of the audience model.

" - } - } + "CollaborationMLInputChannelSummaryConfiguredModelAlgorithmAssociationsList":{ + "type":"list", + "member":{"shape":"ConfiguredModelAlgorithmAssociationArn"}, + "max":1, + "min":1 }, - "CreateConfiguredAudienceModelRequest":{ + "CollaborationMLInputChannelsList":{ + "type":"list", + "member":{"shape":"CollaborationMLInputChannelSummary"} + }, + "CollaborationTrainedModelExportJobList":{ + "type":"list", + "member":{"shape":"CollaborationTrainedModelExportJobSummary"} + }, + "CollaborationTrainedModelExportJobSummary":{ "type":"structure", "required":[ + "createTime", + "updateTime", "name", - "audienceModelArn", - "outputConfig", - "sharedAudienceMetrics" + "outputConfiguration", + "status", + "creatorAccountId", + "trainedModelArn", + "membershipIdentifier", + "collaborationIdentifier" ], "members":{ + "createTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The time at which the trained model export job was created.

" + }, + "updateTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The most recent time at which the trained model export job was updated.

" + }, "name":{ "shape":"NameString", - "documentation":"

The name of the configured audience model.

" - }, - "audienceModelArn":{ - "shape":"AudienceModelArn", - "documentation":"

The Amazon Resource Name (ARN) of the audience model to use for the configured audience model.

" + "documentation":"

The name of the trained model export job.

" }, - "outputConfig":{ - "shape":"ConfiguredAudienceModelOutputConfig", - "documentation":"

Configure the Amazon S3 location and IAM Role for audiences created using this configured audience model. Each audience will have a unique location. The IAM Role must have s3:PutObject permission on the destination Amazon S3 location. If the destination is protected with Amazon S3 KMS-SSE, then the Role must also have the required KMS permissions.

" + "outputConfiguration":{"shape":"TrainedModelExportOutputConfiguration"}, + "status":{ + "shape":"TrainedModelExportJobStatus", + "documentation":"

The status of the trained model.

" }, + "statusDetails":{"shape":"StatusDetails"}, "description":{ "shape":"ResourceDescription", - "documentation":"

The description of the configured audience model.

" - }, - "sharedAudienceMetrics":{ - "shape":"MetricsList", - "documentation":"

Whether audience metrics are shared.

" + "documentation":"

The description of the trained model.

" }, - "minMatchingSeedSize":{ - "shape":"MinMatchingSeedSize", - "documentation":"

The minimum number of users from the seed audience that must match with users in the training data of the audience model. The default value is 500.

" + "creatorAccountId":{ + "shape":"AccountId", + "documentation":"

The account ID of the member that created the trained model.

" }, - "audienceSizeConfig":{ - "shape":"AudienceSizeConfig", - "documentation":"

Configure the list of output sizes of audiences that can be created using this configured audience model. A request to StartAudienceGenerationJob that uses this configured audience model must have an audienceSize selected from this list. You can use the ABSOLUTE AudienceSize to configure out audience sizes using the count of identifiers in the output. You can use the Percentage AudienceSize to configure sizes in the range 1-100 percent.

" + "trainedModelArn":{ + "shape":"TrainedModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the trained model that is being exported.

" }, - "tags":{ - "shape":"TagMap", - "documentation":"

The optional metadata that you apply to the resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

The following basic restrictions apply to tags:

" + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the member that created the trained model export job.

" }, - "childResourceTagOnCreatePolicy":{ - "shape":"TagOnCreatePolicy", - "documentation":"

Configure how the service tags audience generation jobs created using this configured audience model. If you specify NONE, the tags from the StartAudienceGenerationJob request determine the tags of the audience generation job. If you specify FROM_PARENT_RESOURCE, the audience generation job inherits the tags from the configured audience model, by default. Tags in the StartAudienceGenerationJob will override the default.

When the client is in a different account than the configured audience model, the tags from the client are never applied to a resource in the caller's account.

" + "collaborationIdentifier":{ + "shape":"UUID", + "documentation":"

The collaboration ID of the collaboration that contains the trained model export job.

" } - } + }, + "documentation":"

Provides summary information about a trained model export job in a collaboration.

" }, - "CreateConfiguredAudienceModelResponse":{ - "type":"structure", - "required":["configuredAudienceModelArn"], - "members":{ - "configuredAudienceModelArn":{ - "shape":"ConfiguredAudienceModelArn", - "documentation":"

The Amazon Resource Name (ARN) of the configured audience model.

" - } - } + "CollaborationTrainedModelInferenceJobList":{ + "type":"list", + "member":{"shape":"CollaborationTrainedModelInferenceJobSummary"} }, - "CreateTrainingDatasetRequest":{ + "CollaborationTrainedModelInferenceJobSummary":{ "type":"structure", "required":[ + "trainedModelInferenceJobArn", + "membershipIdentifier", + "trainedModelArn", + "collaborationIdentifier", + "status", + "outputConfiguration", "name", - "roleArn", - "trainingData" + "createTime", + "updateTime", + "creatorAccountId" ], "members":{ - "name":{ - "shape":"NameString", - "documentation":"

The name of the training dataset. This name must be unique in your account and region.

" + "trainedModelInferenceJobArn":{ + "shape":"TrainedModelInferenceJobArn", + "documentation":"

The Amazon Resource Name (ARN) of the trained model inference job.

" }, - "roleArn":{ - "shape":"IamRoleArn", - "documentation":"

The ARN of the IAM role that Clean Rooms ML can assume to read the data referred to in the dataSource field of each dataset.

Passing a role across AWS accounts is not allowed. If you pass a role that isn't in your account, you get an AccessDeniedException error.

" + "configuredModelAlgorithmAssociationArn":{ + "shape":"ConfiguredModelAlgorithmAssociationArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured model algorithm association that is used for the trained model inference job.

" }, - "trainingData":{ - "shape":"CreateTrainingDatasetRequestTrainingDataList", - "documentation":"

An array of information that lists the Dataset objects, which specifies the dataset type and details on its location and schema. You must provide a role that has read access to these tables.

" + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the membership that contains the trained model inference job.

" }, - "tags":{ - "shape":"TagMap", - "documentation":"

The optional metadata that you apply to the resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

The following basic restrictions apply to tags:

" + "trainedModelArn":{ + "shape":"TrainedModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the trained model that is used for the trained model inference job.

" + }, + "collaborationIdentifier":{ + "shape":"UUID", + "documentation":"

The collaboration ID of the collaboration that contains the trained model inference job.

" + }, + "status":{ + "shape":"TrainedModelInferenceJobStatus", + "documentation":"

The status of the trained model inference job.

" + }, + "outputConfiguration":{ + "shape":"InferenceOutputConfiguration", + "documentation":"

Returns output configuration information for the trained model inference job.

" + }, + "name":{ + "shape":"NameString", + "documentation":"

The name of the trained model inference job.

" }, "description":{ "shape":"ResourceDescription", - "documentation":"

The description of the training dataset.

" + "documentation":"

The description of the trained model inference job.

" + }, + "metricsStatus":{ + "shape":"MetricsStatus", + "documentation":"

the trained model inference job metrics status.

" + }, + "metricsStatusDetails":{ + "shape":"String", + "documentation":"

Details about the metrics status for trained model inference job.

" + }, + "logsStatus":{ + "shape":"LogsStatus", + "documentation":"

The trained model inference job logs status.

" + }, + "logsStatusDetails":{ + "shape":"String", + "documentation":"

Details about the logs status for the trained model inference job.

" + }, + "createTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The time at which the trained model inference job was created.

" + }, + "updateTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The most recent time at which the trained model inference job was updated.

" + }, + "creatorAccountId":{ + "shape":"AccountId", + "documentation":"

The account ID that created the trained model inference job.

" } - } + }, + "documentation":"

Provides summary information about a trained model inference job in a collaboration.

" }, - "CreateTrainingDatasetRequestTrainingDataList":{ + "CollaborationTrainedModelList":{ "type":"list", - "member":{"shape":"Dataset"}, - "max":1, - "min":1 - }, - "CreateTrainingDatasetResponse":{ - "type":"structure", - "required":["trainingDatasetArn"], - "members":{ - "trainingDatasetArn":{ - "shape":"TrainingDatasetArn", - "documentation":"

The Amazon Resource Name (ARN) of the training dataset resource.

" - } - } - }, - "DataSource":{ - "type":"structure", - "required":["glueDataSource"], - "members":{ - "glueDataSource":{ - "shape":"GlueDataSource", - "documentation":"

A GlueDataSource object that defines the catalog ID, database name, and table name for the training data.

" - } - }, - "documentation":"

Defines information about the Glue data source that contains the training data.

" + "member":{"shape":"CollaborationTrainedModelSummary"} }, - "Dataset":{ + "CollaborationTrainedModelSummary":{ "type":"structure", "required":[ - "type", - "inputConfig" + "createTime", + "updateTime", + "trainedModelArn", + "name", + "membershipIdentifier", + "collaborationIdentifier", + "status", + "configuredModelAlgorithmAssociationArn", + "creatorAccountId" ], "members":{ - "type":{ - "shape":"DatasetType", - "documentation":"

What type of information is found in the dataset.

" + "createTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The time at which the trained model was created.

" }, - "inputConfig":{ - "shape":"DatasetInputConfig", - "documentation":"

A DatasetInputConfig object that defines the data source and schema mapping.

" + "updateTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The most recent time at which the trained model was updated.

" + }, + "trainedModelArn":{ + "shape":"TrainedModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the trained model.

" + }, + "name":{ + "shape":"NameString", + "documentation":"

The name of the trained model.

" + }, + "description":{ + "shape":"ResourceDescription", + "documentation":"

The description of the trained model.

" + }, + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the member that created the trained model.

" + }, + "collaborationIdentifier":{ + "shape":"UUID", + "documentation":"

The collaboration ID of the collaboration that contains the trained model.

" + }, + "status":{ + "shape":"TrainedModelStatus", + "documentation":"

The status of the trained model.

" + }, + "configuredModelAlgorithmAssociationArn":{ + "shape":"ConfiguredModelAlgorithmAssociationArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured model algorithm association that is used for this trained model.

" + }, + "creatorAccountId":{ + "shape":"AccountId", + "documentation":"

The account ID of the member that created the trained model.

" } }, - "documentation":"

Defines where the training dataset is located, what type of data it contains, and how to access the data.

" + "documentation":"

Provides summary information about a trained model in a collaboration.

" }, - "DatasetInputConfig":{ + "ColumnName":{ + "type":"string", + "max":128, + "min":1, + "pattern":"[a-zA-Z0-9_](([a-zA-Z0-9_ ]+-)*([a-zA-Z0-9_ ]+))?" + }, + "ColumnSchema":{ "type":"structure", "required":[ - "schema", - "dataSource" + "columnName", + "columnTypes" ], "members":{ - "schema":{ - "shape":"DatasetInputConfigSchemaList", - "documentation":"

The schema information for the training data.

" + "columnName":{ + "shape":"ColumnName", + "documentation":"

The name of a column.

" }, - "dataSource":{ - "shape":"DataSource", - "documentation":"

A DataSource object that specifies the Glue data source for the training data.

" + "columnTypes":{ + "shape":"ColumnTypeList", + "documentation":"

The data type of column.

" } }, - "documentation":"

Defines the Glue data source and schema mapping information.

" - }, - "DatasetInputConfigSchemaList":{ - "type":"list", - "member":{"shape":"ColumnSchema"}, - "max":100, - "min":1 - }, - "DatasetList":{ - "type":"list", - "member":{"shape":"Dataset"} + "documentation":"

Metadata for a column.

" }, - "DatasetType":{ + "ColumnType":{ "type":"string", - "enum":["INTERACTIONS"] + "enum":[ + "USER_ID", + "ITEM_ID", + "TIMESTAMP", + "CATEGORICAL_FEATURE", + "NUMERICAL_FEATURE" + ] }, - "DeleteAudienceGenerationJobRequest":{ - "type":"structure", - "required":["audienceGenerationJobArn"], - "members":{ - "audienceGenerationJobArn":{ - "shape":"AudienceGenerationJobArn", - "documentation":"

The Amazon Resource Name (ARN) of the audience generation job that you want to delete.

", - "location":"uri", - "locationName":"audienceGenerationJobArn" - } - } + "ColumnTypeList":{ + "type":"list", + "member":{"shape":"ColumnType"}, + "max":1, + "min":1 }, - "DeleteAudienceModelRequest":{ + "ComputeConfiguration":{ "type":"structure", - "required":["audienceModelArn"], "members":{ - "audienceModelArn":{ - "shape":"AudienceModelArn", - "documentation":"

The Amazon Resource Name (ARN) of the audience model that you want to delete.

", - "location":"uri", - "locationName":"audienceModelArn" + "worker":{ + "shape":"WorkerComputeConfiguration", + "documentation":"

The worker instances that will perform the compute work.

" } - } + }, + "documentation":"

Provides configuration information for the instances that will perform the compute work.

", + "union":true }, - "DeleteConfiguredAudienceModelPolicyRequest":{ - "type":"structure", - "required":["configuredAudienceModelArn"], - "members":{ - "configuredAudienceModelArn":{ - "shape":"ConfiguredAudienceModelArn", - "documentation":"

The Amazon Resource Name (ARN) of the configured audience model policy that you want to delete.

", - "location":"uri", - "locationName":"configuredAudienceModelArn" - } - } + "ConfiguredAudienceModelArn":{ + "type":"string", + "max":2048, + "min":20, + "pattern":"arn:aws[-a-z]*:cleanrooms-ml:[-a-z0-9]+:[0-9]{12}:configured-audience-model/[-a-zA-Z0-9_/.]+" }, - "DeleteConfiguredAudienceModelRequest":{ - "type":"structure", - "required":["configuredAudienceModelArn"], - "members":{ - "configuredAudienceModelArn":{ - "shape":"ConfiguredAudienceModelArn", - "documentation":"

The Amazon Resource Name (ARN) of the configured audience model that you want to delete.

", - "location":"uri", - "locationName":"configuredAudienceModelArn" - } - } + "ConfiguredAudienceModelList":{ + "type":"list", + "member":{"shape":"ConfiguredAudienceModelSummary"} }, - "DeleteTrainingDatasetRequest":{ + "ConfiguredAudienceModelOutputConfig":{ "type":"structure", - "required":["trainingDatasetArn"], + "required":[ + "destination", + "roleArn" + ], "members":{ - "trainingDatasetArn":{ - "shape":"TrainingDatasetArn", - "documentation":"

The Amazon Resource Name (ARN) of the training dataset that you want to delete.

", - "location":"uri", - "locationName":"trainingDatasetArn" + "destination":{"shape":"AudienceDestination"}, + "roleArn":{ + "shape":"IamRoleArn", + "documentation":"

The ARN of the IAM role that can write the Amazon S3 bucket.

" } - } - }, - "Double":{ - "type":"double", - "box":true + }, + "documentation":"

Configuration information necessary for the configure audience model output.

" }, - "GetAudienceGenerationJobRequest":{ - "type":"structure", - "required":["audienceGenerationJobArn"], - "members":{ - "audienceGenerationJobArn":{ - "shape":"AudienceGenerationJobArn", - "documentation":"

The Amazon Resource Name (ARN) of the audience generation job that you are interested in.

", - "location":"uri", - "locationName":"audienceGenerationJobArn" - } - } + "ConfiguredAudienceModelStatus":{ + "type":"string", + "enum":["ACTIVE"] }, - "GetAudienceGenerationJobResponse":{ + "ConfiguredAudienceModelSummary":{ "type":"structure", "required":[ "createTime", "updateTime", - "audienceGenerationJobArn", "name", - "status", - "configuredAudienceModelArn" + "audienceModelArn", + "outputConfig", + "configuredAudienceModelArn", + "status" ], "members":{ "createTime":{ "shape":"SyntheticTimestamp_date_time", - "documentation":"

The time at which the audience generation job was created.

" + "documentation":"

The time at which the configured audience model was created.

" }, "updateTime":{ "shape":"SyntheticTimestamp_date_time", - "documentation":"

The most recent time at which the audience generation job was updated.

" - }, - "audienceGenerationJobArn":{ - "shape":"AudienceGenerationJobArn", - "documentation":"

The Amazon Resource Name (ARN) of the audience generation job.

" + "documentation":"

The most recent time at which the configured audience model was updated.

" }, "name":{ "shape":"NameString", - "documentation":"

The name of the audience generation job.

" + "documentation":"

The name of the configured audience model.

" }, - "description":{ - "shape":"ResourceDescription", - "documentation":"

The description of the audience generation job.

" + "audienceModelArn":{ + "shape":"AudienceModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the audience model that was used to create the configured audience model.

" }, - "status":{ - "shape":"AudienceGenerationJobStatus", - "documentation":"

The status of the audience generation job.

" + "outputConfig":{ + "shape":"ConfiguredAudienceModelOutputConfig", + "documentation":"

The output configuration of the configured audience model.

" }, - "statusDetails":{ - "shape":"StatusDetails", - "documentation":"

Details about the status of the audience generation job.

" + "description":{ + "shape":"ResourceDescription", + "documentation":"

The description of the configured audience model.

" }, "configuredAudienceModelArn":{ "shape":"ConfiguredAudienceModelArn", - "documentation":"

The Amazon Resource Name (ARN) of the configured audience model used for this audience generation job.

" - }, - "seedAudience":{ - "shape":"AudienceGenerationJobDataSource", - "documentation":"

The seed audience that was used for this audience generation job. This field will be null if the account calling the API is the account that started this audience generation job.

" - }, - "includeSeedInOutput":{ - "shape":"Boolean", - "documentation":"

Configure whether the seed users are included in the output audience. By default, Clean Rooms ML removes seed users from the output audience. If you specify TRUE, the seed users will appear first in the output. Clean Rooms ML does not explicitly reveal whether a user was in the seed, but the recipient of the audience will know that the first minimumSeedSize count of users are from the seed.

" - }, - "collaborationId":{ - "shape":"UUID", - "documentation":"

The identifier of the collaboration that this audience generation job is associated with.

" - }, - "metrics":{ - "shape":"AudienceQualityMetrics", - "documentation":"

The relevance scores for different audience sizes and the recall score of the generated audience.

" - }, - "startedBy":{ - "shape":"AccountId", - "documentation":"

The AWS account that started this audience generation job.

" - }, - "tags":{ - "shape":"TagMap", - "documentation":"

The tags that are associated to this audience generation job.

" + "documentation":"

The Amazon Resource Name (ARN) of the configured audience model that you are interested in.

" }, - "protectedQueryIdentifier":{ - "shape":"String", - "documentation":"

The unique identifier of the protected query for this audience generation job.

" + "status":{ + "shape":"ConfiguredAudienceModelStatus", + "documentation":"

The status of the configured audience model.

" } - } + }, + "documentation":"

Information about the configured audience model.

" }, - "GetAudienceModelRequest":{ - "type":"structure", - "required":["audienceModelArn"], - "members":{ - "audienceModelArn":{ - "shape":"AudienceModelArn", - "documentation":"

The Amazon Resource Name (ARN) of the audience model that you are interested in.

", - "location":"uri", - "locationName":"audienceModelArn" - } - } + "ConfiguredModelAlgorithmArn":{ + "type":"string", + "max":2048, + "min":20, + "pattern":"arn:aws[-a-z]*:cleanrooms-ml:[-a-z0-9]+:[0-9]{12}:configured-model-algorithm/[-a-zA-Z0-9_/.]+" }, - "GetAudienceModelResponse":{ + "ConfiguredModelAlgorithmAssociationArn":{ + "type":"string", + "max":2048, + "min":20, + "pattern":"arn:aws[-a-z]*:cleanrooms-ml:[-a-z0-9]+:[0-9]{12}:(membership/[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}/)?configured-model-algorithm-association/[-a-zA-Z0-9_/.]+" + }, + "ConfiguredModelAlgorithmAssociationList":{ + "type":"list", + "member":{"shape":"ConfiguredModelAlgorithmAssociationSummary"} + }, + "ConfiguredModelAlgorithmAssociationSummary":{ "type":"structure", "required":[ "createTime", "updateTime", - "audienceModelArn", + "configuredModelAlgorithmAssociationArn", + "configuredModelAlgorithmArn", "name", - "trainingDatasetArn", - "status" + "membershipIdentifier", + "collaborationIdentifier" ], "members":{ "createTime":{ "shape":"SyntheticTimestamp_date_time", - "documentation":"

The time at which the audience model was created.

" + "documentation":"

The time at which the configured model algorithm association was created.

" }, "updateTime":{ "shape":"SyntheticTimestamp_date_time", - "documentation":"

The most recent time at which the audience model was updated.

" - }, - "trainingDataStartTime":{ - "shape":"SyntheticTimestamp_date_time", - "documentation":"

The start date specified for the training window.

" + "documentation":"

The most recent time at which the configured model algorithm association was updated.

" }, - "trainingDataEndTime":{ - "shape":"SyntheticTimestamp_date_time", - "documentation":"

The end date specified for the training window.

" + "configuredModelAlgorithmAssociationArn":{ + "shape":"ConfiguredModelAlgorithmAssociationArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured model algorithm association.

" }, - "audienceModelArn":{ - "shape":"AudienceModelArn", - "documentation":"

The Amazon Resource Name (ARN) of the audience model.

" + "configuredModelAlgorithmArn":{ + "shape":"ConfiguredModelAlgorithmArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured model algorithm that is being associated.

" }, "name":{ "shape":"NameString", - "documentation":"

The name of the audience model.

" + "documentation":"

The name of the configured model algorithm association.

" }, - "trainingDatasetArn":{ - "shape":"TrainingDatasetArn", - "documentation":"

The Amazon Resource Name (ARN) of the training dataset that was used for this audience model.

" + "description":{ + "shape":"ResourceDescription", + "documentation":"

The description of the configured model algorithm association.

" }, - "status":{ - "shape":"AudienceModelStatus", - "documentation":"

The status of the audience model.

" + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the member that created the configured model algorithm association.

" }, - "statusDetails":{ - "shape":"StatusDetails", - "documentation":"

Details about the status of the audience model.

" + "collaborationIdentifier":{ + "shape":"UUID", + "documentation":"

The collaboration ID of the collaboration that contains the configured model algorithm association.

" + } + }, + "documentation":"

Provides summary information about the configured model algorithm association.

" + }, + "ConfiguredModelAlgorithmList":{ + "type":"list", + "member":{"shape":"ConfiguredModelAlgorithmSummary"} + }, + "ConfiguredModelAlgorithmSummary":{ + "type":"structure", + "required":[ + "createTime", + "updateTime", + "configuredModelAlgorithmArn", + "name" + ], + "members":{ + "createTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The time at which the configured model algorithm was created.

" }, - "kmsKeyArn":{ - "shape":"KmsKeyArn", - "documentation":"

The KMS key ARN used for the audience model.

" + "updateTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The most recent time at which the configured model algorithm was updated.

" }, - "tags":{ - "shape":"TagMap", - "documentation":"

The tags that are assigned to the audience model.

" + "configuredModelAlgorithmArn":{ + "shape":"ConfiguredModelAlgorithmArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured model algorithm.

" + }, + "name":{ + "shape":"NameString", + "documentation":"

The name of the configured model algorithm.

" }, "description":{ "shape":"ResourceDescription", - "documentation":"

The description of the audience model.

" + "documentation":"

The description of the configured model algorithm.

" } - } + }, + "documentation":"

Provides summary information about a configured model algorithm.

" }, - "GetConfiguredAudienceModelPolicyRequest":{ + "ConflictException":{ "type":"structure", - "required":["configuredAudienceModelArn"], + "required":["message"], "members":{ - "configuredAudienceModelArn":{ - "shape":"ConfiguredAudienceModelArn", - "documentation":"

The Amazon Resource Name (ARN) of the configured audience model that you are interested in.

", - "location":"uri", + "message":{"shape":"String"} + }, + "documentation":"

You can't complete this action because another resource depends on this resource.

", + "error":{ + "httpStatusCode":409, + "senderFault":true + }, + "exception":true + }, + "ContainerArgument":{ + "type":"string", + "max":256, + "min":1, + "pattern":".*" + }, + "ContainerArguments":{ + "type":"list", + "member":{"shape":"ContainerArgument"}, + "max":100, + "min":1 + }, + "ContainerConfig":{ + "type":"structure", + "required":["imageUri"], + "members":{ + "imageUri":{ + "shape":"AlgorithmImage", + "documentation":"

The registry path of the docker image that contains the algorithm. Clean Rooms ML supports both registry/repository[:tag] and registry/repositry[@digest] image path formats. For more information about using images in Clean Rooms ML, see the Sagemaker API reference.

" + }, + "entrypoint":{ + "shape":"ContainerEntrypoint", + "documentation":"

The entrypoint script for a Docker container used to run a training job. This script takes precedence over the default train processing instructions. See How Amazon SageMaker Runs Your Training Image for additional information. For more information, see How Sagemaker runs your training image.

" + }, + "arguments":{ + "shape":"ContainerArguments", + "documentation":"

The arguments for a container used to run a training job. See How Amazon SageMaker Runs Your Training Image for additional information. For more information, see How Sagemaker runs your training image.

" + }, + "metricDefinitions":{ + "shape":"MetricDefinitionList", + "documentation":"

A list of metric definition objects. Each object specifies the metric name and regular expressions used to parse algorithm logs. Amazon Web Services Clean Rooms ML publishes each metric to all members' Amazon CloudWatch using IAM role configured in PutMLConfiguration.

" + } + }, + "documentation":"

Provides configuration information for the dockerized container where the model algorithm is stored.

" + }, + "ContainerEntrypoint":{ + "type":"list", + "member":{"shape":"ContainerEntrypointString"}, + "max":100, + "min":1 + }, + "ContainerEntrypointString":{ + "type":"string", + "max":256, + "min":1, + "pattern":".*" + }, + "CreateAudienceModelRequest":{ + "type":"structure", + "required":[ + "name", + "trainingDatasetArn" + ], + "members":{ + "trainingDataStartTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The start date and time of the training window.

" + }, + "trainingDataEndTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The end date and time of the training window.

" + }, + "name":{ + "shape":"NameString", + "documentation":"

The name of the audience model resource.

" + }, + "trainingDatasetArn":{ + "shape":"TrainingDatasetArn", + "documentation":"

The Amazon Resource Name (ARN) of the training dataset for this audience model.

" + }, + "kmsKeyArn":{ + "shape":"KmsKeyArn", + "documentation":"

The Amazon Resource Name (ARN) of the KMS key. This key is used to encrypt and decrypt customer-owned data in the trained ML model and the associated data.

" + }, + "tags":{ + "shape":"TagMap", + "documentation":"

The optional metadata that you apply to the resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

The following basic restrictions apply to tags:

" + }, + "description":{ + "shape":"ResourceDescription", + "documentation":"

The description of the audience model.

" + } + } + }, + "CreateAudienceModelResponse":{ + "type":"structure", + "required":["audienceModelArn"], + "members":{ + "audienceModelArn":{ + "shape":"AudienceModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the audience model.

" + } + } + }, + "CreateConfiguredAudienceModelRequest":{ + "type":"structure", + "required":[ + "name", + "audienceModelArn", + "outputConfig", + "sharedAudienceMetrics" + ], + "members":{ + "name":{ + "shape":"NameString", + "documentation":"

The name of the configured audience model.

" + }, + "audienceModelArn":{ + "shape":"AudienceModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the audience model to use for the configured audience model.

" + }, + "outputConfig":{ + "shape":"ConfiguredAudienceModelOutputConfig", + "documentation":"

Configure the Amazon S3 location and IAM Role for audiences created using this configured audience model. Each audience will have a unique location. The IAM Role must have s3:PutObject permission on the destination Amazon S3 location. If the destination is protected with Amazon S3 KMS-SSE, then the Role must also have the required KMS permissions.

" + }, + "description":{ + "shape":"ResourceDescription", + "documentation":"

The description of the configured audience model.

" + }, + "sharedAudienceMetrics":{ + "shape":"MetricsList", + "documentation":"

Whether audience metrics are shared.

" + }, + "minMatchingSeedSize":{ + "shape":"MinMatchingSeedSize", + "documentation":"

The minimum number of users from the seed audience that must match with users in the training data of the audience model. The default value is 500.

" + }, + "audienceSizeConfig":{ + "shape":"AudienceSizeConfig", + "documentation":"

Configure the list of output sizes of audiences that can be created using this configured audience model. A request to StartAudienceGenerationJob that uses this configured audience model must have an audienceSize selected from this list. You can use the ABSOLUTE AudienceSize to configure out audience sizes using the count of identifiers in the output. You can use the Percentage AudienceSize to configure sizes in the range 1-100 percent.

" + }, + "tags":{ + "shape":"TagMap", + "documentation":"

The optional metadata that you apply to the resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

The following basic restrictions apply to tags:

" + }, + "childResourceTagOnCreatePolicy":{ + "shape":"TagOnCreatePolicy", + "documentation":"

Configure how the service tags audience generation jobs created using this configured audience model. If you specify NONE, the tags from the StartAudienceGenerationJob request determine the tags of the audience generation job. If you specify FROM_PARENT_RESOURCE, the audience generation job inherits the tags from the configured audience model, by default. Tags in the StartAudienceGenerationJob will override the default.

When the client is in a different account than the configured audience model, the tags from the client are never applied to a resource in the caller's account.

" + } + } + }, + "CreateConfiguredAudienceModelResponse":{ + "type":"structure", + "required":["configuredAudienceModelArn"], + "members":{ + "configuredAudienceModelArn":{ + "shape":"ConfiguredAudienceModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured audience model.

" + } + } + }, + "CreateConfiguredModelAlgorithmAssociationRequest":{ + "type":"structure", + "required":[ + "membershipIdentifier", + "configuredModelAlgorithmArn", + "name" + ], + "members":{ + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the member who is associating this configured model algorithm.

", + "location":"uri", + "locationName":"membershipIdentifier" + }, + "configuredModelAlgorithmArn":{ + "shape":"ConfiguredModelAlgorithmArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured model algorithm that you want to associate.

" + }, + "name":{ + "shape":"NameString", + "documentation":"

The name of the configured model algorithm association.

" + }, + "description":{ + "shape":"ResourceDescription", + "documentation":"

The description of the configured model algorithm association.

" + }, + "privacyConfiguration":{ + "shape":"PrivacyConfiguration", + "documentation":"

Specifies the privacy configuration information for the configured model algorithm association. This information includes the maximum data size that can be exported.

" + }, + "tags":{ + "shape":"TagMap", + "documentation":"

The optional metadata that you apply to the resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

The following basic restrictions apply to tags:

" + } + } + }, + "CreateConfiguredModelAlgorithmAssociationResponse":{ + "type":"structure", + "required":["configuredModelAlgorithmAssociationArn"], + "members":{ + "configuredModelAlgorithmAssociationArn":{ + "shape":"ConfiguredModelAlgorithmAssociationArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured model algorithm association.

" + } + } + }, + "CreateConfiguredModelAlgorithmRequest":{ + "type":"structure", + "required":[ + "name", + "roleArn" + ], + "members":{ + "name":{ + "shape":"NameString", + "documentation":"

The name of the configured model algorithm.

" + }, + "description":{ + "shape":"ResourceDescription", + "documentation":"

The description of the configured model algorithm.

" + }, + "roleArn":{ + "shape":"IamRoleArn", + "documentation":"

The Amazon Resource Name (ARN) of the role that is used to access the repository.

" + }, + "trainingContainerConfig":{ + "shape":"ContainerConfig", + "documentation":"

Configuration information for the training container, including entrypoints and arguments.

" + }, + "inferenceContainerConfig":{ + "shape":"InferenceContainerConfig", + "documentation":"

Configuration information for the inference container that is used when you run an inference job on a configured model algorithm.

" + }, + "tags":{ + "shape":"TagMap", + "documentation":"

The optional metadata that you apply to the resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

The following basic restrictions apply to tags:

" + }, + "kmsKeyArn":{ + "shape":"KmsKeyArn", + "documentation":"

The Amazon Resource Name (ARN) of the KMS key. This key is used to encrypt and decrypt customer-owned data in the configured ML model algorithm and associated data.

" + } + } + }, + "CreateConfiguredModelAlgorithmResponse":{ + "type":"structure", + "required":["configuredModelAlgorithmArn"], + "members":{ + "configuredModelAlgorithmArn":{ + "shape":"ConfiguredModelAlgorithmArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured model algorithm.

" + } + } + }, + "CreateMLInputChannelRequest":{ + "type":"structure", + "required":[ + "membershipIdentifier", + "configuredModelAlgorithmAssociations", + "inputChannel", + "name", + "retentionInDays" + ], + "members":{ + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the member that is creating the ML input channel.

", + "location":"uri", + "locationName":"membershipIdentifier" + }, + "configuredModelAlgorithmAssociations":{ + "shape":"CreateMLInputChannelRequestConfiguredModelAlgorithmAssociationsList", + "documentation":"

The associated configured model algorithms that are necessary to create this ML input channel.

" + }, + "inputChannel":{ + "shape":"InputChannel", + "documentation":"

The input data that is used to create this ML input channel.

" + }, + "name":{ + "shape":"NameString", + "documentation":"

The name of the ML input channel.

" + }, + "retentionInDays":{ + "shape":"CreateMLInputChannelRequestRetentionInDaysInteger", + "documentation":"

The number of days that the data in the ML input channel is retained.

" + }, + "description":{ + "shape":"ResourceDescription", + "documentation":"

The description of the ML input channel.

" + }, + "kmsKeyArn":{ + "shape":"KmsKeyArn", + "documentation":"

The Amazon Resource Name (ARN) of the KMS key that is used to access the input channel.

" + }, + "tags":{ + "shape":"TagMap", + "documentation":"

The optional metadata that you apply to the resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

The following basic restrictions apply to tags:

" + } + } + }, + "CreateMLInputChannelRequestConfiguredModelAlgorithmAssociationsList":{ + "type":"list", + "member":{"shape":"ConfiguredModelAlgorithmAssociationArn"}, + "max":1, + "min":1 + }, + "CreateMLInputChannelRequestRetentionInDaysInteger":{ + "type":"integer", + "box":true, + "max":30, + "min":1 + }, + "CreateMLInputChannelResponse":{ + "type":"structure", + "required":["mlInputChannelArn"], + "members":{ + "mlInputChannelArn":{ + "shape":"MLInputChannelArn", + "documentation":"

The Amazon Resource Name (ARN) of the ML input channel.

" + } + } + }, + "CreateTrainedModelRequest":{ + "type":"structure", + "required":[ + "membershipIdentifier", + "name", + "configuredModelAlgorithmAssociationArn", + "resourceConfig", + "dataChannels" + ], + "members":{ + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the member that is creating the trained model.

", + "location":"uri", + "locationName":"membershipIdentifier" + }, + "name":{ + "shape":"NameString", + "documentation":"

The name of the trained model.

" + }, + "configuredModelAlgorithmAssociationArn":{ + "shape":"ConfiguredModelAlgorithmAssociationArn", + "documentation":"

The associated configured model algorithm used to train this model.

" + }, + "hyperparameters":{ + "shape":"HyperParameters", + "documentation":"

Algorithm-specific parameters that influence the quality of the model. You set hyperparameters before you start the learning process.

" + }, + "environment":{ + "shape":"Environment", + "documentation":"

The environment variables to set in the Docker container.

" + }, + "resourceConfig":{ + "shape":"ResourceConfig", + "documentation":"

Information about the EC2 resources that are used to train this model.

" + }, + "stoppingCondition":{ + "shape":"StoppingCondition", + "documentation":"

The criteria that is used to stop model training.

" + }, + "dataChannels":{ + "shape":"ModelTrainingDataChannels", + "documentation":"

Defines the data channels that are used as input for the trained model request.

" + }, + "description":{ + "shape":"ResourceDescription", + "documentation":"

The description of the trained model.

" + }, + "kmsKeyArn":{ + "shape":"KmsKeyArn", + "documentation":"

The Amazon Resource Name (ARN) of the KMS key. This key is used to encrypt and decrypt customer-owned data in the trained ML model and the associated data.

" + }, + "tags":{ + "shape":"TagMap", + "documentation":"

The optional metadata that you apply to the resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

The following basic restrictions apply to tags:

" + } + } + }, + "CreateTrainedModelResponse":{ + "type":"structure", + "required":["trainedModelArn"], + "members":{ + "trainedModelArn":{ + "shape":"TrainedModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the trained model.

" + } + } + }, + "CreateTrainingDatasetRequest":{ + "type":"structure", + "required":[ + "name", + "roleArn", + "trainingData" + ], + "members":{ + "name":{ + "shape":"NameString", + "documentation":"

The name of the training dataset. This name must be unique in your account and region.

" + }, + "roleArn":{ + "shape":"IamRoleArn", + "documentation":"

The ARN of the IAM role that Clean Rooms ML can assume to read the data referred to in the dataSource field of each dataset.

Passing a role across AWS accounts is not allowed. If you pass a role that isn't in your account, you get an AccessDeniedException error.

" + }, + "trainingData":{ + "shape":"CreateTrainingDatasetRequestTrainingDataList", + "documentation":"

An array of information that lists the Dataset objects, which specifies the dataset type and details on its location and schema. You must provide a role that has read access to these tables.

" + }, + "tags":{ + "shape":"TagMap", + "documentation":"

The optional metadata that you apply to the resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

The following basic restrictions apply to tags:

" + }, + "description":{ + "shape":"ResourceDescription", + "documentation":"

The description of the training dataset.

" + } + } + }, + "CreateTrainingDatasetRequestTrainingDataList":{ + "type":"list", + "member":{"shape":"Dataset"}, + "max":1, + "min":1 + }, + "CreateTrainingDatasetResponse":{ + "type":"structure", + "required":["trainingDatasetArn"], + "members":{ + "trainingDatasetArn":{ + "shape":"TrainingDatasetArn", + "documentation":"

The Amazon Resource Name (ARN) of the training dataset resource.

" + } + } + }, + "DataSource":{ + "type":"structure", + "required":["glueDataSource"], + "members":{ + "glueDataSource":{ + "shape":"GlueDataSource", + "documentation":"

A GlueDataSource object that defines the catalog ID, database name, and table name for the training data.

" + } + }, + "documentation":"

Defines information about the Glue data source that contains the training data.

" + }, + "Dataset":{ + "type":"structure", + "required":[ + "type", + "inputConfig" + ], + "members":{ + "type":{ + "shape":"DatasetType", + "documentation":"

What type of information is found in the dataset.

" + }, + "inputConfig":{ + "shape":"DatasetInputConfig", + "documentation":"

A DatasetInputConfig object that defines the data source and schema mapping.

" + } + }, + "documentation":"

Defines where the training dataset is located, what type of data it contains, and how to access the data.

" + }, + "DatasetInputConfig":{ + "type":"structure", + "required":[ + "schema", + "dataSource" + ], + "members":{ + "schema":{ + "shape":"DatasetInputConfigSchemaList", + "documentation":"

The schema information for the training data.

" + }, + "dataSource":{ + "shape":"DataSource", + "documentation":"

A DataSource object that specifies the Glue data source for the training data.

" + } + }, + "documentation":"

Defines the Glue data source and schema mapping information.

" + }, + "DatasetInputConfigSchemaList":{ + "type":"list", + "member":{"shape":"ColumnSchema"}, + "max":100, + "min":1 + }, + "DatasetList":{ + "type":"list", + "member":{"shape":"Dataset"} + }, + "DatasetType":{ + "type":"string", + "enum":["INTERACTIONS"] + }, + "DeleteAudienceGenerationJobRequest":{ + "type":"structure", + "required":["audienceGenerationJobArn"], + "members":{ + "audienceGenerationJobArn":{ + "shape":"AudienceGenerationJobArn", + "documentation":"

The Amazon Resource Name (ARN) of the audience generation job that you want to delete.

", + "location":"uri", + "locationName":"audienceGenerationJobArn" + } + } + }, + "DeleteAudienceModelRequest":{ + "type":"structure", + "required":["audienceModelArn"], + "members":{ + "audienceModelArn":{ + "shape":"AudienceModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the audience model that you want to delete.

", + "location":"uri", + "locationName":"audienceModelArn" + } + } + }, + "DeleteConfiguredAudienceModelPolicyRequest":{ + "type":"structure", + "required":["configuredAudienceModelArn"], + "members":{ + "configuredAudienceModelArn":{ + "shape":"ConfiguredAudienceModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured audience model policy that you want to delete.

", + "location":"uri", + "locationName":"configuredAudienceModelArn" + } + } + }, + "DeleteConfiguredAudienceModelRequest":{ + "type":"structure", + "required":["configuredAudienceModelArn"], + "members":{ + "configuredAudienceModelArn":{ + "shape":"ConfiguredAudienceModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured audience model that you want to delete.

", + "location":"uri", + "locationName":"configuredAudienceModelArn" + } + } + }, + "DeleteConfiguredModelAlgorithmAssociationRequest":{ + "type":"structure", + "required":[ + "configuredModelAlgorithmAssociationArn", + "membershipIdentifier" + ], + "members":{ + "configuredModelAlgorithmAssociationArn":{ + "shape":"ConfiguredModelAlgorithmAssociationArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured model algorithm association that you want to delete.

", + "location":"uri", + "locationName":"configuredModelAlgorithmAssociationArn" + }, + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the member that is deleting the configured model algorithm association.

", + "location":"uri", + "locationName":"membershipIdentifier" + } + } + }, + "DeleteConfiguredModelAlgorithmRequest":{ + "type":"structure", + "required":["configuredModelAlgorithmArn"], + "members":{ + "configuredModelAlgorithmArn":{ + "shape":"ConfiguredModelAlgorithmArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured model algorithm that you want to delete.

", + "location":"uri", + "locationName":"configuredModelAlgorithmArn" + } + } + }, + "DeleteMLConfigurationRequest":{ + "type":"structure", + "required":["membershipIdentifier"], + "members":{ + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the of the member that is deleting the ML modeling configuration.

", + "location":"uri", + "locationName":"membershipIdentifier" + } + } + }, + "DeleteMLInputChannelDataRequest":{ + "type":"structure", + "required":[ + "mlInputChannelArn", + "membershipIdentifier" + ], + "members":{ + "mlInputChannelArn":{ + "shape":"MLInputChannelArn", + "documentation":"

The Amazon Resource Name (ARN) of the ML input channel that you want to delete.

", + "location":"uri", + "locationName":"mlInputChannelArn" + }, + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the membership that contains the ML input channel you want to delete.

", + "location":"uri", + "locationName":"membershipIdentifier" + } + } + }, + "DeleteTrainedModelOutputRequest":{ + "type":"structure", + "required":[ + "trainedModelArn", + "membershipIdentifier" + ], + "members":{ + "trainedModelArn":{ + "shape":"TrainedModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the trained model whose output you want to delete.

", + "location":"uri", + "locationName":"trainedModelArn" + }, + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the member that is deleting the trained model output.

", + "location":"uri", + "locationName":"membershipIdentifier" + } + } + }, + "DeleteTrainingDatasetRequest":{ + "type":"structure", + "required":["trainingDatasetArn"], + "members":{ + "trainingDatasetArn":{ + "shape":"TrainingDatasetArn", + "documentation":"

The Amazon Resource Name (ARN) of the training dataset that you want to delete.

", + "location":"uri", + "locationName":"trainingDatasetArn" + } + } + }, + "Destination":{ + "type":"structure", + "required":["s3Destination"], + "members":{ + "s3Destination":{"shape":"S3ConfigMap"} + }, + "documentation":"

The Amazon S3 location where the exported model artifacts are stored.

" + }, + "Environment":{ + "type":"map", + "key":{"shape":"EnvironmentKeyString"}, + "value":{"shape":"EnvironmentValueString"}, + "max":100, + "min":0 + }, + "EnvironmentKeyString":{ + "type":"string", + "max":512, + "min":1, + "pattern":"[a-zA-Z_][a-zA-Z0-9_]*" + }, + "EnvironmentValueString":{ + "type":"string", + "max":512, + "min":1, + "pattern":"[\\S\\s]*" + }, + "GetAudienceGenerationJobRequest":{ + "type":"structure", + "required":["audienceGenerationJobArn"], + "members":{ + "audienceGenerationJobArn":{ + "shape":"AudienceGenerationJobArn", + "documentation":"

The Amazon Resource Name (ARN) of the audience generation job that you are interested in.

", + "location":"uri", + "locationName":"audienceGenerationJobArn" + } + } + }, + "GetAudienceGenerationJobResponse":{ + "type":"structure", + "required":[ + "createTime", + "updateTime", + "audienceGenerationJobArn", + "name", + "status", + "configuredAudienceModelArn" + ], + "members":{ + "createTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The time at which the audience generation job was created.

" + }, + "updateTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The most recent time at which the audience generation job was updated.

" + }, + "audienceGenerationJobArn":{ + "shape":"AudienceGenerationJobArn", + "documentation":"

The Amazon Resource Name (ARN) of the audience generation job.

" + }, + "name":{ + "shape":"NameString", + "documentation":"

The name of the audience generation job.

" + }, + "description":{ + "shape":"ResourceDescription", + "documentation":"

The description of the audience generation job.

" + }, + "status":{ + "shape":"AudienceGenerationJobStatus", + "documentation":"

The status of the audience generation job.

" + }, + "statusDetails":{ + "shape":"StatusDetails", + "documentation":"

Details about the status of the audience generation job.

" + }, + "configuredAudienceModelArn":{ + "shape":"ConfiguredAudienceModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured audience model used for this audience generation job.

" + }, + "seedAudience":{ + "shape":"AudienceGenerationJobDataSource", + "documentation":"

The seed audience that was used for this audience generation job. This field will be null if the account calling the API is the account that started this audience generation job.

" + }, + "includeSeedInOutput":{ + "shape":"Boolean", + "documentation":"

Configure whether the seed users are included in the output audience. By default, Clean Rooms ML removes seed users from the output audience. If you specify TRUE, the seed users will appear first in the output. Clean Rooms ML does not explicitly reveal whether a user was in the seed, but the recipient of the audience will know that the first minimumSeedSize count of users are from the seed.

" + }, + "collaborationId":{ + "shape":"UUID", + "documentation":"

The identifier of the collaboration that this audience generation job is associated with.

" + }, + "metrics":{ + "shape":"AudienceQualityMetrics", + "documentation":"

The relevance scores for different audience sizes and the recall score of the generated audience.

" + }, + "startedBy":{ + "shape":"AccountId", + "documentation":"

The AWS account that started this audience generation job.

" + }, + "tags":{ + "shape":"TagMap", + "documentation":"

The tags that are associated to this audience generation job.

" + }, + "protectedQueryIdentifier":{ + "shape":"String", + "documentation":"

The unique identifier of the protected query for this audience generation job.

" + } + } + }, + "GetAudienceModelRequest":{ + "type":"structure", + "required":["audienceModelArn"], + "members":{ + "audienceModelArn":{ + "shape":"AudienceModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the audience model that you are interested in.

", + "location":"uri", + "locationName":"audienceModelArn" + } + } + }, + "GetAudienceModelResponse":{ + "type":"structure", + "required":[ + "createTime", + "updateTime", + "audienceModelArn", + "name", + "trainingDatasetArn", + "status" + ], + "members":{ + "createTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The time at which the audience model was created.

" + }, + "updateTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The most recent time at which the audience model was updated.

" + }, + "trainingDataStartTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The start date specified for the training window.

" + }, + "trainingDataEndTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The end date specified for the training window.

" + }, + "audienceModelArn":{ + "shape":"AudienceModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the audience model.

" + }, + "name":{ + "shape":"NameString", + "documentation":"

The name of the audience model.

" + }, + "trainingDatasetArn":{ + "shape":"TrainingDatasetArn", + "documentation":"

The Amazon Resource Name (ARN) of the training dataset that was used for this audience model.

" + }, + "status":{ + "shape":"AudienceModelStatus", + "documentation":"

The status of the audience model.

" + }, + "statusDetails":{ + "shape":"StatusDetails", + "documentation":"

Details about the status of the audience model.

" + }, + "kmsKeyArn":{ + "shape":"KmsKeyArn", + "documentation":"

The KMS key ARN used for the audience model.

" + }, + "tags":{ + "shape":"TagMap", + "documentation":"

The tags that are assigned to the audience model.

" + }, + "description":{ + "shape":"ResourceDescription", + "documentation":"

The description of the audience model.

" + } + } + }, + "GetCollaborationConfiguredModelAlgorithmAssociationRequest":{ + "type":"structure", + "required":[ + "configuredModelAlgorithmAssociationArn", + "collaborationIdentifier" + ], + "members":{ + "configuredModelAlgorithmAssociationArn":{ + "shape":"ConfiguredModelAlgorithmAssociationArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured model algorithm association that you want to return information about.

", + "location":"uri", + "locationName":"configuredModelAlgorithmAssociationArn" + }, + "collaborationIdentifier":{ + "shape":"UUID", + "documentation":"

The collaboration ID for the collaboration that contains the configured model algorithm association that you want to return information about.

", + "location":"uri", + "locationName":"collaborationIdentifier" + } + } + }, + "GetCollaborationConfiguredModelAlgorithmAssociationResponse":{ + "type":"structure", + "required":[ + "createTime", + "updateTime", + "configuredModelAlgorithmAssociationArn", + "membershipIdentifier", + "collaborationIdentifier", + "configuredModelAlgorithmArn", + "name", + "creatorAccountId" + ], + "members":{ + "createTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The time at which the configured model algorithm association was created.

" + }, + "updateTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The most recent time at which the configured model algorithm association was updated.

" + }, + "configuredModelAlgorithmAssociationArn":{ + "shape":"ConfiguredModelAlgorithmAssociationArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured model algorithm association.

" + }, + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the member that created the configured model algorithm association.

" + }, + "collaborationIdentifier":{ + "shape":"UUID", + "documentation":"

The collaboration ID of the collaboration that contains the configured model algorithm association.

" + }, + "configuredModelAlgorithmArn":{ + "shape":"ConfiguredModelAlgorithmArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured model algorithm association.

" + }, + "name":{ + "shape":"NameString", + "documentation":"

The name of the configured model algorithm association.

" + }, + "description":{ + "shape":"ResourceDescription", + "documentation":"

The description of the configured model algorithm association.

" + }, + "creatorAccountId":{ + "shape":"AccountId", + "documentation":"

The account ID of the member that created the configured model algorithm association.

" + }, + "privacyConfiguration":{"shape":"PrivacyConfiguration"} + } + }, + "GetCollaborationMLInputChannelRequest":{ + "type":"structure", + "required":[ + "mlInputChannelArn", + "collaborationIdentifier" + ], + "members":{ + "mlInputChannelArn":{ + "shape":"MLInputChannelArn", + "documentation":"

The Amazon Resource Name (ARN) of the ML input channel that you want to get.

", + "location":"uri", + "locationName":"mlInputChannelArn" + }, + "collaborationIdentifier":{ + "shape":"UUID", + "documentation":"

The collaboration ID of the collaboration that contains the ML input channel that you want to get.

", + "location":"uri", + "locationName":"collaborationIdentifier" + } + } + }, + "GetCollaborationMLInputChannelResponse":{ + "type":"structure", + "required":[ + "createTime", + "updateTime", + "creatorAccountId", + "membershipIdentifier", + "collaborationIdentifier", + "mlInputChannelArn", + "name", + "configuredModelAlgorithmAssociations", + "status", + "retentionInDays" + ], + "members":{ + "createTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The time at which the ML input channel was created.

" + }, + "updateTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The most recent time at which the ML input channel was updated.

" + }, + "creatorAccountId":{ + "shape":"AccountId", + "documentation":"

The account ID of the member who created the ML input channel.

" + }, + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the membership that contains the ML input channel.

" + }, + "collaborationIdentifier":{ + "shape":"UUID", + "documentation":"

The collaboration ID of the collaboration that contains the ML input channel.

" + }, + "mlInputChannelArn":{ + "shape":"MLInputChannelArn", + "documentation":"

The Amazon Resource Name (ARN) of the ML input channel.

" + }, + "name":{ + "shape":"NameString", + "documentation":"

The name of the ML input channel.

" + }, + "configuredModelAlgorithmAssociations":{ + "shape":"GetCollaborationMLInputChannelResponseConfiguredModelAlgorithmAssociationsList", + "documentation":"

The configured model algorithm associations that were used to create the ML input channel.

" + }, + "status":{ + "shape":"MLInputChannelStatus", + "documentation":"

The status of the ML input channel.

" + }, + "statusDetails":{"shape":"StatusDetails"}, + "retentionInDays":{ + "shape":"GetCollaborationMLInputChannelResponseRetentionInDaysInteger", + "documentation":"

The number of days to retain the data for the ML input channel.

" + }, + "numberOfRecords":{ + "shape":"GetCollaborationMLInputChannelResponseNumberOfRecordsLong", + "documentation":"

The number of records in the ML input channel.

" + }, + "description":{ + "shape":"ResourceDescription", + "documentation":"

The description of the ML input channel.

" + } + } + }, + "GetCollaborationMLInputChannelResponseConfiguredModelAlgorithmAssociationsList":{ + "type":"list", + "member":{"shape":"ConfiguredModelAlgorithmAssociationArn"}, + "max":1, + "min":1 + }, + "GetCollaborationMLInputChannelResponseNumberOfRecordsLong":{ + "type":"long", + "box":true, + "max":100000000000, + "min":0 + }, + "GetCollaborationMLInputChannelResponseRetentionInDaysInteger":{ + "type":"integer", + "box":true, + "max":30, + "min":1 + }, + "GetCollaborationTrainedModelRequest":{ + "type":"structure", + "required":[ + "trainedModelArn", + "collaborationIdentifier" + ], + "members":{ + "trainedModelArn":{ + "shape":"TrainedModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the trained model that you want to return information about.

", + "location":"uri", + "locationName":"trainedModelArn" + }, + "collaborationIdentifier":{ + "shape":"UUID", + "documentation":"

The collaboration ID that contains the trained model that you want to return information about.

", + "location":"uri", + "locationName":"collaborationIdentifier" + } + } + }, + "GetCollaborationTrainedModelResponse":{ + "type":"structure", + "required":[ + "membershipIdentifier", + "collaborationIdentifier", + "trainedModelArn", + "name", + "status", + "configuredModelAlgorithmAssociationArn", + "createTime", + "updateTime", + "creatorAccountId" + ], + "members":{ + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the member that created the trained model.

" + }, + "collaborationIdentifier":{ + "shape":"UUID", + "documentation":"

The collaboration ID of the collaboration that contains the trained model.

" + }, + "trainedModelArn":{ + "shape":"TrainedModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the trained model.

" + }, + "name":{ + "shape":"NameString", + "documentation":"

The name of the trained model.

" + }, + "description":{ + "shape":"ResourceDescription", + "documentation":"

The description of the trained model.

" + }, + "status":{ + "shape":"TrainedModelStatus", + "documentation":"

The status of the trained model.

" + }, + "statusDetails":{"shape":"StatusDetails"}, + "configuredModelAlgorithmAssociationArn":{ + "shape":"ConfiguredModelAlgorithmAssociationArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured model algorithm association that was used to create this trained model.

" + }, + "resourceConfig":{ + "shape":"ResourceConfig", + "documentation":"

The EC2 resource configuration that was used to train this model.

" + }, + "stoppingCondition":{ + "shape":"StoppingCondition", + "documentation":"

The stopping condition that determined when model training ended.

" + }, + "metricsStatus":{ + "shape":"MetricsStatus", + "documentation":"

The status of the model metrics.

" + }, + "metricsStatusDetails":{ + "shape":"String", + "documentation":"

Details about the status information for the model metrics.

" + }, + "logsStatus":{ + "shape":"LogsStatus", + "documentation":"

Status information for the logs.

" + }, + "logsStatusDetails":{ + "shape":"String", + "documentation":"

Details about the status information for the logs.

" + }, + "trainingContainerImageDigest":{ + "shape":"String", + "documentation":"

Information about the training container image.

" + }, + "createTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The time at which the trained model was created.

" + }, + "updateTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The most recent time at which the trained model was updated.

" + }, + "creatorAccountId":{ + "shape":"AccountId", + "documentation":"

The account ID of the member that created the trained model.

" + } + } + }, + "GetConfiguredAudienceModelPolicyRequest":{ + "type":"structure", + "required":["configuredAudienceModelArn"], + "members":{ + "configuredAudienceModelArn":{ + "shape":"ConfiguredAudienceModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured audience model that you are interested in.

", + "location":"uri", + "locationName":"configuredAudienceModelArn" + } + } + }, + "GetConfiguredAudienceModelPolicyResponse":{ + "type":"structure", + "required":[ + "configuredAudienceModelArn", + "configuredAudienceModelPolicy", + "policyHash" + ], + "members":{ + "configuredAudienceModelArn":{ + "shape":"ConfiguredAudienceModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured audience model.

" + }, + "configuredAudienceModelPolicy":{ + "shape":"ResourcePolicy", + "documentation":"

The configured audience model policy. This is a JSON IAM resource policy.

" + }, + "policyHash":{ + "shape":"Hash", + "documentation":"

A cryptographic hash of the contents of the policy used to prevent unexpected concurrent modification of the policy.

" + } + } + }, + "GetConfiguredAudienceModelRequest":{ + "type":"structure", + "required":["configuredAudienceModelArn"], + "members":{ + "configuredAudienceModelArn":{ + "shape":"ConfiguredAudienceModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured audience model that you are interested in.

", + "location":"uri", + "locationName":"configuredAudienceModelArn" + } + } + }, + "GetConfiguredAudienceModelResponse":{ + "type":"structure", + "required":[ + "createTime", + "updateTime", + "configuredAudienceModelArn", + "name", + "audienceModelArn", + "outputConfig", + "status", + "sharedAudienceMetrics" + ], + "members":{ + "createTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The time at which the configured audience model was created.

" + }, + "updateTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The most recent time at which the configured audience model was updated.

" + }, + "configuredAudienceModelArn":{ + "shape":"ConfiguredAudienceModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured audience model.

" + }, + "name":{ + "shape":"NameString", + "documentation":"

The name of the configured audience model.

" + }, + "audienceModelArn":{ + "shape":"AudienceModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the audience model used for this configured audience model.

" + }, + "outputConfig":{ + "shape":"ConfiguredAudienceModelOutputConfig", + "documentation":"

The output configuration of the configured audience model

" + }, + "description":{ + "shape":"ResourceDescription", + "documentation":"

The description of the configured audience model.

" + }, + "status":{ + "shape":"ConfiguredAudienceModelStatus", + "documentation":"

The status of the configured audience model.

" + }, + "sharedAudienceMetrics":{ + "shape":"MetricsList", + "documentation":"

Whether audience metrics are shared.

" + }, + "minMatchingSeedSize":{ + "shape":"MinMatchingSeedSize", + "documentation":"

The minimum number of users from the seed audience that must match with users in the training data of the audience model.

" + }, + "audienceSizeConfig":{ + "shape":"AudienceSizeConfig", + "documentation":"

The list of output sizes of audiences that can be created using this configured audience model. A request to StartAudienceGenerationJob that uses this configured audience model must have an audienceSize selected from this list. You can use the ABSOLUTE AudienceSize to configure out audience sizes using the count of identifiers in the output. You can use the Percentage AudienceSize to configure sizes in the range 1-100 percent.

" + }, + "tags":{ + "shape":"TagMap", + "documentation":"

The tags that are associated to this configured audience model.

" + }, + "childResourceTagOnCreatePolicy":{ + "shape":"TagOnCreatePolicy", + "documentation":"

Provides the childResourceTagOnCreatePolicy that was used for this configured audience model.

" + } + } + }, + "GetConfiguredModelAlgorithmAssociationRequest":{ + "type":"structure", + "required":[ + "configuredModelAlgorithmAssociationArn", + "membershipIdentifier" + ], + "members":{ + "configuredModelAlgorithmAssociationArn":{ + "shape":"ConfiguredModelAlgorithmAssociationArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured model algorithm association that you want to return information about.

", + "location":"uri", + "locationName":"configuredModelAlgorithmAssociationArn" + }, + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the member that created the configured model algorithm association.

", + "location":"uri", + "locationName":"membershipIdentifier" + } + } + }, + "GetConfiguredModelAlgorithmAssociationResponse":{ + "type":"structure", + "required":[ + "createTime", + "updateTime", + "configuredModelAlgorithmAssociationArn", + "membershipIdentifier", + "collaborationIdentifier", + "configuredModelAlgorithmArn", + "name" + ], + "members":{ + "createTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The time at which the configured model algorithm association was created.

" + }, + "updateTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The most recent time at which the configured model algorithm association was updated.

" + }, + "configuredModelAlgorithmAssociationArn":{ + "shape":"ConfiguredModelAlgorithmAssociationArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured model algorithm association.

" + }, + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the member that created the configured model algorithm association.

" + }, + "collaborationIdentifier":{ + "shape":"UUID", + "documentation":"

The collaboration ID of the collaboration that contains the configured model algorithm association.

" + }, + "configuredModelAlgorithmArn":{ + "shape":"ConfiguredModelAlgorithmArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured model algorithm that was associated to the collaboration.

" + }, + "name":{ + "shape":"NameString", + "documentation":"

The name of the configured model algorithm association.

" + }, + "privacyConfiguration":{ + "shape":"PrivacyConfiguration", + "documentation":"

The privacy configuration information for the configured model algorithm association.

" + }, + "description":{ + "shape":"ResourceDescription", + "documentation":"

The description of the configured model algorithm association.

" + }, + "tags":{ + "shape":"TagMap", + "documentation":"

The optional metadata that you applied to the resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

The following basic restrictions apply to tags:

" + } + } + }, + "GetConfiguredModelAlgorithmRequest":{ + "type":"structure", + "required":["configuredModelAlgorithmArn"], + "members":{ + "configuredModelAlgorithmArn":{ + "shape":"ConfiguredModelAlgorithmArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured model algorithm that you want to return information about.

", + "location":"uri", + "locationName":"configuredModelAlgorithmArn" + } + } + }, + "GetConfiguredModelAlgorithmResponse":{ + "type":"structure", + "required":[ + "createTime", + "updateTime", + "configuredModelAlgorithmArn", + "name", + "roleArn" + ], + "members":{ + "createTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The time at which the configured model algorithm was created.

" + }, + "updateTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The most recent time at which the configured model algorithm was updated.

" + }, + "configuredModelAlgorithmArn":{ + "shape":"ConfiguredModelAlgorithmArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured model algorithm.

" + }, + "name":{ + "shape":"NameString", + "documentation":"

The name of the configured model algorithm.

" + }, + "trainingContainerConfig":{ + "shape":"ContainerConfig", + "documentation":"

The configuration information of the training container for the configured model algorithm.

" + }, + "inferenceContainerConfig":{ + "shape":"InferenceContainerConfig", + "documentation":"

Configuration information for the inference container.

" + }, + "roleArn":{ + "shape":"IamRoleArn", + "documentation":"

The Amazon Resource Name (ARN) of the service role that was used to create the configured model algorithm.

" + }, + "description":{ + "shape":"ResourceDescription", + "documentation":"

The description of the configured model algorithm.

" + }, + "tags":{ + "shape":"TagMap", + "documentation":"

The optional metadata that you applied to the resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

The following basic restrictions apply to tags:

" + }, + "kmsKeyArn":{ + "shape":"KmsKeyArn", + "documentation":"

The Amazon Resource Name (ARN) of the KMS key. This key is used to encrypt and decrypt customer-owned data in the configured ML model and associated data.

" + } + } + }, + "GetMLConfigurationRequest":{ + "type":"structure", + "required":["membershipIdentifier"], + "members":{ + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the member that owns the ML configuration you want to return information about.

", + "location":"uri", + "locationName":"membershipIdentifier" + } + } + }, + "GetMLConfigurationResponse":{ + "type":"structure", + "required":[ + "membershipIdentifier", + "defaultOutputLocation", + "createTime", + "updateTime" + ], + "members":{ + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the member that owns the ML configuration you requested.

" + }, + "defaultOutputLocation":{ + "shape":"MLOutputConfiguration", + "documentation":"

The Amazon S3 location where ML model output is stored.

" + }, + "createTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The time at which the ML configuration was created.

" + }, + "updateTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The most recent time at which the ML configuration was updated.

" + } + } + }, + "GetMLInputChannelRequest":{ + "type":"structure", + "required":[ + "mlInputChannelArn", + "membershipIdentifier" + ], + "members":{ + "mlInputChannelArn":{ + "shape":"MLInputChannelArn", + "documentation":"

The Amazon Resource Name (ARN) of the ML input channel that you want to get.

", + "location":"uri", + "locationName":"mlInputChannelArn" + }, + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the membership that contains the ML input channel that you want to get.

", + "location":"uri", + "locationName":"membershipIdentifier" + } + } + }, + "GetMLInputChannelResponse":{ + "type":"structure", + "required":[ + "createTime", + "updateTime", + "membershipIdentifier", + "collaborationIdentifier", + "inputChannel", + "mlInputChannelArn", + "name", + "configuredModelAlgorithmAssociations", + "status", + "retentionInDays" + ], + "members":{ + "createTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The time at which the ML input channel was created.

" + }, + "updateTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The most recent time at which the ML input channel was updated.

" + }, + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the membership that contains the ML input channel.

" + }, + "collaborationIdentifier":{ + "shape":"UUID", + "documentation":"

The collaboration ID of the collaboration that contains the ML input channel.

" + }, + "inputChannel":{ + "shape":"InputChannel", + "documentation":"

The input channel that was used to create the ML input channel.

" + }, + "protectedQueryIdentifier":{ + "shape":"UUID", + "documentation":"

The ID of the protected query that was used to create the ML input channel.

" + }, + "mlInputChannelArn":{ + "shape":"MLInputChannelArn", + "documentation":"

The Amazon Resource Name (ARN) of the ML input channel.

" + }, + "name":{ + "shape":"NameString", + "documentation":"

The name of the ML input channel.

" + }, + "configuredModelAlgorithmAssociations":{ + "shape":"GetMLInputChannelResponseConfiguredModelAlgorithmAssociationsList", + "documentation":"

The configured model algorithm associations that were used to create the ML input channel.

" + }, + "status":{ + "shape":"MLInputChannelStatus", + "documentation":"

The status of the ML input channel.

" + }, + "statusDetails":{"shape":"StatusDetails"}, + "retentionInDays":{ + "shape":"GetMLInputChannelResponseRetentionInDaysInteger", + "documentation":"

The number of days to keep the data in the ML input channel.

" + }, + "numberOfRecords":{ + "shape":"GetMLInputChannelResponseNumberOfRecordsLong", + "documentation":"

The number of records in the ML input channel.

" + }, + "numberOfFiles":{ + "shape":"GetMLInputChannelResponseNumberOfFilesDouble", + "documentation":"

The number of files in the ML input channel.

" + }, + "sizeInGb":{ + "shape":"GetMLInputChannelResponseSizeInGbDouble", + "documentation":"

The size, in GB, of the ML input channel.

" + }, + "description":{ + "shape":"ResourceDescription", + "documentation":"

The description of the ML input channel.

" + }, + "kmsKeyArn":{ + "shape":"KmsKeyArn", + "documentation":"

The Amazon Resource Name (ARN) of the KMS key that was used to create the ML input channel.

" + }, + "tags":{ + "shape":"TagMap", + "documentation":"

The optional metadata that you applied to the resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

The following basic restrictions apply to tags:

" + } + } + }, + "GetMLInputChannelResponseConfiguredModelAlgorithmAssociationsList":{ + "type":"list", + "member":{"shape":"ConfiguredModelAlgorithmAssociationArn"}, + "max":1, + "min":1 + }, + "GetMLInputChannelResponseNumberOfFilesDouble":{ + "type":"double", + "box":true, + "max":1000000, + "min":0 + }, + "GetMLInputChannelResponseNumberOfRecordsLong":{ + "type":"long", + "box":true, + "max":100000000000, + "min":0 + }, + "GetMLInputChannelResponseRetentionInDaysInteger":{ + "type":"integer", + "box":true, + "max":30, + "min":1 + }, + "GetMLInputChannelResponseSizeInGbDouble":{ + "type":"double", + "box":true, + "max":1000000, + "min":0 + }, + "GetTrainedModelInferenceJobRequest":{ + "type":"structure", + "required":[ + "membershipIdentifier", + "trainedModelInferenceJobArn" + ], + "members":{ + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

Provides the membership ID of the membership that contains the trained model inference job that you are interested in.

", + "location":"uri", + "locationName":"membershipIdentifier" + }, + "trainedModelInferenceJobArn":{ + "shape":"TrainedModelInferenceJobArn", + "documentation":"

Provides the Amazon Resource Name (ARN) of the trained model inference job that you are interested in.

", + "location":"uri", + "locationName":"trainedModelInferenceJobArn" + } + } + }, + "GetTrainedModelInferenceJobResponse":{ + "type":"structure", + "required":[ + "createTime", + "updateTime", + "trainedModelInferenceJobArn", + "name", + "status", + "trainedModelArn", + "resourceConfig", + "outputConfiguration", + "membershipIdentifier", + "dataSource" + ], + "members":{ + "createTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The time at which the trained model inference job was created.

" + }, + "updateTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The most recent time at which the trained model inference job was updated.

" + }, + "trainedModelInferenceJobArn":{ + "shape":"TrainedModelInferenceJobArn", + "documentation":"

The Amazon Resource Name (ARN) of the trained model inference job.

" + }, + "configuredModelAlgorithmAssociationArn":{ + "shape":"ConfiguredModelAlgorithmAssociationArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured model algorithm association that was used for the trained model inference job.

" + }, + "name":{ + "shape":"NameString", + "documentation":"

The name of the trained model inference job.

" + }, + "status":{ + "shape":"TrainedModelInferenceJobStatus", + "documentation":"

The status of the trained model inference job.

" + }, + "trainedModelArn":{ + "shape":"TrainedModelArn", + "documentation":"

The Amazon Resource Name (ARN) for the trained model that was used for the trained model inference job.

" + }, + "resourceConfig":{ + "shape":"InferenceResourceConfig", + "documentation":"

The resource configuration information for the trained model inference job.

" + }, + "outputConfiguration":{ + "shape":"InferenceOutputConfiguration", + "documentation":"

The output configuration information for the trained model inference job.

" + }, + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the membership that contains the trained model inference job.

" + }, + "dataSource":{ + "shape":"ModelInferenceDataSource", + "documentation":"

The data source that was used for the trained model inference job.

" + }, + "containerExecutionParameters":{ + "shape":"InferenceContainerExecutionParameters", + "documentation":"

The execution parameters for the model inference job container.

" + }, + "statusDetails":{"shape":"StatusDetails"}, + "description":{ + "shape":"ResourceDescription", + "documentation":"

The description of the trained model inference job.

" + }, + "inferenceContainerImageDigest":{ + "shape":"String", + "documentation":"

Information about the training container image.

" + }, + "environment":{ + "shape":"InferenceEnvironmentMap", + "documentation":"

The environment variables to set in the Docker container.

" + }, + "kmsKeyArn":{ + "shape":"KmsKeyArn", + "documentation":"

The Amazon Resource Name (ARN) of the KMS key. This key is used to encrypt and decrypt customer-owned data in the ML inference job and associated data.

" + }, + "metricsStatus":{ + "shape":"MetricsStatus", + "documentation":"

The metrics status for the trained model inference job.

" + }, + "metricsStatusDetails":{ + "shape":"String", + "documentation":"

Details about the metrics status for the trained model inference job.

" + }, + "logsStatus":{ + "shape":"LogsStatus", + "documentation":"

The logs status for the trained model inference job.

" + }, + "logsStatusDetails":{ + "shape":"String", + "documentation":"

Details about the logs status for the trained model inference job.

" + }, + "tags":{ + "shape":"TagMap", + "documentation":"

The optional metadata that you applied to the resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

The following basic restrictions apply to tags:

" + } + } + }, + "GetTrainedModelRequest":{ + "type":"structure", + "required":[ + "trainedModelArn", + "membershipIdentifier" + ], + "members":{ + "trainedModelArn":{ + "shape":"TrainedModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the trained model that you are interested in.

", + "location":"uri", + "locationName":"trainedModelArn" + }, + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the member that created the trained model that you are interested in.

", + "location":"uri", + "locationName":"membershipIdentifier" + } + } + }, + "GetTrainedModelResponse":{ + "type":"structure", + "required":[ + "membershipIdentifier", + "collaborationIdentifier", + "trainedModelArn", + "name", + "status", + "configuredModelAlgorithmAssociationArn", + "createTime", + "updateTime", + "dataChannels" + ], + "members":{ + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the member that created the trained model.

" + }, + "collaborationIdentifier":{ + "shape":"UUID", + "documentation":"

The collaboration ID of the collaboration that contains the trained model.

" + }, + "trainedModelArn":{ + "shape":"TrainedModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the trained model.

" + }, + "name":{ + "shape":"NameString", + "documentation":"

The name of the trained model.

" + }, + "description":{ + "shape":"ResourceDescription", + "documentation":"

The description of the trained model.

" + }, + "status":{ + "shape":"TrainedModelStatus", + "documentation":"

The status of the trained model.

" + }, + "statusDetails":{"shape":"StatusDetails"}, + "configuredModelAlgorithmAssociationArn":{ + "shape":"ConfiguredModelAlgorithmAssociationArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured model algorithm association that was used to create the trained model.

" + }, + "resourceConfig":{ + "shape":"ResourceConfig", + "documentation":"

The EC2 resource configuration that was used to create the trained model.

" + }, + "stoppingCondition":{ + "shape":"StoppingCondition", + "documentation":"

The stopping condition that was used to terminate model training.

" + }, + "metricsStatus":{ + "shape":"MetricsStatus", + "documentation":"

The status of the model metrics.

" + }, + "metricsStatusDetails":{ + "shape":"String", + "documentation":"

Details about the metrics status for the trained model.

" + }, + "logsStatus":{ + "shape":"LogsStatus", + "documentation":"

The logs status for the trained model.

" + }, + "logsStatusDetails":{ + "shape":"String", + "documentation":"

Details about the logs status for the trained model.

" + }, + "trainingContainerImageDigest":{ + "shape":"String", + "documentation":"

Information about the training image container.

" + }, + "createTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The time at which the trained model was created.

" + }, + "updateTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The most recent time at which the trained model was updated.

" + }, + "hyperparameters":{ + "shape":"HyperParameters", + "documentation":"

The hyperparameters that were used to create the trained model.

" + }, + "environment":{ + "shape":"Environment", + "documentation":"

The EC2 environment that was used to create the trained model.

" + }, + "kmsKeyArn":{ + "shape":"KmsKeyArn", + "documentation":"

The Amazon Resource Name (ARN) of the KMS key. This key is used to encrypt and decrypt customer-owned data in the trained ML model and associated data.

" + }, + "tags":{ + "shape":"TagMap", + "documentation":"

The optional metadata that you applied to the resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

The following basic restrictions apply to tags:

" + }, + "dataChannels":{ + "shape":"ModelTrainingDataChannels", + "documentation":"

The data channels that were used for the trained model.

" + } + } + }, + "GetTrainingDatasetRequest":{ + "type":"structure", + "required":["trainingDatasetArn"], + "members":{ + "trainingDatasetArn":{ + "shape":"TrainingDatasetArn", + "documentation":"

The Amazon Resource Name (ARN) of the training dataset that you are interested in.

", + "location":"uri", + "locationName":"trainingDatasetArn" + } + } + }, + "GetTrainingDatasetResponse":{ + "type":"structure", + "required":[ + "createTime", + "updateTime", + "trainingDatasetArn", + "name", + "trainingData", + "status", + "roleArn" + ], + "members":{ + "createTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The time at which the training dataset was created.

" + }, + "updateTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The most recent time at which the training dataset was updated.

" + }, + "trainingDatasetArn":{ + "shape":"TrainingDatasetArn", + "documentation":"

The Amazon Resource Name (ARN) of the training dataset.

" + }, + "name":{ + "shape":"NameString", + "documentation":"

The name of the training dataset.

" + }, + "trainingData":{ + "shape":"DatasetList", + "documentation":"

Metadata about the requested training data.

" + }, + "status":{ + "shape":"TrainingDatasetStatus", + "documentation":"

The status of the training dataset.

" + }, + "roleArn":{ + "shape":"IamRoleArn", + "documentation":"

The IAM role used to read the training data.

" + }, + "tags":{ + "shape":"TagMap", + "documentation":"

The tags that are assigned to this training dataset.

" + }, + "description":{ + "shape":"ResourceDescription", + "documentation":"

The description of the training dataset.

" + } + } + }, + "GlueDataSource":{ + "type":"structure", + "required":[ + "tableName", + "databaseName" + ], + "members":{ + "tableName":{ + "shape":"GlueTableName", + "documentation":"

The Glue table that contains the training data.

" + }, + "databaseName":{ + "shape":"GlueDatabaseName", + "documentation":"

The Glue database that contains the training data.

" + }, + "catalogId":{ + "shape":"AccountId", + "documentation":"

The Glue catalog that contains the training data.

" + } + }, + "documentation":"

Defines the Glue data source that contains the training data.

" + }, + "GlueDatabaseName":{ + "type":"string", + "max":128, + "min":1, + "pattern":"[a-zA-Z0-9_](([a-zA-Z0-9_]+-)*([a-zA-Z0-9_]+))?" + }, + "GlueTableName":{ + "type":"string", + "max":128, + "min":1, + "pattern":"[a-zA-Z0-9_](([a-zA-Z0-9_ ]+-)*([a-zA-Z0-9_ ]+))?" + }, + "Hash":{ + "type":"string", + "max":128, + "min":64, + "pattern":"[0-9a-f]+" + }, + "HyperParameters":{ + "type":"map", + "key":{"shape":"HyperParametersKeyString"}, + "value":{"shape":"HyperParametersValueString"}, + "max":100, + "min":0 + }, + "HyperParametersKeyString":{ + "type":"string", + "max":256, + "min":1, + "pattern":".*" + }, + "HyperParametersValueString":{ + "type":"string", + "max":2500, + "min":1, + "pattern":".*" + }, + "IamRoleArn":{ + "type":"string", + "max":2048, + "min":20, + "pattern":"arn:aws[-a-z]*:iam::[0-9]{12}:role/.+" + }, + "InferenceContainerConfig":{ + "type":"structure", + "required":["imageUri"], + "members":{ + "imageUri":{ + "shape":"AlgorithmImage", + "documentation":"

The registry path of the docker image that contains the inference algorithm. Clean Rooms ML supports both registry/repository[:tag] and registry/repositry[@digest] image path formats. For more information about using images in Clean Rooms ML, see the Sagemaker API reference.

" + } + }, + "documentation":"

Provides configuration information for the inference container.

" + }, + "InferenceContainerExecutionParameters":{ + "type":"structure", + "members":{ + "maxPayloadInMB":{ + "shape":"InferenceContainerExecutionParametersMaxPayloadInMBInteger", + "documentation":"

The maximum size of the inference container payload, specified in MB.

" + } + }, + "documentation":"

Provides execution parameters for the inference container.

" + }, + "InferenceContainerExecutionParametersMaxPayloadInMBInteger":{ + "type":"integer", + "box":true, + "max":100, + "min":1 + }, + "InferenceEnvironmentMap":{ + "type":"map", + "key":{"shape":"InferenceEnvironmentMapKeyString"}, + "value":{"shape":"InferenceEnvironmentMapValueString"}, + "max":16, + "min":0 + }, + "InferenceEnvironmentMapKeyString":{ + "type":"string", + "max":1024, + "min":1, + "pattern":"[a-zA-Z_][a-zA-Z0-9_]*" + }, + "InferenceEnvironmentMapValueString":{ + "type":"string", + "max":10240, + "min":1, + "pattern":"[\\S\\s]*" + }, + "InferenceInstanceType":{ + "type":"string", + "enum":[ + "ml.r7i.48xlarge", + "ml.r6i.16xlarge", + "ml.m6i.xlarge", + "ml.m5.4xlarge", + "ml.p2.xlarge", + "ml.m4.16xlarge", + "ml.r7i.16xlarge", + "ml.m7i.xlarge", + "ml.m6i.12xlarge", + "ml.r7i.8xlarge", + "ml.r7i.large", + "ml.m7i.12xlarge", + "ml.m6i.24xlarge", + "ml.m7i.24xlarge", + "ml.r6i.8xlarge", + "ml.r6i.large", + "ml.g5.2xlarge", + "ml.m5.large", + "ml.p3.16xlarge", + "ml.m7i.48xlarge", + "ml.m6i.16xlarge", + "ml.p2.16xlarge", + "ml.g5.4xlarge", + "ml.m7i.16xlarge", + "ml.c4.2xlarge", + "ml.c5.2xlarge", + "ml.c6i.32xlarge", + "ml.c4.4xlarge", + "ml.g5.8xlarge", + "ml.c6i.xlarge", + "ml.c5.4xlarge", + "ml.g4dn.xlarge", + "ml.c7i.xlarge", + "ml.c6i.12xlarge", + "ml.g4dn.12xlarge", + "ml.c7i.12xlarge", + "ml.c6i.24xlarge", + "ml.g4dn.2xlarge", + "ml.c7i.24xlarge", + "ml.c7i.2xlarge", + "ml.c4.8xlarge", + "ml.c6i.2xlarge", + "ml.g4dn.4xlarge", + "ml.c7i.48xlarge", + "ml.c7i.4xlarge", + "ml.c6i.16xlarge", + "ml.c5.9xlarge", + "ml.g4dn.16xlarge", + "ml.c7i.16xlarge", + "ml.c6i.4xlarge", + "ml.c5.xlarge", + "ml.c4.xlarge", + "ml.g4dn.8xlarge", + "ml.c7i.8xlarge", + "ml.c7i.large", + "ml.g5.xlarge", + "ml.c6i.8xlarge", + "ml.c6i.large", + "ml.g5.12xlarge", + "ml.g5.24xlarge", + "ml.m7i.2xlarge", + "ml.c5.18xlarge", + "ml.g5.48xlarge", + "ml.m6i.2xlarge", + "ml.g5.16xlarge", + "ml.m7i.4xlarge", + "ml.p3.2xlarge", + "ml.r6i.32xlarge", + "ml.m6i.4xlarge", + "ml.m5.xlarge", + "ml.m4.10xlarge", + "ml.r6i.xlarge", + "ml.m5.12xlarge", + "ml.m4.xlarge", + "ml.r7i.2xlarge", + "ml.r7i.xlarge", + "ml.r6i.12xlarge", + "ml.m5.24xlarge", + "ml.r7i.12xlarge", + "ml.m7i.8xlarge", + "ml.m7i.large", + "ml.r6i.24xlarge", + "ml.r6i.2xlarge", + "ml.m4.2xlarge", + "ml.r7i.24xlarge", + "ml.r7i.4xlarge", + "ml.m6i.8xlarge", + "ml.m6i.large", + "ml.m5.2xlarge", + "ml.p2.8xlarge", + "ml.r6i.4xlarge", + "ml.m6i.32xlarge", + "ml.p3.8xlarge", + "ml.m4.4xlarge" + ] + }, + "InferenceOutputConfiguration":{ + "type":"structure", + "required":["members"], + "members":{ + "accept":{ + "shape":"InferenceOutputConfigurationAcceptString", + "documentation":"

The MIME type used to specify the output data.

" + }, + "members":{ + "shape":"InferenceReceiverMembers", + "documentation":"

Defines the members that can receive inference output.

" + } + }, + "documentation":"

Configuration information about how the inference output is stored.

" + }, + "InferenceOutputConfigurationAcceptString":{ + "type":"string", + "max":256, + "min":0, + "pattern":".*" + }, + "InferenceReceiverMember":{ + "type":"structure", + "required":["accountId"], + "members":{ + "accountId":{ + "shape":"AccountId", + "documentation":"

The account ID of the member that can receive inference results.

" + } + }, + "documentation":"

Defines who will receive inference results.

" + }, + "InferenceReceiverMembers":{ + "type":"list", + "member":{"shape":"InferenceReceiverMember"}, + "max":1, + "min":1 + }, + "InferenceResourceConfig":{ + "type":"structure", + "required":["instanceType"], + "members":{ + "instanceType":{ + "shape":"InferenceInstanceType", + "documentation":"

The type of instance that is used to perform model inference.

" + }, + "instanceCount":{ + "shape":"InferenceResourceConfigInstanceCountInteger", + "documentation":"

The number of instances to use.

" + } + }, + "documentation":"

Defines the resources used to perform model inference.

" + }, + "InferenceResourceConfigInstanceCountInteger":{ + "type":"integer", + "box":true, + "max":10, + "min":1 + }, + "InputChannel":{ + "type":"structure", + "required":[ + "dataSource", + "roleArn" + ], + "members":{ + "dataSource":{ + "shape":"InputChannelDataSource", + "documentation":"

The data source that is used to create the ML input channel.

" + }, + "roleArn":{ + "shape":"IamRoleArn", + "documentation":"

The ARN of the IAM role that Clean Rooms ML can assume to read the data referred to in the dataSource field the input channel.

Passing a role across AWS accounts is not allowed. If you pass a role that isn't in your account, you get an AccessDeniedException error.

" + } + }, + "documentation":"

Provides information about the data source that is used to create an ML input channel.

" + }, + "InputChannelDataSource":{ + "type":"structure", + "members":{ + "protectedQueryInputParameters":{"shape":"ProtectedQueryInputParameters"} + }, + "documentation":"

Provides the data source that is used to define an input channel.

", + "union":true + }, + "InstanceType":{ + "type":"string", + "enum":[ + "ml.m4.xlarge", + "ml.m4.2xlarge", + "ml.m4.4xlarge", + "ml.m4.10xlarge", + "ml.m4.16xlarge", + "ml.g4dn.xlarge", + "ml.g4dn.2xlarge", + "ml.g4dn.4xlarge", + "ml.g4dn.8xlarge", + "ml.g4dn.12xlarge", + "ml.g4dn.16xlarge", + "ml.m5.large", + "ml.m5.xlarge", + "ml.m5.2xlarge", + "ml.m5.4xlarge", + "ml.m5.12xlarge", + "ml.m5.24xlarge", + "ml.c4.xlarge", + "ml.c4.2xlarge", + "ml.c4.4xlarge", + "ml.c4.8xlarge", + "ml.p2.xlarge", + "ml.p2.8xlarge", + "ml.p2.16xlarge", + "ml.p3.2xlarge", + "ml.p3.8xlarge", + "ml.p3.16xlarge", + "ml.p3dn.24xlarge", + "ml.p4d.24xlarge", + "ml.p4de.24xlarge", + "ml.p5.48xlarge", + "ml.c5.xlarge", + "ml.c5.2xlarge", + "ml.c5.4xlarge", + "ml.c5.9xlarge", + "ml.c5.18xlarge", + "ml.c5n.xlarge", + "ml.c5n.2xlarge", + "ml.c5n.4xlarge", + "ml.c5n.9xlarge", + "ml.c5n.18xlarge", + "ml.g5.xlarge", + "ml.g5.2xlarge", + "ml.g5.4xlarge", + "ml.g5.8xlarge", + "ml.g5.16xlarge", + "ml.g5.12xlarge", + "ml.g5.24xlarge", + "ml.g5.48xlarge", + "ml.trn1.2xlarge", + "ml.trn1.32xlarge", + "ml.trn1n.32xlarge", + "ml.m6i.large", + "ml.m6i.xlarge", + "ml.m6i.2xlarge", + "ml.m6i.4xlarge", + "ml.m6i.8xlarge", + "ml.m6i.12xlarge", + "ml.m6i.16xlarge", + "ml.m6i.24xlarge", + "ml.m6i.32xlarge", + "ml.c6i.xlarge", + "ml.c6i.2xlarge", + "ml.c6i.8xlarge", + "ml.c6i.4xlarge", + "ml.c6i.12xlarge", + "ml.c6i.16xlarge", + "ml.c6i.24xlarge", + "ml.c6i.32xlarge", + "ml.r5d.large", + "ml.r5d.xlarge", + "ml.r5d.2xlarge", + "ml.r5d.4xlarge", + "ml.r5d.8xlarge", + "ml.r5d.12xlarge", + "ml.r5d.16xlarge", + "ml.r5d.24xlarge", + "ml.t3.medium", + "ml.t3.large", + "ml.t3.xlarge", + "ml.t3.2xlarge", + "ml.r5.large", + "ml.r5.xlarge", + "ml.r5.2xlarge", + "ml.r5.4xlarge", + "ml.r5.8xlarge", + "ml.r5.12xlarge", + "ml.r5.16xlarge", + "ml.r5.24xlarge" + ] + }, + "KmsKeyArn":{ + "type":"string", + "max":2048, + "min":20, + "pattern":"arn:aws[-a-z]*:kms:[-a-z0-9]+:[0-9]{12}:key/.+" + }, + "ListAudienceExportJobsRequest":{ + "type":"structure", + "members":{ + "nextToken":{ + "shape":"NextToken", + "documentation":"

The token value retrieved from a previous call to access the next page of results.

", + "location":"querystring", + "locationName":"nextToken" + }, + "maxResults":{ + "shape":"MaxResults", + "documentation":"

The maximum size of the results that is returned per call.

", + "location":"querystring", + "locationName":"maxResults" + }, + "audienceGenerationJobArn":{ + "shape":"AudienceGenerationJobArn", + "documentation":"

The Amazon Resource Name (ARN) of the audience generation job that you are interested in.

", + "location":"querystring", + "locationName":"audienceGenerationJobArn" + } + } + }, + "ListAudienceExportJobsResponse":{ + "type":"structure", + "required":["audienceExportJobs"], + "members":{ + "nextToken":{ + "shape":"NextToken", + "documentation":"

The token value used to access the next page of results.

" + }, + "audienceExportJobs":{ + "shape":"AudienceExportJobList", + "documentation":"

The audience export jobs that match the request.

" + } + } + }, + "ListAudienceGenerationJobsRequest":{ + "type":"structure", + "members":{ + "nextToken":{ + "shape":"NextToken", + "documentation":"

The token value retrieved from a previous call to access the next page of results.

", + "location":"querystring", + "locationName":"nextToken" + }, + "maxResults":{ + "shape":"MaxResults", + "documentation":"

The maximum size of the results that is returned per call.

", + "location":"querystring", + "locationName":"maxResults" + }, + "configuredAudienceModelArn":{ + "shape":"ConfiguredAudienceModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured audience model that was used for the audience generation jobs that you are interested in.

", + "location":"querystring", "locationName":"configuredAudienceModelArn" + }, + "collaborationId":{ + "shape":"UUID", + "documentation":"

The identifier of the collaboration that contains the audience generation jobs that you are interested in.

", + "location":"querystring", + "locationName":"collaborationId" + } + } + }, + "ListAudienceGenerationJobsResponse":{ + "type":"structure", + "required":["audienceGenerationJobs"], + "members":{ + "nextToken":{ + "shape":"NextToken", + "documentation":"

The token value used to access the next page of results.

" + }, + "audienceGenerationJobs":{ + "shape":"AudienceGenerationJobList", + "documentation":"

The audience generation jobs that match the request.

" + } + } + }, + "ListAudienceModelsRequest":{ + "type":"structure", + "members":{ + "nextToken":{ + "shape":"NextToken", + "documentation":"

The token value retrieved from a previous call to access the next page of results.

", + "location":"querystring", + "locationName":"nextToken" + }, + "maxResults":{ + "shape":"MaxResults", + "documentation":"

The maximum size of the results that is returned per call.

", + "location":"querystring", + "locationName":"maxResults" + } + } + }, + "ListAudienceModelsResponse":{ + "type":"structure", + "required":["audienceModels"], + "members":{ + "nextToken":{ + "shape":"NextToken", + "documentation":"

The token value used to access the next page of results.

" + }, + "audienceModels":{ + "shape":"AudienceModelList", + "documentation":"

The audience models that match the request.

" + } + } + }, + "ListCollaborationConfiguredModelAlgorithmAssociationsRequest":{ + "type":"structure", + "required":["collaborationIdentifier"], + "members":{ + "nextToken":{ + "shape":"NextToken", + "documentation":"

The token value retrieved from a previous call to access the next page of results.

", + "location":"querystring", + "locationName":"nextToken" + }, + "maxResults":{ + "shape":"MaxResults", + "documentation":"

The maximum size of the results that is returned per call.

", + "location":"querystring", + "locationName":"maxResults" + }, + "collaborationIdentifier":{ + "shape":"UUID", + "documentation":"

The collaboration ID of the collaboration that contains the configured model algorithm associations that you are interested in.

", + "location":"uri", + "locationName":"collaborationIdentifier" + } + } + }, + "ListCollaborationConfiguredModelAlgorithmAssociationsResponse":{ + "type":"structure", + "required":["collaborationConfiguredModelAlgorithmAssociations"], + "members":{ + "nextToken":{ + "shape":"NextToken", + "documentation":"

The token value used to access the next page of results.

" + }, + "collaborationConfiguredModelAlgorithmAssociations":{ + "shape":"CollaborationConfiguredModelAlgorithmAssociationList", + "documentation":"

The configured model algorithm associations that belong to this collaboration.

" + } + } + }, + "ListCollaborationMLInputChannelsRequest":{ + "type":"structure", + "required":["collaborationIdentifier"], + "members":{ + "nextToken":{ + "shape":"NextToken", + "documentation":"

The token value retrieved from a previous call to access the next page of results.

", + "location":"querystring", + "locationName":"nextToken" + }, + "maxResults":{ + "shape":"MaxResults", + "documentation":"

The maximum number of results to return.

", + "location":"querystring", + "locationName":"maxResults" + }, + "collaborationIdentifier":{ + "shape":"UUID", + "documentation":"

The collaboration ID of the collaboration that contains the ML input channels that you want to list.

", + "location":"uri", + "locationName":"collaborationIdentifier" + } + } + }, + "ListCollaborationMLInputChannelsResponse":{ + "type":"structure", + "required":["collaborationMLInputChannelsList"], + "members":{ + "nextToken":{ + "shape":"NextToken", + "documentation":"

The token value used to access the next page of results.

" + }, + "collaborationMLInputChannelsList":{ + "shape":"CollaborationMLInputChannelsList", + "documentation":"

The list of ML input channels that you wanted.

" } } }, - "GetConfiguredAudienceModelPolicyResponse":{ + "ListCollaborationTrainedModelExportJobsRequest":{ "type":"structure", "required":[ - "configuredAudienceModelArn", - "configuredAudienceModelPolicy", - "policyHash" + "collaborationIdentifier", + "trainedModelArn" ], "members":{ - "configuredAudienceModelArn":{ - "shape":"ConfiguredAudienceModelArn", - "documentation":"

The Amazon Resource Name (ARN) of the configured audience model.

" + "nextToken":{ + "shape":"NextToken", + "documentation":"

The token value retrieved from a previous call to access the next page of results.

", + "location":"querystring", + "locationName":"nextToken" }, - "configuredAudienceModelPolicy":{ - "shape":"ResourcePolicy", - "documentation":"

The configured audience model policy. This is a JSON IAM resource policy.

" + "maxResults":{ + "shape":"MaxResults", + "documentation":"

The maximum size of the results that is returned per call.

", + "location":"querystring", + "locationName":"maxResults" }, - "policyHash":{ - "shape":"Hash", - "documentation":"

A cryptographic hash of the contents of the policy used to prevent unexpected concurrent modification of the policy.

" + "collaborationIdentifier":{ + "shape":"UUID", + "documentation":"

The collaboration ID of the collaboration that contains the trained model export jobs that you are interested in.

", + "location":"uri", + "locationName":"collaborationIdentifier" + }, + "trainedModelArn":{ + "shape":"TrainedModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the trained model that was used to create the export jobs that you are interested in.

", + "location":"uri", + "locationName":"trainedModelArn" } } }, - "GetConfiguredAudienceModelRequest":{ + "ListCollaborationTrainedModelExportJobsResponse":{ "type":"structure", - "required":["configuredAudienceModelArn"], + "required":["collaborationTrainedModelExportJobs"], "members":{ - "configuredAudienceModelArn":{ - "shape":"ConfiguredAudienceModelArn", - "documentation":"

The Amazon Resource Name (ARN) of the configured audience model that you are interested in.

", - "location":"uri", - "locationName":"configuredAudienceModelArn" + "nextToken":{ + "shape":"NextToken", + "documentation":"

The token value used to access the next page of results.

" + }, + "collaborationTrainedModelExportJobs":{ + "shape":"CollaborationTrainedModelExportJobList", + "documentation":"

The exports jobs that exist for the requested trained model in the requested collaboration.

" } } }, - "GetConfiguredAudienceModelResponse":{ + "ListCollaborationTrainedModelInferenceJobsRequest":{ "type":"structure", - "required":[ - "createTime", - "updateTime", - "configuredAudienceModelArn", - "name", - "audienceModelArn", - "outputConfig", - "status", - "sharedAudienceMetrics" - ], + "required":["collaborationIdentifier"], "members":{ - "createTime":{ - "shape":"SyntheticTimestamp_date_time", - "documentation":"

The time at which the configured audience model was created.

" - }, - "updateTime":{ - "shape":"SyntheticTimestamp_date_time", - "documentation":"

The most recent time at which the configured audience model was updated.

" - }, - "configuredAudienceModelArn":{ - "shape":"ConfiguredAudienceModelArn", - "documentation":"

The Amazon Resource Name (ARN) of the configured audience model.

" - }, - "name":{ - "shape":"NameString", - "documentation":"

The name of the configured audience model.

" - }, - "audienceModelArn":{ - "shape":"AudienceModelArn", - "documentation":"

The Amazon Resource Name (ARN) of the audience model used for this configured audience model.

" - }, - "outputConfig":{ - "shape":"ConfiguredAudienceModelOutputConfig", - "documentation":"

The output configuration of the configured audience model

" - }, - "description":{ - "shape":"ResourceDescription", - "documentation":"

The description of the configured audience model.

" - }, - "status":{ - "shape":"ConfiguredAudienceModelStatus", - "documentation":"

The status of the configured audience model.

" - }, - "sharedAudienceMetrics":{ - "shape":"MetricsList", - "documentation":"

Whether audience metrics are shared.

" - }, - "minMatchingSeedSize":{ - "shape":"MinMatchingSeedSize", - "documentation":"

The minimum number of users from the seed audience that must match with users in the training data of the audience model.

" + "nextToken":{ + "shape":"NextToken", + "documentation":"

The token value retrieved from a previous call to access the next page of results.

", + "location":"querystring", + "locationName":"nextToken" }, - "audienceSizeConfig":{ - "shape":"AudienceSizeConfig", - "documentation":"

The list of output sizes of audiences that can be created using this configured audience model. A request to StartAudienceGenerationJob that uses this configured audience model must have an audienceSize selected from this list. You can use the ABSOLUTE AudienceSize to configure out audience sizes using the count of identifiers in the output. You can use the Percentage AudienceSize to configure sizes in the range 1-100 percent.

" + "maxResults":{ + "shape":"MaxResults", + "documentation":"

The maximum size of the results that is returned per call.

", + "location":"querystring", + "locationName":"maxResults" }, - "tags":{ - "shape":"TagMap", - "documentation":"

The tags that are associated to this configured audience model.

" + "collaborationIdentifier":{ + "shape":"UUID", + "documentation":"

The collaboration ID of the collaboration that contains the trained model inference jobs that you are interested in.

", + "location":"uri", + "locationName":"collaborationIdentifier" }, - "childResourceTagOnCreatePolicy":{ - "shape":"TagOnCreatePolicy", - "documentation":"

Provides the childResourceTagOnCreatePolicy that was used for this configured audience model.

" + "trainedModelArn":{ + "shape":"TrainedModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the trained model that was used to create the trained model inference jobs that you are interested in.

", + "location":"querystring", + "locationName":"trainedModelArn" } } }, - "GetTrainingDatasetRequest":{ + "ListCollaborationTrainedModelInferenceJobsResponse":{ "type":"structure", - "required":["trainingDatasetArn"], + "required":["collaborationTrainedModelInferenceJobs"], "members":{ - "trainingDatasetArn":{ - "shape":"TrainingDatasetArn", - "documentation":"

The Amazon Resource Name (ARN) of the training dataset that you are interested in.

", - "location":"uri", - "locationName":"trainingDatasetArn" + "nextToken":{ + "shape":"NextToken", + "documentation":"

The token value used to access the next page of results.

" + }, + "collaborationTrainedModelInferenceJobs":{ + "shape":"CollaborationTrainedModelInferenceJobList", + "documentation":"

The trained model inference jobs that you are interested in.

" } } }, - "GetTrainingDatasetResponse":{ + "ListCollaborationTrainedModelsRequest":{ "type":"structure", - "required":[ - "createTime", - "updateTime", - "trainingDatasetArn", - "name", - "trainingData", - "status", - "roleArn" - ], + "required":["collaborationIdentifier"], "members":{ - "createTime":{ - "shape":"SyntheticTimestamp_date_time", - "documentation":"

The time at which the training dataset was created.

" - }, - "updateTime":{ - "shape":"SyntheticTimestamp_date_time", - "documentation":"

The most recent time at which the training dataset was updated.

" - }, - "trainingDatasetArn":{ - "shape":"TrainingDatasetArn", - "documentation":"

The Amazon Resource Name (ARN) of the training dataset.

" - }, - "name":{ - "shape":"NameString", - "documentation":"

The name of the training dataset.

" - }, - "trainingData":{ - "shape":"DatasetList", - "documentation":"

Metadata about the requested training data.

" - }, - "status":{ - "shape":"TrainingDatasetStatus", - "documentation":"

The status of the training dataset.

" - }, - "roleArn":{ - "shape":"IamRoleArn", - "documentation":"

The IAM role used to read the training data.

" + "nextToken":{ + "shape":"NextToken", + "documentation":"

The token value retrieved from a previous call to access the next page of results.

", + "location":"querystring", + "locationName":"nextToken" }, - "tags":{ - "shape":"TagMap", - "documentation":"

The tags that are assigned to this training dataset.

" + "maxResults":{ + "shape":"MaxResults", + "documentation":"

The maximum size of the results that is returned per call.

", + "location":"querystring", + "locationName":"maxResults" }, - "description":{ - "shape":"ResourceDescription", - "documentation":"

The description of the training dataset.

" + "collaborationIdentifier":{ + "shape":"UUID", + "documentation":"

The collaboration ID of the collaboration that contains the trained models you are interested in.

", + "location":"uri", + "locationName":"collaborationIdentifier" } } }, - "GlueDataSource":{ + "ListCollaborationTrainedModelsResponse":{ "type":"structure", - "required":[ - "tableName", - "databaseName" - ], + "required":["collaborationTrainedModels"], "members":{ - "tableName":{ - "shape":"GlueTableName", - "documentation":"

The Glue table that contains the training data.

" - }, - "databaseName":{ - "shape":"GlueDatabaseName", - "documentation":"

The Glue database that contains the training data.

" + "nextToken":{ + "shape":"NextToken", + "documentation":"

The token value used to access the next page of results.

" }, - "catalogId":{ - "shape":"AccountId", - "documentation":"

The Glue catalog that contains the training data.

" + "collaborationTrainedModels":{ + "shape":"CollaborationTrainedModelList", + "documentation":"

The trained models in the collaboration that you requested.

" } - }, - "documentation":"

Defines the Glue data source that contains the training data.

" - }, - "GlueDatabaseName":{ - "type":"string", - "max":128, - "min":1, - "pattern":"[a-zA-Z0-9_](([a-zA-Z0-9_]+-)*([a-zA-Z0-9_]+))?" - }, - "GlueTableName":{ - "type":"string", - "max":128, - "min":1, - "pattern":"[a-zA-Z0-9_](([a-zA-Z0-9_ ]+-)*([a-zA-Z0-9_ ]+))?" - }, - "Hash":{ - "type":"string", - "max":128, - "min":64, - "pattern":"[0-9a-f]+" - }, - "IamRoleArn":{ - "type":"string", - "max":2048, - "min":20, - "pattern":"arn:aws[-a-z]*:iam::[0-9]{12}:role/.+" - }, - "KmsKeyArn":{ - "type":"string", - "max":2048, - "min":20, - "pattern":"arn:aws[-a-z]*:kms:[-a-z0-9]+:[0-9]{12}:key/.+" + } }, - "ListAudienceExportJobsRequest":{ + "ListConfiguredAudienceModelsRequest":{ "type":"structure", "members":{ "nextToken":{ @@ -1555,31 +4481,26 @@ "documentation":"

The maximum size of the results that is returned per call.

", "location":"querystring", "locationName":"maxResults" - }, - "audienceGenerationJobArn":{ - "shape":"AudienceGenerationJobArn", - "documentation":"

The Amazon Resource Name (ARN) of the audience generation job that you are interested in.

", - "location":"querystring", - "locationName":"audienceGenerationJobArn" } } }, - "ListAudienceExportJobsResponse":{ + "ListConfiguredAudienceModelsResponse":{ "type":"structure", - "required":["audienceExportJobs"], + "required":["configuredAudienceModels"], "members":{ "nextToken":{ "shape":"NextToken", - "documentation":"

The token value retrieved from a previous call to access the next page of results.

" + "documentation":"

The token value used to access the next page of results.

" }, - "audienceExportJobs":{ - "shape":"AudienceExportJobList", - "documentation":"

The audience export jobs that match the request.

" + "configuredAudienceModels":{ + "shape":"ConfiguredAudienceModelList", + "documentation":"

The configured audience models.

" } } }, - "ListAudienceGenerationJobsRequest":{ + "ListConfiguredModelAlgorithmAssociationsRequest":{ "type":"structure", + "required":["membershipIdentifier"], "members":{ "nextToken":{ "shape":"NextToken", @@ -1593,35 +4514,29 @@ "location":"querystring", "locationName":"maxResults" }, - "configuredAudienceModelArn":{ - "shape":"ConfiguredAudienceModelArn", - "documentation":"

The Amazon Resource Name (ARN) of the configured audience model that was used for the audience generation jobs that you are interested in.

", - "location":"querystring", - "locationName":"configuredAudienceModelArn" - }, - "collaborationId":{ + "membershipIdentifier":{ "shape":"UUID", - "documentation":"

The identifier of the collaboration that contains the audience generation jobs that you are interested in.

", - "location":"querystring", - "locationName":"collaborationId" + "documentation":"

The membership ID of the member that created the configured model algorithm associations you are interested in.

", + "location":"uri", + "locationName":"membershipIdentifier" } } }, - "ListAudienceGenerationJobsResponse":{ + "ListConfiguredModelAlgorithmAssociationsResponse":{ "type":"structure", - "required":["audienceGenerationJobs"], + "required":["configuredModelAlgorithmAssociations"], "members":{ "nextToken":{ "shape":"NextToken", - "documentation":"

The token value retrieved from a previous call to access the next page of results.

" + "documentation":"

The token value used to access the next page of results.

" }, - "audienceGenerationJobs":{ - "shape":"AudienceGenerationJobList", - "documentation":"

The audience generation jobs that match the request.

" + "configuredModelAlgorithmAssociations":{ + "shape":"ConfiguredModelAlgorithmAssociationList", + "documentation":"

The list of configured model algorithm associations.

" } } }, - "ListAudienceModelsRequest":{ + "ListConfiguredModelAlgorithmsRequest":{ "type":"structure", "members":{ "nextToken":{ @@ -1638,22 +4553,23 @@ } } }, - "ListAudienceModelsResponse":{ + "ListConfiguredModelAlgorithmsResponse":{ "type":"structure", - "required":["audienceModels"], + "required":["configuredModelAlgorithms"], "members":{ "nextToken":{ "shape":"NextToken", - "documentation":"

The token value retrieved from a previous call to access the next page of results.

" + "documentation":"

The token value used to access the next page of results.

" }, - "audienceModels":{ - "shape":"AudienceModelList", - "documentation":"

The audience models that match the request.

" + "configuredModelAlgorithms":{ + "shape":"ConfiguredModelAlgorithmList", + "documentation":"

The list of configured model algorithms.

" } } }, - "ListConfiguredAudienceModelsRequest":{ + "ListMLInputChannelsRequest":{ "type":"structure", + "required":["membershipIdentifier"], "members":{ "nextToken":{ "shape":"NextToken", @@ -1663,23 +4579,29 @@ }, "maxResults":{ "shape":"MaxResults", - "documentation":"

The maximum size of the results that is returned per call.

", + "documentation":"

The maximum number of ML input channels to return.

", "location":"querystring", "locationName":"maxResults" + }, + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the membership that contains the ML input channels that you want to list.

", + "location":"uri", + "locationName":"membershipIdentifier" } } }, - "ListConfiguredAudienceModelsResponse":{ + "ListMLInputChannelsResponse":{ "type":"structure", - "required":["configuredAudienceModels"], + "required":["mlInputChannelsList"], "members":{ "nextToken":{ "shape":"NextToken", - "documentation":"

The token value retrieved from a previous call to access the next page of results.

" + "documentation":"

The token value used to access the next page of results.

" }, - "configuredAudienceModels":{ - "shape":"ConfiguredAudienceModelList", - "documentation":"

The configured audience models.

" + "mlInputChannelsList":{ + "shape":"MLInputChannelsList", + "documentation":"

The list of ML input channels that you wanted.

" } } }, @@ -1705,6 +4627,88 @@ } } }, + "ListTrainedModelInferenceJobsRequest":{ + "type":"structure", + "required":["membershipIdentifier"], + "members":{ + "nextToken":{ + "shape":"NextToken", + "documentation":"

The token value retrieved from a previous call to access the next page of results.

", + "location":"querystring", + "locationName":"nextToken" + }, + "maxResults":{ + "shape":"MaxResults", + "documentation":"

The maximum size of the results that is returned per call.

", + "location":"querystring", + "locationName":"maxResults" + }, + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership

", + "location":"uri", + "locationName":"membershipIdentifier" + }, + "trainedModelArn":{ + "shape":"TrainedModelArn", + "documentation":"

The Amazon Resource Name (ARN) of a trained model that was used to create the trained model inference jobs that you are interested in.

", + "location":"querystring", + "locationName":"trainedModelArn" + } + } + }, + "ListTrainedModelInferenceJobsResponse":{ + "type":"structure", + "required":["trainedModelInferenceJobs"], + "members":{ + "nextToken":{ + "shape":"NextToken", + "documentation":"

The token value used to access the next page of results.

" + }, + "trainedModelInferenceJobs":{ + "shape":"TrainedModelInferenceJobList", + "documentation":"

Returns the requested trained model inference jobs.

" + } + } + }, + "ListTrainedModelsRequest":{ + "type":"structure", + "required":["membershipIdentifier"], + "members":{ + "nextToken":{ + "shape":"NextToken", + "documentation":"

The token value retrieved from a previous call to access the next page of results.

", + "location":"querystring", + "locationName":"nextToken" + }, + "maxResults":{ + "shape":"MaxResults", + "documentation":"

The maximum size of the results that is returned per call.

", + "location":"querystring", + "locationName":"maxResults" + }, + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the member that created the trained models you are interested in.

", + "location":"uri", + "locationName":"membershipIdentifier" + } + } + }, + "ListTrainedModelsResponse":{ + "type":"structure", + "required":["trainedModels"], + "members":{ + "nextToken":{ + "shape":"NextToken", + "documentation":"

The token value used to access the next page of results.

" + }, + "trainedModels":{ + "shape":"TrainedModelList", + "documentation":"

The list of trained models.

" + } + } + }, "ListTrainingDatasetsRequest":{ "type":"structure", "members":{ @@ -1728,7 +4732,7 @@ "members":{ "nextToken":{ "shape":"NextToken", - "documentation":"

The token value retrieved from a previous call to access the next page of results.

" + "documentation":"

The token value used to access the next page of results.

" }, "trainingDatasets":{ "shape":"TrainingDatasetList", @@ -1736,24 +4740,252 @@ } } }, + "LogsConfigurationPolicy":{ + "type":"structure", + "required":["allowedAccountIds"], + "members":{ + "allowedAccountIds":{ + "shape":"AccountIdList", + "documentation":"

A list of account IDs that are allowed to access the logs.

" + }, + "filterPattern":{ + "shape":"LogsConfigurationPolicyFilterPatternString", + "documentation":"

A regular expression pattern that is used to parse the logs and return information that matches the pattern.

" + } + }, + "documentation":"

Provides the information necessary for a user to access the logs.

" + }, + "LogsConfigurationPolicyFilterPatternString":{ + "type":"string", + "max":1024, + "min":0 + }, + "LogsConfigurationPolicyList":{ + "type":"list", + "member":{"shape":"LogsConfigurationPolicy"}, + "max":5, + "min":1 + }, + "LogsStatus":{ + "type":"string", + "enum":[ + "PUBLISH_SUCCEEDED", + "PUBLISH_FAILED" + ] + }, + "MLInputChannelArn":{ + "type":"string", + "max":2048, + "min":20, + "pattern":"arn:aws[-a-z]*:cleanrooms-ml:[-a-z0-9]+:[0-9]{12}:membership/[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}/ml-input-channel/[-a-zA-Z0-9_/.]+" + }, + "MLInputChannelStatus":{ + "type":"string", + "enum":[ + "CREATE_PENDING", + "CREATE_IN_PROGRESS", + "CREATE_FAILED", + "ACTIVE", + "DELETE_PENDING", + "DELETE_IN_PROGRESS", + "DELETE_FAILED", + "INACTIVE" + ] + }, + "MLInputChannelSummary":{ + "type":"structure", + "required":[ + "createTime", + "updateTime", + "membershipIdentifier", + "collaborationIdentifier", + "name", + "configuredModelAlgorithmAssociations", + "mlInputChannelArn", + "status" + ], + "members":{ + "createTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The time at which the ML input channel was created.

" + }, + "updateTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The most recent time at which the ML input channel was updated.

" + }, + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the membership that contains the ML input channel.

" + }, + "collaborationIdentifier":{ + "shape":"UUID", + "documentation":"

The collaboration ID of the collaboration that contains the ML input channel.

" + }, + "name":{ + "shape":"NameString", + "documentation":"

The name of the ML input channel.

" + }, + "configuredModelAlgorithmAssociations":{ + "shape":"MLInputChannelSummaryConfiguredModelAlgorithmAssociationsList", + "documentation":"

The associated configured model algorithms used to create the ML input channel.

" + }, + "protectedQueryIdentifier":{ + "shape":"UUID", + "documentation":"

The ID of the protected query that was used to create the ML input channel.

" + }, + "mlInputChannelArn":{ + "shape":"MLInputChannelArn", + "documentation":"

The Amazon Resource Name (ARN) of the ML input channel.

" + }, + "status":{ + "shape":"MLInputChannelStatus", + "documentation":"

The status of the ML input channel.

" + }, + "description":{ + "shape":"ResourceDescription", + "documentation":"

The description of the ML input channel.

" + } + }, + "documentation":"

Provides summary information about the ML input channel.

" + }, + "MLInputChannelSummaryConfiguredModelAlgorithmAssociationsList":{ + "type":"list", + "member":{"shape":"ConfiguredModelAlgorithmAssociationArn"}, + "max":1, + "min":1 + }, + "MLInputChannelsList":{ + "type":"list", + "member":{"shape":"MLInputChannelSummary"} + }, + "MLOutputConfiguration":{ + "type":"structure", + "required":["roleArn"], + "members":{ + "destination":{ + "shape":"Destination", + "documentation":"

The Amazon S3 location where exported model artifacts are stored.

" + }, + "roleArn":{ + "shape":"IamRoleArn", + "documentation":"

The Amazon Resource Name (ARN) of the service access role that is used to store the model artifacts.

" + } + }, + "documentation":"

Configuration information about how the exported model artifacts are stored.

" + }, "MaxResults":{ "type":"integer", "box":true, "max":100, "min":1 }, + "MetricDefinition":{ + "type":"structure", + "required":[ + "name", + "regex" + ], + "members":{ + "name":{ + "shape":"MetricName", + "documentation":"

The name of the model metric.

" + }, + "regex":{ + "shape":"MetricRegex", + "documentation":"

The regular expression statement that defines how the model metric is reported.

" + } + }, + "documentation":"

Information about the model metric that is reported for a trained model.

" + }, + "MetricDefinitionList":{ + "type":"list", + "member":{"shape":"MetricDefinition"}, + "max":40, + "min":0 + }, + "MetricName":{ + "type":"string", + "max":255, + "min":1, + "pattern":".+" + }, + "MetricRegex":{ + "type":"string", + "max":500, + "min":1, + "pattern":".+" + }, + "MetricsConfigurationPolicy":{ + "type":"structure", + "required":["noiseLevel"], + "members":{ + "noiseLevel":{ + "shape":"NoiseLevelType", + "documentation":"

The noise level for the generated metrics.

" + } + }, + "documentation":"

Provides the configuration policy for metrics generation.

" + }, "MetricsList":{ "type":"list", "member":{"shape":"SharedAudienceMetrics"}, "max":1, "min":1 }, + "MetricsStatus":{ + "type":"string", + "enum":[ + "PUBLISH_SUCCEEDED", + "PUBLISH_FAILED" + ] + }, "MinMatchingSeedSize":{ "type":"integer", "box":true, "max":500000, "min":25 }, + "ModelInferenceDataSource":{ + "type":"structure", + "required":["mlInputChannelArn"], + "members":{ + "mlInputChannelArn":{ + "shape":"MLInputChannelArn", + "documentation":"

The Amazon Resource Name (ARN) of the ML input channel for this model inference data source.

" + } + }, + "documentation":"

Defines information about the data source used for model inference.

" + }, + "ModelTrainingDataChannel":{ + "type":"structure", + "required":[ + "mlInputChannelArn", + "channelName" + ], + "members":{ + "mlInputChannelArn":{ + "shape":"MLInputChannelArn", + "documentation":"

The Amazon Resource Name (ARN) of the ML input channel for this model training data channel.

" + }, + "channelName":{ + "shape":"ModelTrainingDataChannelName", + "documentation":"

The name of the training data channel.

" + } + }, + "documentation":"

Information about the model training data channel. A training data channel is a named data source that the training algorithms can consume.

" + }, + "ModelTrainingDataChannelName":{ + "type":"string", + "max":64, + "min":1, + "pattern":"[A-Za-z0-9\\.\\-_]+" + }, + "ModelTrainingDataChannels":{ + "type":"list", + "member":{"shape":"ModelTrainingDataChannel"}, + "max":20, + "min":1 + }, "NameString":{ "type":"string", "max":63, @@ -1765,6 +4997,15 @@ "max":10240, "min":1 }, + "NoiseLevelType":{ + "type":"string", + "enum":[ + "HIGH", + "MEDIUM", + "LOW", + "NONE" + ] + }, "ParameterKey":{ "type":"string", "max":100, @@ -1788,6 +5029,47 @@ "POLICY_MUST_NOT_EXIST" ] }, + "PrivacyConfiguration":{ + "type":"structure", + "required":["policies"], + "members":{ + "policies":{ + "shape":"PrivacyConfigurationPolicies", + "documentation":"

The privacy configuration policies for a configured model algorithm association.

" + } + }, + "documentation":"

Information about the privacy configuration for a configured model algorithm association.

" + }, + "PrivacyConfigurationPolicies":{ + "type":"structure", + "members":{ + "trainedModels":{ + "shape":"TrainedModelsConfigurationPolicy", + "documentation":"

Specifies who will receive the trained models.

" + }, + "trainedModelExports":{ + "shape":"TrainedModelExportsConfigurationPolicy", + "documentation":"

Specifies who will receive the trained model export.

" + }, + "trainedModelInferenceJobs":{ + "shape":"TrainedModelInferenceJobsConfigurationPolicy", + "documentation":"

Specifies who will receive the trained model inference jobs.

" + } + }, + "documentation":"

Information about the privacy configuration policies for a configured model algorithm association.

" + }, + "ProtectedQueryInputParameters":{ + "type":"structure", + "required":["sqlParameters"], + "members":{ + "sqlParameters":{"shape":"ProtectedQuerySQLParameters"}, + "computeConfiguration":{ + "shape":"ComputeConfiguration", + "documentation":"

Provides configuration information for the workers that will perform the protected query.

" + } + }, + "documentation":"

Provides information necessary to perform the protected query.

" + }, "ProtectedQuerySQLParameters":{ "type":"structure", "members":{ @@ -1809,7 +5091,7 @@ }, "ProtectedQuerySQLParametersQueryStringString":{ "type":"string", - "max":90000, + "max":500000, "min":0 }, "PutConfiguredAudienceModelPolicyRequest":{ @@ -1856,22 +5138,81 @@ } } }, + "PutMLConfigurationRequest":{ + "type":"structure", + "required":[ + "membershipIdentifier", + "defaultOutputLocation" + ], + "members":{ + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the member that is being configured.

", + "location":"uri", + "locationName":"membershipIdentifier" + }, + "defaultOutputLocation":{ + "shape":"MLOutputConfiguration", + "documentation":"

The default Amazon S3 location where ML output is stored for the specified member.

" + } + } + }, "RelevanceMetric":{ "type":"structure", "required":["audienceSize"], "members":{ "audienceSize":{"shape":"AudienceSize"}, "score":{ - "shape":"Double", + "shape":"RelevanceMetricScoreDouble", "documentation":"

The relevance score of the generated audience.

" } }, "documentation":"

The relevance score of a generated audience.

" }, + "RelevanceMetricScoreDouble":{ + "type":"double", + "box":true, + "max":10.0, + "min":0.0 + }, "RelevanceMetrics":{ "type":"list", "member":{"shape":"RelevanceMetric"} }, + "ResourceConfig":{ + "type":"structure", + "required":[ + "instanceType", + "volumeSizeInGB" + ], + "members":{ + "instanceCount":{ + "shape":"ResourceConfigInstanceCountInteger", + "documentation":"

The number of resources that are used to train the model.

" + }, + "instanceType":{ + "shape":"InstanceType", + "documentation":"

The instance type that is used to train the model.

" + }, + "volumeSizeInGB":{ + "shape":"ResourceConfigVolumeSizeInGBInteger", + "documentation":"

The maximum size of the instance that is used to train the model.

" + } + }, + "documentation":"

Information about the EC2 resources that are used to train the model.

" + }, + "ResourceConfigInstanceCountInteger":{ + "type":"integer", + "box":true, + "max":1, + "min":1 + }, + "ResourceConfigVolumeSizeInGBInteger":{ + "type":"integer", + "box":true, + "max":8192, + "min":1 + }, "ResourceDescription":{ "type":"string", "max":255, @@ -2004,6 +5345,114 @@ } } }, + "StartTrainedModelExportJobRequest":{ + "type":"structure", + "required":[ + "name", + "trainedModelArn", + "membershipIdentifier", + "outputConfiguration" + ], + "members":{ + "name":{ + "shape":"NameString", + "documentation":"

The name of the trained model export job.

" + }, + "trainedModelArn":{ + "shape":"TrainedModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the trained model that you want to export.

", + "location":"uri", + "locationName":"trainedModelArn" + }, + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the member that is receiving the exported trained model artifacts.

", + "location":"uri", + "locationName":"membershipIdentifier" + }, + "outputConfiguration":{ + "shape":"TrainedModelExportOutputConfiguration", + "documentation":"

The output configuration information for the trained model export job.

" + }, + "description":{ + "shape":"ResourceDescription", + "documentation":"

The description of the trained model export job.

" + } + } + }, + "StartTrainedModelInferenceJobRequest":{ + "type":"structure", + "required":[ + "membershipIdentifier", + "name", + "trainedModelArn", + "resourceConfig", + "outputConfiguration", + "dataSource" + ], + "members":{ + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the membership that contains the trained model inference job.

", + "location":"uri", + "locationName":"membershipIdentifier" + }, + "name":{ + "shape":"NameString", + "documentation":"

The name of the trained model inference job.

" + }, + "trainedModelArn":{ + "shape":"TrainedModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the trained model that is used for this trained model inference job.

" + }, + "configuredModelAlgorithmAssociationArn":{ + "shape":"ConfiguredModelAlgorithmAssociationArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured model algorithm association that is used for this trained model inference job.

" + }, + "resourceConfig":{ + "shape":"InferenceResourceConfig", + "documentation":"

Defines the resource configuration for the trained model inference job.

" + }, + "outputConfiguration":{ + "shape":"InferenceOutputConfiguration", + "documentation":"

Defines the output configuration information for the trained model inference job.

" + }, + "dataSource":{ + "shape":"ModelInferenceDataSource", + "documentation":"

Defines he data source that is used for the trained model inference job.

" + }, + "description":{ + "shape":"ResourceDescription", + "documentation":"

The description of the trained model inference job.

" + }, + "containerExecutionParameters":{ + "shape":"InferenceContainerExecutionParameters", + "documentation":"

The execution parameters for the container.

" + }, + "environment":{ + "shape":"InferenceEnvironmentMap", + "documentation":"

The environment variables to set in the Docker container.

" + }, + "kmsKeyArn":{ + "shape":"KmsKeyArn", + "documentation":"

The Amazon Resource Name (ARN) of the KMS key. This key is used to encrypt and decrypt customer-owned data in the ML inference job and associated data.

" + }, + "tags":{ + "shape":"TagMap", + "documentation":"

The optional metadata that you apply to the resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

The following basic restrictions apply to tags:

" + } + } + }, + "StartTrainedModelInferenceJobResponse":{ + "type":"structure", + "required":["trainedModelInferenceJobArn"], + "members":{ + "trainedModelInferenceJobArn":{ + "shape":"TrainedModelInferenceJobArn", + "documentation":"

The Amazon Resource Name (ARN) of the trained model inference job.

" + } + } + }, "StatusDetails":{ "type":"structure", "members":{ @@ -2018,6 +5467,22 @@ }, "documentation":"

Details about the status of a resource.

" }, + "StoppingCondition":{ + "type":"structure", + "members":{ + "maxRuntimeInSeconds":{ + "shape":"StoppingConditionMaxRuntimeInSecondsInteger", + "documentation":"

The maximum amount of time, in seconds, that model training can run before it is terminated.

" + } + }, + "documentation":"

The criteria used to stop model training.

" + }, + "StoppingConditionMaxRuntimeInSecondsInteger":{ + "type":"integer", + "box":true, + "max":2419200, + "min":1 + }, "String":{"type":"string"}, "SyntheticTimestamp_date_time":{ "type":"timestamp", @@ -2081,7 +5546,337 @@ "type":"string", "max":2048, "min":20, - "pattern":"arn:aws[-a-z]*:cleanrooms-ml:[-a-z0-9]+:[0-9]{12}:(training-dataset|audience-model|configured-audience-model|audience-generation-job)/[-a-zA-Z0-9_/.]+" + "pattern":"arn:aws[-a-z]*:cleanrooms-ml:[-a-z0-9]+:[0-9]{12}:(membership/[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}/(configured-model-algorithm-association|trained-model|trained-model-inference-job|ml-input-channel)|training-dataset|audience-model|configured-audience-model|audience-generation-job|configured-model-algorithm|configured-model-algorithm-association|trained-model|trained-model-inference-job)/[-a-zA-Z0-9_/.]+" + }, + "TrainedModelArn":{ + "type":"string", + "max":2048, + "min":20, + "pattern":"arn:aws[-a-z]*:cleanrooms-ml:[-a-z0-9]+:[0-9]{12}:(membership/[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}/)?trained-model/[-a-zA-Z0-9_/.]+" + }, + "TrainedModelExportFileType":{ + "type":"string", + "enum":[ + "MODEL", + "OUTPUT" + ] + }, + "TrainedModelExportFileTypeList":{ + "type":"list", + "member":{"shape":"TrainedModelExportFileType"}, + "max":2, + "min":1 + }, + "TrainedModelExportJobStatus":{ + "type":"string", + "enum":[ + "CREATE_PENDING", + "CREATE_IN_PROGRESS", + "CREATE_FAILED", + "ACTIVE" + ] + }, + "TrainedModelExportOutputConfiguration":{ + "type":"structure", + "required":["members"], + "members":{ + "members":{ + "shape":"TrainedModelExportReceiverMembers", + "documentation":"

The members that will received the exported trained model output.

" + } + }, + "documentation":"

Information about the output of the trained model export job.

" + }, + "TrainedModelExportReceiverMember":{ + "type":"structure", + "required":["accountId"], + "members":{ + "accountId":{ + "shape":"AccountId", + "documentation":"

The account ID of the member who will receive trained model exports.

" + } + }, + "documentation":"

Provides information about the member who will receive trained model exports.

" + }, + "TrainedModelExportReceiverMembers":{ + "type":"list", + "member":{"shape":"TrainedModelExportReceiverMember"}, + "max":1, + "min":1 + }, + "TrainedModelExportsConfigurationPolicy":{ + "type":"structure", + "required":[ + "maxSize", + "filesToExport" + ], + "members":{ + "maxSize":{ + "shape":"TrainedModelExportsMaxSize", + "documentation":"

The maximum size of the data that can be exported.

" + }, + "filesToExport":{ + "shape":"TrainedModelExportFileTypeList", + "documentation":"

The files that are exported during the trained model export job.

" + } + }, + "documentation":"

Information about how the trained model exports are configured.

" + }, + "TrainedModelExportsMaxSize":{ + "type":"structure", + "required":[ + "unit", + "value" + ], + "members":{ + "unit":{ + "shape":"TrainedModelExportsMaxSizeUnitType", + "documentation":"

The unit of measurement for the data size.

" + }, + "value":{ + "shape":"TrainedModelExportsMaxSizeValue", + "documentation":"

The maximum size of the dataset to export.

" + } + }, + "documentation":"

The maximum size of the trained model metrics that can be exported. If the trained model metrics dataset is larger than this value, it will not be exported.

" + }, + "TrainedModelExportsMaxSizeUnitType":{ + "type":"string", + "enum":["GB"] + }, + "TrainedModelExportsMaxSizeValue":{ + "type":"double", + "box":true, + "max":10.0, + "min":0.01 + }, + "TrainedModelInferenceJobArn":{ + "type":"string", + "max":2048, + "min":20, + "pattern":"arn:aws[-a-z]*:cleanrooms-ml:[-a-z0-9]+:[0-9]{12}:(membership/[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}/)?trained-model-inference-job/[-a-zA-Z0-9_/.]+" + }, + "TrainedModelInferenceJobList":{ + "type":"list", + "member":{"shape":"TrainedModelInferenceJobSummary"} + }, + "TrainedModelInferenceJobStatus":{ + "type":"string", + "enum":[ + "CREATE_PENDING", + "CREATE_IN_PROGRESS", + "CREATE_FAILED", + "ACTIVE", + "CANCEL_PENDING", + "CANCEL_IN_PROGRESS", + "CANCEL_FAILED", + "INACTIVE" + ] + }, + "TrainedModelInferenceJobSummary":{ + "type":"structure", + "required":[ + "trainedModelInferenceJobArn", + "membershipIdentifier", + "trainedModelArn", + "collaborationIdentifier", + "status", + "outputConfiguration", + "name", + "createTime", + "updateTime" + ], + "members":{ + "trainedModelInferenceJobArn":{ + "shape":"TrainedModelInferenceJobArn", + "documentation":"

The Amazon Resource Name (ARN) of the trained model inference job.

" + }, + "configuredModelAlgorithmAssociationArn":{ + "shape":"ConfiguredModelAlgorithmAssociationArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured model algorithm association that is used for the trained model inference job.

" + }, + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the membership that contains the trained model inference job.

" + }, + "trainedModelArn":{ + "shape":"TrainedModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the trained model that is used for the trained model inference job.

" + }, + "collaborationIdentifier":{ + "shape":"UUID", + "documentation":"

The collaboration ID of the collaboration that contains the trained model inference job.

" + }, + "status":{ + "shape":"TrainedModelInferenceJobStatus", + "documentation":"

The status of the trained model inference job.

" + }, + "outputConfiguration":{ + "shape":"InferenceOutputConfiguration", + "documentation":"

The output configuration information of the trained model job.

" + }, + "name":{ + "shape":"NameString", + "documentation":"

The name of the trained model inference job.

" + }, + "description":{ + "shape":"ResourceDescription", + "documentation":"

The description of the trained model inference job.

" + }, + "metricsStatus":{ + "shape":"MetricsStatus", + "documentation":"

The metric status of the trained model inference job.

" + }, + "metricsStatusDetails":{ + "shape":"String", + "documentation":"

Details about the metrics status for the trained model inference job.

" + }, + "logsStatus":{ + "shape":"LogsStatus", + "documentation":"

The log status of the trained model inference job.

" + }, + "logsStatusDetails":{ + "shape":"String", + "documentation":"

Details about the log status for the trained model inference job.

" + }, + "createTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The time at which the trained model inference job was created.

" + }, + "updateTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The most recent time at which the trained model inference job was updated.

" + } + }, + "documentation":"

Provides information about the trained model inference job.

" + }, + "TrainedModelInferenceJobsConfigurationPolicy":{ + "type":"structure", + "members":{ + "containerLogs":{ + "shape":"LogsConfigurationPolicyList", + "documentation":"

The logs container for the trained model inference job.

" + }, + "maxOutputSize":{ + "shape":"TrainedModelInferenceMaxOutputSize", + "documentation":"

The maximum allowed size of the output of the trained model inference job.

" + } + }, + "documentation":"

Provides configuration information for the trained model inference job.

" + }, + "TrainedModelInferenceMaxOutputSize":{ + "type":"structure", + "required":[ + "unit", + "value" + ], + "members":{ + "unit":{ + "shape":"TrainedModelInferenceMaxOutputSizeUnitType", + "documentation":"

The measurement unit to use.

" + }, + "value":{ + "shape":"TrainedModelInferenceMaxOutputSizeValue", + "documentation":"

The maximum output size value.

" + } + }, + "documentation":"

Information about the maximum output size for a trained model inference job.

" + }, + "TrainedModelInferenceMaxOutputSizeUnitType":{ + "type":"string", + "enum":["GB"] + }, + "TrainedModelInferenceMaxOutputSizeValue":{ + "type":"double", + "box":true, + "max":10.0, + "min":0.01 + }, + "TrainedModelList":{ + "type":"list", + "member":{"shape":"TrainedModelSummary"} + }, + "TrainedModelStatus":{ + "type":"string", + "enum":[ + "CREATE_PENDING", + "CREATE_IN_PROGRESS", + "CREATE_FAILED", + "ACTIVE", + "DELETE_PENDING", + "DELETE_IN_PROGRESS", + "DELETE_FAILED", + "INACTIVE", + "CANCEL_PENDING", + "CANCEL_IN_PROGRESS", + "CANCEL_FAILED" + ] + }, + "TrainedModelSummary":{ + "type":"structure", + "required":[ + "createTime", + "updateTime", + "trainedModelArn", + "name", + "membershipIdentifier", + "collaborationIdentifier", + "status", + "configuredModelAlgorithmAssociationArn" + ], + "members":{ + "createTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The time at which the trained model was created.

" + }, + "updateTime":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The most recent time at which the trained model was updated.

" + }, + "trainedModelArn":{ + "shape":"TrainedModelArn", + "documentation":"

The Amazon Resource Name (ARN) of the trained model.

" + }, + "name":{ + "shape":"NameString", + "documentation":"

The name of the trained model.

" + }, + "description":{ + "shape":"ResourceDescription", + "documentation":"

The description of the trained model.

" + }, + "membershipIdentifier":{ + "shape":"UUID", + "documentation":"

The membership ID of the member that created the trained model.

" + }, + "collaborationIdentifier":{ + "shape":"UUID", + "documentation":"

The collaboration ID of the collaboration that contains the trained model.

" + }, + "status":{ + "shape":"TrainedModelStatus", + "documentation":"

The status of the trained model.

" + }, + "configuredModelAlgorithmAssociationArn":{ + "shape":"ConfiguredModelAlgorithmAssociationArn", + "documentation":"

The Amazon Resource Name (ARN) of the configured model algorithm association that was used to create this trained model.

" + } + }, + "documentation":"

Summary information about the trained model.

" + }, + "TrainedModelsConfigurationPolicy":{ + "type":"structure", + "members":{ + "containerLogs":{ + "shape":"LogsConfigurationPolicyList", + "documentation":"

The container for the logs of the trained model.

" + }, + "containerMetrics":{ + "shape":"MetricsConfigurationPolicy", + "documentation":"

The container for the metrics of the trained model.

" + } + }, + "documentation":"

The configuration policy for the trained models.

" }, "TrainingDatasetArn":{ "type":"string", @@ -2224,6 +6019,33 @@ "senderFault":true }, "exception":true + }, + "WorkerComputeConfiguration":{ + "type":"structure", + "members":{ + "type":{ + "shape":"WorkerComputeType", + "documentation":"

The instance type of the compute workers that are used.

" + }, + "number":{ + "shape":"WorkerComputeConfigurationNumberInteger", + "documentation":"

The number of compute workers that are used.

" + } + }, + "documentation":"

Configuration information about the compute workers that perform the transform job.

" + }, + "WorkerComputeConfigurationNumberInteger":{ + "type":"integer", + "box":true, + "max":400, + "min":2 + }, + "WorkerComputeType":{ + "type":"string", + "enum":[ + "CR.1X", + "CR.4X" + ] } }, "documentation":"

Welcome to the Amazon Web Services Clean Rooms ML API Reference.

Amazon Web Services Clean Rooms ML provides a privacy-enhancing method for two parties to identify similar users in their data without the need to share their data with each other. The first party brings the training data to Clean Rooms so that they can create and configure an audience model (lookalike model) and associate it with a collaboration. The second party then brings their seed data to Clean Rooms and generates an audience (lookalike segment) that resembles the training data.

To learn more about Amazon Web Services Clean Rooms ML concepts, procedures, and best practices, see the Clean Rooms User Guide.

To learn more about SQL commands, functions, and conditions supported in Clean Rooms, see the Clean Rooms SQL Reference.

" diff --git a/botocore/data/quicksight/2018-04-01/service-2.json b/botocore/data/quicksight/2018-04-01/service-2.json index f21cb2a381..b979d27108 100644 --- a/botocore/data/quicksight/2018-04-01/service-2.json +++ b/botocore/data/quicksight/2018-04-01/service-2.json @@ -5587,6 +5587,14 @@ "IAM_IDENTITY_CENTER" ] }, + "AuthenticationType":{ + "type":"string", + "enum":[ + "PASSWORD", + "TOKEN", + "X509" + ] + }, "AuthorSpecifiedAggregation":{ "type":"string", "enum":[ @@ -11192,6 +11200,10 @@ "max":128, "min":1 }, + "DatabaseAccessControlRole":{ + "type":"string", + "max":128 + }, "DatabaseGroup":{ "type":"string", "max":64, @@ -18852,6 +18864,11 @@ "type":"list", "member":{"shape":"IdentityName"} }, + "IdentityProviderResourceUri":{ + "type":"string", + "max":2048, + "min":1 + }, "IdentityStore":{ "type":"string", "enum":["QUICKSIGHT"] @@ -22951,6 +22968,31 @@ }, "documentation":"

The measure type field with numerical type columns.

" }, + "OAuthParameters":{ + "type":"structure", + "required":["TokenProviderUrl"], + "members":{ + "TokenProviderUrl":{ + "shape":"TokenProviderUrl", + "documentation":"

The token endpoint URL of the identity provider.

" + }, + "OAuthScope":{ + "shape":"OAuthScope", + "documentation":"

The OAuth scope.

" + }, + "IdentityProviderVpcConnectionProperties":{"shape":"VpcConnectionProperties"}, + "IdentityProviderResourceUri":{ + "shape":"IdentityProviderResourceUri", + "documentation":"

The resource uri of the identity provider.

" + } + }, + "documentation":"

An object that contains information needed to create a data source connection that uses OAuth client credentials. This option is available for data source connections that are made with Snowflake and Starburst.

" + }, + "OAuthScope":{ + "type":"string", + "max":128, + "min":1 + }, "OnClause":{ "type":"string", "max":512, @@ -27803,6 +27845,18 @@ "Warehouse":{ "shape":"Warehouse", "documentation":"

Warehouse.

" + }, + "AuthenticationType":{ + "shape":"AuthenticationType", + "documentation":"

The authentication type that you want to use for your connection. This parameter accepts OAuth and non-OAuth authentication types.

" + }, + "DatabaseAccessControlRole":{ + "shape":"DatabaseAccessControlRole", + "documentation":"

The database access control role.

" + }, + "OAuthParameters":{ + "shape":"OAuthParameters", + "documentation":"

An object that contains information needed to create a data source connection between an Amazon QuickSight account and Snowflake.

" } }, "documentation":"

The parameters for Snowflake.

" @@ -27928,6 +27982,18 @@ "ProductType":{ "shape":"StarburstProductType", "documentation":"

The product type for the Starburst data source.

" + }, + "DatabaseAccessControlRole":{ + "shape":"DatabaseAccessControlRole", + "documentation":"

The database access control role.

" + }, + "AuthenticationType":{ + "shape":"AuthenticationType", + "documentation":"

The authentication type that you want to use for your connection. This parameter accepts OAuth and non-OAuth authentication types.

" + }, + "OAuthParameters":{ + "shape":"OAuthParameters", + "documentation":"

An object that contains information needed to create a data source connection between an Amazon QuickSight account and Starburst.

" } }, "documentation":"

The parameters that are required to connect to a Starburst data source.

" @@ -29935,6 +30001,11 @@ "documentation":"

The value of a time range filter.

This is a union type structure. For this structure to be valid, only one of the attributes can be defined.

" }, "Timestamp":{"type":"timestamp"}, + "TokenProviderUrl":{ + "type":"string", + "max":2048, + "min":1 + }, "TooltipItem":{ "type":"structure", "members":{ diff --git a/botocore/data/resource-explorer-2/2022-07-28/paginators-1.json b/botocore/data/resource-explorer-2/2022-07-28/paginators-1.json index 2acd787094..ed6acb734c 100644 --- a/botocore/data/resource-explorer-2/2022-07-28/paginators-1.json +++ b/botocore/data/resource-explorer-2/2022-07-28/paginators-1.json @@ -35,6 +35,12 @@ "output_token": "NextToken", "limit_key": "MaxResults", "result_key": "Resources" + }, + "ListManagedViews": { + "input_token": "NextToken", + "output_token": "NextToken", + "limit_key": "MaxResults", + "result_key": "ManagedViews" } } } diff --git a/botocore/data/resource-explorer-2/2022-07-28/service-2.json b/botocore/data/resource-explorer-2/2022-07-28/service-2.json index f8625af30e..e38ef1d442 100644 --- a/botocore/data/resource-explorer-2/2022-07-28/service-2.json +++ b/botocore/data/resource-explorer-2/2022-07-28/service-2.json @@ -196,6 +196,25 @@ ], "documentation":"

Retrieves details about the Amazon Web Services Resource Explorer index in the Amazon Web Services Region in which you invoked the operation.

" }, + "GetManagedView":{ + "name":"GetManagedView", + "http":{ + "method":"POST", + "requestUri":"/GetManagedView", + "responseCode":200 + }, + "input":{"shape":"GetManagedViewInput"}, + "output":{"shape":"GetManagedViewOutput"}, + "errors":[ + {"shape":"ResourceNotFoundException"}, + {"shape":"InternalServerException"}, + {"shape":"ValidationException"}, + {"shape":"UnauthorizedException"}, + {"shape":"ThrottlingException"}, + {"shape":"AccessDeniedException"} + ], + "documentation":"

Retrieves details of the specified Amazon Web Services-managed view.

" + }, "GetView":{ "name":"GetView", "http":{ @@ -249,6 +268,24 @@ ], "documentation":"

Retrieves a list of a member's indexes in all Amazon Web Services Regions that are currently collecting resource information for Amazon Web Services Resource Explorer. Only the management account or a delegated administrator with service access enabled can invoke this API call.

" }, + "ListManagedViews":{ + "name":"ListManagedViews", + "http":{ + "method":"POST", + "requestUri":"/ListManagedViews", + "responseCode":200 + }, + "input":{"shape":"ListManagedViewsInput"}, + "output":{"shape":"ListManagedViewsOutput"}, + "errors":[ + {"shape":"InternalServerException"}, + {"shape":"ValidationException"}, + {"shape":"UnauthorizedException"}, + {"shape":"ThrottlingException"}, + {"shape":"AccessDeniedException"} + ], + "documentation":"

Lists the Amazon resource names (ARNs) of the Amazon Web Services-managed views available in the Amazon Web Services Region in which you call this operation.

" + }, "ListResources":{ "name":"ListResources", "http":{ @@ -728,6 +765,30 @@ } } }, + "GetManagedViewInput":{ + "type":"structure", + "required":["ManagedViewArn"], + "members":{ + "ManagedViewArn":{ + "shape":"GetManagedViewInputManagedViewArnString", + "documentation":"

The Amazon resource name (ARN) of the managed view.

" + } + } + }, + "GetManagedViewInputManagedViewArnString":{ + "type":"string", + "max":1011, + "min":1 + }, + "GetManagedViewOutput":{ + "type":"structure", + "members":{ + "ManagedView":{ + "shape":"ManagedView", + "documentation":"

Details about the specified managed view.

" + } + } + }, "GetViewInput":{ "type":"structure", "required":["ViewArn"], @@ -924,6 +985,52 @@ } } }, + "ListManagedViewsInput":{ + "type":"structure", + "members":{ + "MaxResults":{ + "shape":"ListManagedViewsInputMaxResultsInteger", + "documentation":"

The maximum number of results that you want included on each page of the response. If you do not include this parameter, it defaults to a value appropriate to the operation. If additional items exist beyond those included in the current response, the NextToken response element is present and has a value (is not null). Include that value as the NextToken request parameter in the next call to the operation to get the next part of the results.

An API operation can return fewer results than the maximum even when there are more results available. You should check NextToken after every operation to ensure that you receive all of the results.

" + }, + "NextToken":{ + "shape":"ListManagedViewsInputNextTokenString", + "documentation":"

The parameter for receiving additional results if you receive a NextToken response in a previous request. A NextToken response indicates that more output is available. Set this parameter to the value of the previous call's NextToken response to indicate where the output should continue from. The pagination tokens expire after 24 hours.

" + }, + "ServicePrincipal":{ + "shape":"ListManagedViewsInputServicePrincipalString", + "documentation":"

Specifies a service principal name. If specified, then the operation only returns the managed views that are managed by the input service.

" + } + } + }, + "ListManagedViewsInputMaxResultsInteger":{ + "type":"integer", + "box":true, + "max":50, + "min":1 + }, + "ListManagedViewsInputNextTokenString":{ + "type":"string", + "max":2048, + "min":1 + }, + "ListManagedViewsInputServicePrincipalString":{ + "type":"string", + "max":1024, + "min":1 + }, + "ListManagedViewsOutput":{ + "type":"structure", + "members":{ + "ManagedViews":{ + "shape":"ManagedViewArnList", + "documentation":"

The list of managed views available in the Amazon Web Services Region in which you called this operation.

" + }, + "NextToken":{ + "shape":"String", + "documentation":"

If present, indicates that more output is available than is included in the current response. Use this value in the NextToken request parameter in a subsequent call to the operation to get the next part of the output. You should repeat this until the NextToken response element comes back as null. The pagination tokens expire after 24 hours.

" + } + } + }, "ListResourcesInput":{ "type":"structure", "members":{ @@ -1074,6 +1181,53 @@ "type":"long", "box":true }, + "ManagedView":{ + "type":"structure", + "members":{ + "Filters":{"shape":"SearchFilter"}, + "IncludedProperties":{ + "shape":"IncludedPropertyList", + "documentation":"

A structure that contains additional information about the managed view.

" + }, + "LastUpdatedAt":{ + "shape":"SyntheticTimestamp_date_time", + "documentation":"

The date and time when this managed view was last modified.

" + }, + "ManagedViewArn":{ + "shape":"String", + "documentation":"

The Amazon resource name (ARN) of the managed view.

" + }, + "ManagedViewName":{ + "shape":"String", + "documentation":"

The name of the managed view.

" + }, + "Owner":{ + "shape":"String", + "documentation":"

The Amazon Web Services account that owns this managed view.

" + }, + "ResourcePolicy":{ + "shape":"String", + "documentation":"

The resource policy that defines access to the managed view. To learn more about this policy, review Managed views.

" + }, + "Scope":{ + "shape":"String", + "documentation":"

An Amazon resource name (ARN) of an Amazon Web Services account or organization that specifies whether this managed view includes resources from only the specified Amazon Web Services account or all accounts in the specified organization.

" + }, + "TrustedService":{ + "shape":"String", + "documentation":"

The service principal of the Amazon Web Services service that created and manages the managed view.

" + }, + "Version":{ + "shape":"String", + "documentation":"

The version of the managed view.

" + } + }, + "documentation":"

An Amazon Web Services-managed view is how other Amazon Web Services services can access resource information indexed by Resource Explorer for your Amazon Web Services account or organization with your consent. For more information, see Managed views.

" + }, + "ManagedViewArnList":{ + "type":"list", + "member":{"shape":"String"} + }, "MemberIndex":{ "type":"structure", "members":{ @@ -1154,7 +1308,7 @@ }, "Service":{ "shape":"String", - "documentation":"

The Amazon Web Servicesservice that owns the resource and is responsible for creating and updating it.

" + "documentation":"

The Amazon Web Services service that owns the resource and is responsible for creating and updating it.

" } }, "documentation":"

A resource in Amazon Web Services that Amazon Web Services Resource Explorer has discovered, and for which it has stored information in the index of the Amazon Web Services Region that contains the resource.

" @@ -1341,7 +1495,7 @@ }, "Service":{ "shape":"String", - "documentation":"

The Amazon Web Servicesservice that is associated with the resource type. This is the primary service that lets you create and interact with resources of this type.

" + "documentation":"

The Amazon Web Services service that is associated with the resource type. This is the primary service that lets you create and interact with resources of this type.

" } }, "documentation":"

A structure that describes a resource type supported by Amazon Web Services Resource Explorer.

" diff --git a/botocore/data/synthetics/2017-10-11/service-2.json b/botocore/data/synthetics/2017-10-11/service-2.json index 84941cade4..e241625299 100644 --- a/botocore/data/synthetics/2017-10-11/service-2.json +++ b/botocore/data/synthetics/2017-10-11/service-2.json @@ -77,7 +77,7 @@ {"shape":"ResourceNotFoundException"}, {"shape":"ConflictException"} ], - "documentation":"

Permanently deletes the specified canary.

If you specify DeleteLambda to true, CloudWatch Synthetics also deletes the Lambda functions and layers that are used by the canary.

Other resources used and created by the canary are not automatically deleted. After you delete a canary that you do not intend to use again, you should also delete the following:

Before you delete a canary, you might want to use GetCanary to display the information about this canary. Make note of the information returned by this operation so that you can delete these resources after you delete the canary.

" + "documentation":"

Permanently deletes the specified canary.

If the canary's ProvisionedResourceCleanup field is set to AUTOMATIC or you specify DeleteLambda in this operation as true, CloudWatch Synthetics also deletes the Lambda functions and layers that are used by the canary.

Other resources used and created by the canary are not automatically deleted. After you delete a canary, you should also delete the following:

Before you delete a canary, you might want to use GetCanary to display the information about this canary. Make note of the information returned by this operation so that you can delete these resources after you delete the canary.

" }, "DeleteGroup":{ "name":"DeleteGroup", @@ -494,6 +494,10 @@ "shape":"VisualReferenceOutput", "documentation":"

If this canary performs visual monitoring by comparing screenshots, this structure contains the ID of the canary run to use as the baseline for screenshots, and the coordinates of any parts of the screen to ignore during the visual monitoring comparison.

" }, + "ProvisionedResourceCleanup":{ + "shape":"ProvisionedResourceCleanupSetting", + "documentation":"

Specifies whether to also delete the Lambda functions and layers used by this canary when the canary is deleted. If it is AUTOMATIC, the Lambda functions and layers will be deleted when the canary is deleted.

If the value of this parameter is OFF, then the value of the DeleteLambda parameter of the DeleteCanary operation determines whether the Lambda functions and layers will be deleted.

" + }, "Tags":{ "shape":"TagMap", "documentation":"

The list of key-value pairs that are associated with the canary.

" @@ -859,6 +863,10 @@ "shape":"ResourceList", "documentation":"

To have the tags that you apply to this canary also be applied to the Lambda function that the canary uses, specify this parameter with the value lambda-function.

If you specify this parameter and don't specify any tags in the Tags parameter, the canary creation fails.

" }, + "ProvisionedResourceCleanup":{ + "shape":"ProvisionedResourceCleanupSetting", + "documentation":"

Specifies whether to also delete the Lambda functions and layers used by this canary when the canary is deleted. If you omit this parameter, the default of AUTOMATIC is used, which means that the Lambda functions and layers will be deleted when the canary is deleted.

If the value of this parameter is OFF, then the value of the DeleteLambda parameter of the DeleteCanary operation determines whether the Lambda functions and layers will be deleted.

" + }, "Tags":{ "shape":"TagMap", "documentation":"

A list of key-value pairs to associate with the canary. You can associate as many as 50 tags with a canary.

Tags can help you organize and categorize your resources. You can also use them to scope user permissions, by granting a user permission to access or change only the resources that have certain tag values.

To have the tags that you apply to this canary also be applied to the Lambda function that the canary uses, specify this parameter with the value lambda-function.

" @@ -913,7 +921,7 @@ }, "DeleteLambda":{ "shape":"boolean", - "documentation":"

Specifies whether to also delete the Lambda functions and layers used by this canary. The default is false.

Type: Boolean

", + "documentation":"

Specifies whether to also delete the Lambda functions and layers used by this canary. The default is false.

Your setting for this parameter is used only if the canary doesn't have AUTOMATIC for its ProvisionedResourceCleanup field. If that field is set to AUTOMATIC, then the Lambda functions and layers will be deleted when this canary is deleted.

Type: Boolean

", "location":"querystring", "locationName":"deleteLambda" } @@ -1418,6 +1426,13 @@ "min":1, "pattern":"^.+$" }, + "ProvisionedResourceCleanupSetting":{ + "type":"string", + "enum":[ + "AUTOMATIC", + "OFF" + ] + }, "RequestEntityTooLargeException":{ "type":"structure", "members":{ @@ -1709,6 +1724,10 @@ "ArtifactConfig":{ "shape":"ArtifactConfigInput", "documentation":"

A structure that contains the configuration for canary artifacts, including the encryption-at-rest settings for artifacts that the canary uploads to Amazon S3.

" + }, + "ProvisionedResourceCleanup":{ + "shape":"ProvisionedResourceCleanupSetting", + "documentation":"

Specifies whether to also delete the Lambda functions and layers used by this canary when the canary is deleted.

If the value of this parameter is OFF, then the value of the DeleteLambda parameter of the DeleteCanary operation determines whether the Lambda functions and layers will be deleted.

" } } }, From bc6384de7d8e5a988412beb0fb3a6e6710857590 Mon Sep 17 00:00:00 2001 From: aws-sdk-python-automation Date: Thu, 7 Nov 2024 19:24:24 +0000 Subject: [PATCH 2/3] Update endpoints model --- botocore/data/endpoints.json | 14 ++++++++++++++ 1 file changed, 14 insertions(+) diff --git a/botocore/data/endpoints.json b/botocore/data/endpoints.json index 7aaaa1b1ce..4e25bc2a2b 100644 --- a/botocore/data/endpoints.json +++ b/botocore/data/endpoints.json @@ -2815,6 +2815,12 @@ }, "hostname" : "bedrock.eu-central-1.amazonaws.com" }, + "bedrock-eu-central-2" : { + "credentialScope" : { + "region" : "eu-central-2" + }, + "hostname" : "bedrock.eu-central-2.amazonaws.com" + }, "bedrock-eu-west-1" : { "credentialScope" : { "region" : "eu-west-1" @@ -2899,6 +2905,12 @@ }, "hostname" : "bedrock-runtime.eu-central-1.amazonaws.com" }, + "bedrock-runtime-eu-central-2" : { + "credentialScope" : { + "region" : "eu-central-2" + }, + "hostname" : "bedrock-runtime.eu-central-2.amazonaws.com" + }, "bedrock-runtime-eu-west-1" : { "credentialScope" : { "region" : "eu-west-1" @@ -2991,6 +3003,7 @@ }, "ca-central-1" : { }, "eu-central-1" : { }, + "eu-central-2" : { }, "eu-west-1" : { }, "eu-west-2" : { }, "eu-west-3" : { }, @@ -8939,6 +8952,7 @@ }, "ap-southeast-3" : { }, "ap-southeast-4" : { }, + "ap-southeast-5" : { }, "ca-central-1" : { "variants" : [ { "hostname" : "fms-fips.ca-central-1.amazonaws.com", From b05f89c13bb2fff464f5a5824a3a1fff4149d77b Mon Sep 17 00:00:00 2001 From: aws-sdk-python-automation Date: Thu, 7 Nov 2024 19:25:33 +0000 Subject: [PATCH 3/3] Bumping version to 1.35.56 --- .changes/1.35.56.json | 42 +++++++++++++++++++ .../api-change-autoscaling-52998.json | 5 --- .../api-change-bedrockagent-80823.json | 5 --- .../api-change-bedrockruntime-93186.json | 5 --- .../api-change-cleanrooms-18465.json | 5 --- .../api-change-cleanroomsml-37452.json | 5 --- .../api-change-quicksight-96534.json | 5 --- .../api-change-resourceexplorer2-90529.json | 5 --- .../api-change-synthetics-53205.json | 5 --- CHANGELOG.rst | 13 ++++++ botocore/__init__.py | 2 +- docs/source/conf.py | 2 +- 12 files changed, 57 insertions(+), 42 deletions(-) create mode 100644 .changes/1.35.56.json delete mode 100644 .changes/next-release/api-change-autoscaling-52998.json delete mode 100644 .changes/next-release/api-change-bedrockagent-80823.json delete mode 100644 .changes/next-release/api-change-bedrockruntime-93186.json delete mode 100644 .changes/next-release/api-change-cleanrooms-18465.json delete mode 100644 .changes/next-release/api-change-cleanroomsml-37452.json delete mode 100644 .changes/next-release/api-change-quicksight-96534.json delete mode 100644 .changes/next-release/api-change-resourceexplorer2-90529.json delete mode 100644 .changes/next-release/api-change-synthetics-53205.json diff --git a/.changes/1.35.56.json b/.changes/1.35.56.json new file mode 100644 index 0000000000..55b680dad2 --- /dev/null +++ b/.changes/1.35.56.json @@ -0,0 +1,42 @@ +[ + { + "category": "``autoscaling``", + "description": "Auto Scaling groups now support the ability to strictly balance instances across Availability Zones by configuring the AvailabilityZoneDistribution parameter. If balanced-only is configured for a group, launches will always be attempted in the under scaled Availability Zone even if it is unhealthy.", + "type": "api-change" + }, + { + "category": "``bedrock-agent``", + "description": "Add prompt support for chat template configuration and agent generative AI resource. Add support for configuring an optional guardrail in Prompt and Knowledge Base nodes in Prompt Flows. Add API to validate flow definition", + "type": "api-change" + }, + { + "category": "``bedrock-runtime``", + "description": "Add Prompt management support to Bedrock runtime APIs: Converse, ConverseStream, InvokeModel, InvokeModelWithStreamingResponse", + "type": "api-change" + }, + { + "category": "``cleanrooms``", + "description": "This release introduces support for Custom Models in AWS Clean Rooms ML.", + "type": "api-change" + }, + { + "category": "``cleanroomsml``", + "description": "This release introduces support for Custom Models in AWS Clean Rooms ML.", + "type": "api-change" + }, + { + "category": "``quicksight``", + "description": "Add Client Credentials based OAuth support for Snowflake and Starburst", + "type": "api-change" + }, + { + "category": "``resource-explorer-2``", + "description": "Add GetManagedView, ListManagedViews APIs.", + "type": "api-change" + }, + { + "category": "``synthetics``", + "description": "Add support to toggle if a canary will automatically delete provisioned canary resources such as Lambda functions and layers when a canary is deleted. This behavior can be controlled via the new ProvisionedResourceCleanup property exposed in the CreateCanary and UpdateCanary APIs.", + "type": "api-change" + } +] \ No newline at end of file diff --git a/.changes/next-release/api-change-autoscaling-52998.json b/.changes/next-release/api-change-autoscaling-52998.json deleted file mode 100644 index 1560b4a7f1..0000000000 --- a/.changes/next-release/api-change-autoscaling-52998.json +++ /dev/null @@ -1,5 +0,0 @@ -{ - "type": "api-change", - "category": "``autoscaling``", - "description": "Auto Scaling groups now support the ability to strictly balance instances across Availability Zones by configuring the AvailabilityZoneDistribution parameter. If balanced-only is configured for a group, launches will always be attempted in the under scaled Availability Zone even if it is unhealthy." -} diff --git a/.changes/next-release/api-change-bedrockagent-80823.json b/.changes/next-release/api-change-bedrockagent-80823.json deleted file mode 100644 index d0775ea205..0000000000 --- a/.changes/next-release/api-change-bedrockagent-80823.json +++ /dev/null @@ -1,5 +0,0 @@ -{ - "type": "api-change", - "category": "``bedrock-agent``", - "description": "Add prompt support for chat template configuration and agent generative AI resource. Add support for configuring an optional guardrail in Prompt and Knowledge Base nodes in Prompt Flows. Add API to validate flow definition" -} diff --git a/.changes/next-release/api-change-bedrockruntime-93186.json b/.changes/next-release/api-change-bedrockruntime-93186.json deleted file mode 100644 index 12bce9d7f6..0000000000 --- a/.changes/next-release/api-change-bedrockruntime-93186.json +++ /dev/null @@ -1,5 +0,0 @@ -{ - "type": "api-change", - "category": "``bedrock-runtime``", - "description": "Add Prompt management support to Bedrock runtime APIs: Converse, ConverseStream, InvokeModel, InvokeModelWithStreamingResponse" -} diff --git a/.changes/next-release/api-change-cleanrooms-18465.json b/.changes/next-release/api-change-cleanrooms-18465.json deleted file mode 100644 index 3fba7345b7..0000000000 --- a/.changes/next-release/api-change-cleanrooms-18465.json +++ /dev/null @@ -1,5 +0,0 @@ -{ - "type": "api-change", - "category": "``cleanrooms``", - "description": "This release introduces support for Custom Models in AWS Clean Rooms ML." -} diff --git a/.changes/next-release/api-change-cleanroomsml-37452.json b/.changes/next-release/api-change-cleanroomsml-37452.json deleted file mode 100644 index e9c4ecd5bd..0000000000 --- a/.changes/next-release/api-change-cleanroomsml-37452.json +++ /dev/null @@ -1,5 +0,0 @@ -{ - "type": "api-change", - "category": "``cleanroomsml``", - "description": "This release introduces support for Custom Models in AWS Clean Rooms ML." -} diff --git a/.changes/next-release/api-change-quicksight-96534.json b/.changes/next-release/api-change-quicksight-96534.json deleted file mode 100644 index 6d42d27e7b..0000000000 --- a/.changes/next-release/api-change-quicksight-96534.json +++ /dev/null @@ -1,5 +0,0 @@ -{ - "type": "api-change", - "category": "``quicksight``", - "description": "Add Client Credentials based OAuth support for Snowflake and Starburst" -} diff --git a/.changes/next-release/api-change-resourceexplorer2-90529.json b/.changes/next-release/api-change-resourceexplorer2-90529.json deleted file mode 100644 index 86681e10cb..0000000000 --- a/.changes/next-release/api-change-resourceexplorer2-90529.json +++ /dev/null @@ -1,5 +0,0 @@ -{ - "type": "api-change", - "category": "``resource-explorer-2``", - "description": "Add GetManagedView, ListManagedViews APIs." -} diff --git a/.changes/next-release/api-change-synthetics-53205.json b/.changes/next-release/api-change-synthetics-53205.json deleted file mode 100644 index b5e96027f7..0000000000 --- a/.changes/next-release/api-change-synthetics-53205.json +++ /dev/null @@ -1,5 +0,0 @@ -{ - "type": "api-change", - "category": "``synthetics``", - "description": "Add support to toggle if a canary will automatically delete provisioned canary resources such as Lambda functions and layers when a canary is deleted. This behavior can be controlled via the new ProvisionedResourceCleanup property exposed in the CreateCanary and UpdateCanary APIs." -} diff --git a/CHANGELOG.rst b/CHANGELOG.rst index 5180642646..bb482016ab 100644 --- a/CHANGELOG.rst +++ b/CHANGELOG.rst @@ -2,6 +2,19 @@ CHANGELOG ========= +1.35.56 +======= + +* api-change:``autoscaling``: Auto Scaling groups now support the ability to strictly balance instances across Availability Zones by configuring the AvailabilityZoneDistribution parameter. If balanced-only is configured for a group, launches will always be attempted in the under scaled Availability Zone even if it is unhealthy. +* api-change:``bedrock-agent``: Add prompt support for chat template configuration and agent generative AI resource. Add support for configuring an optional guardrail in Prompt and Knowledge Base nodes in Prompt Flows. Add API to validate flow definition +* api-change:``bedrock-runtime``: Add Prompt management support to Bedrock runtime APIs: Converse, ConverseStream, InvokeModel, InvokeModelWithStreamingResponse +* api-change:``cleanrooms``: This release introduces support for Custom Models in AWS Clean Rooms ML. +* api-change:``cleanroomsml``: This release introduces support for Custom Models in AWS Clean Rooms ML. +* api-change:``quicksight``: Add Client Credentials based OAuth support for Snowflake and Starburst +* api-change:``resource-explorer-2``: Add GetManagedView, ListManagedViews APIs. +* api-change:``synthetics``: Add support to toggle if a canary will automatically delete provisioned canary resources such as Lambda functions and layers when a canary is deleted. This behavior can be controlled via the new ProvisionedResourceCleanup property exposed in the CreateCanary and UpdateCanary APIs. + + 1.35.55 ======= diff --git a/botocore/__init__.py b/botocore/__init__.py index 4585bfecbb..4e9f6bed23 100644 --- a/botocore/__init__.py +++ b/botocore/__init__.py @@ -16,7 +16,7 @@ import os import re -__version__ = '1.35.55' +__version__ = '1.35.56' class NullHandler(logging.Handler): diff --git a/docs/source/conf.py b/docs/source/conf.py index bd2e28dcf3..bcfba42e9e 100644 --- a/docs/source/conf.py +++ b/docs/source/conf.py @@ -59,7 +59,7 @@ # The short X.Y version. version = '1.35.' # The full version, including alpha/beta/rc tags. -release = '1.35.55' +release = '1.35.56' # The language for content autogenerated by Sphinx. Refer to documentation # for a list of supported languages.