The total number of objects that are in the bucket, grouped by server-side encryption type. This includes a grouping that reports the total number of objects that aren't encrypted.
" + "documentation": "The total number of objects that are in the bucket, grouped by server-side encryption type. This includes a grouping that reports the total number of objects that aren't encrypted or use client-side encryption.
" }, "publicAccess": { "shape": "BucketPublicAccess", @@ -4450,7 +4450,7 @@ "filterBy": { "shape": "__listOfUsageStatisticsFilter", "locationName": "filterBy", - "documentation": "The criteria to use to filter the query results.
" + "documentation": "An array of objects, one for each condition to use to filter the query results. If the array contains more than one object, Amazon Macie uses an AND operator to join the conditions specified by the objects.
" }, "maxResults": { "shape": "__integer", @@ -5246,25 +5246,25 @@ "customerManaged": { "shape": "__long", "locationName": "customerManaged", - "documentation": "Reserved for future use.
" + "documentation": "The total number of objects that are encrypted using a customer-managed key. The objects use customer-provided server-side (SSE-C) encryption.
" }, "kmsManaged": { "shape": "__long", "locationName": "kmsManaged", - "documentation": "Reserved for future use.
" + "documentation": "The total number of objects that are encrypted using an AWS Key Management Service (AWS KMS) customer master key (CMK). The objects use AWS KMS AWS-managed (AWS-KMS) encryption or AWS KMS customer-managed (SSE-KMS) encryption.
" }, "s3Managed": { "shape": "__long", "locationName": "s3Managed", - "documentation": "Reserved for future use.
" + "documentation": "The total number of objects that are encrypted using an Amazon S3-managed key. The objects use Amazon S3-managed (SSE-S3) encryption.
" }, "unencrypted": { "shape": "__long", "locationName": "unencrypted", - "documentation": "Reserved for future use.
" + "documentation": "The total number of objects that aren't encrypted or use client-side encryption.
" } }, - "documentation": "The total number of objects that are in the bucket, grouped by server-side encryption type. This includes a grouping that reports the total number of objects that aren't encrypted.
" + "documentation": "Provides information about the number of objects that are in an S3 bucket and use certain types of server-side encryption, use client-side encryption, or aren't encrypted.
" }, "OrderBy": { "type": "string", @@ -6208,7 +6208,7 @@ "freeTrialStartDate": { "shape": "__timestampIso8601", "locationName": "freeTrialStartDate", - "documentation": "The date and time, in UTC and extended ISO 8601 format, when the free trial period started for the account. This value is null if the account didn't participate in the free trial.
" + "documentation": "The date and time, in UTC and extended ISO 8601 format, when the free trial started for the account.
" }, "usage": { "shape": "__listOfUsageByAccount", @@ -6221,24 +6221,45 @@ "UsageStatisticsFilter": { "type": "structure", "members": { + "comparator": { + "shape": "UsageStatisticsFilterComparator", + "locationName": "comparator", + "documentation": "The operator to use in the condition. If the value for the key property is accountId, this value must be CONTAINS. If the value for the key property is any other supported field, this value can be EQ, GT, GTE, LT, LTE, or NE.
" + }, "key": { "shape": "UsageStatisticsFilterKey", "locationName": "key", - "documentation": "The field to use to filter the results. The only supported value is accountId.
" + "documentation": "The field to use in the condition.
" }, "values": { "shape": "__listOf__string", "locationName": "values", - "documentation": "An array that lists the AWS account ID for each account to include in the results.
" + "documentation": "An array that lists values to use in the condition, based on the value for the field specified by the key property. If the value for the key property is accountId, this array can specify multiple values. Otherwise, this array can specify only one value.
Valid values for each supported field are:
accountId - The unique identifier for an AWS account.
freeTrialStartDate - The date and time, in UTC and extended ISO 8601 format, when the free trial started for an account.
serviceLimit - A Boolean (true or false) value that indicates whether an account has reached its monthly quota.
total - A string that represents the current, estimated month-to-date cost for an account.
Specifies criteria for filtering the results of a query for account quotas and usage data.
" + "documentation": "Specifies a condition for filtering the results of a query for account quotas and usage data.
" + }, + "UsageStatisticsFilterComparator": { + "type": "string", + "documentation": "The operator to use in a condition that filters the results of a query for account quotas and usage data. Valid values are:
", + "enum": [ + "GT", + "GTE", + "LT", + "LTE", + "EQ", + "NE", + "CONTAINS" + ] }, "UsageStatisticsFilterKey": { "type": "string", - "documentation": "The field to use to filter the results of a query for account quotas and usage data:
", + "documentation": "The field to use in a condition that filters the results of a query for account quotas and usage data. Valid values are:
", "enum": [ - "accountId" + "accountId", + "serviceLimit", + "freeTrialStartDate", + "total" ] }, "UsageStatisticsSortBy": { @@ -6262,7 +6283,9 @@ "documentation": "The field to use to sort the results of a query for account quotas and usage data. Valid values are:
", "enum": [ "accountId", - "total" + "total", + "serviceLimitValue", + "freeTrialStartDate" ] }, "UsageTotal": { From 8867c67d51eb29426f2f157ccab5d481fdf32c4d Mon Sep 17 00:00:00 2001 From: AWS <> Date: Fri, 24 Jul 2020 18:04:35 +0000 Subject: [PATCH 04/11] AWSKendraFrontendService Update: Amazon Kendra now supports sorting query results based on document attributes. Amazon Kendra also introduced an option to enclose table and column names with double quotes for database data sources. --- ...ture-AWSKendraFrontendService-a938d0c.json | 5 ++ .../codegen-resources/service-2.json | 60 ++++++++++++++++++- 2 files changed, 62 insertions(+), 3 deletions(-) create mode 100644 .changes/next-release/feature-AWSKendraFrontendService-a938d0c.json diff --git a/.changes/next-release/feature-AWSKendraFrontendService-a938d0c.json b/.changes/next-release/feature-AWSKendraFrontendService-a938d0c.json new file mode 100644 index 000000000000..367178402e83 --- /dev/null +++ b/.changes/next-release/feature-AWSKendraFrontendService-a938d0c.json @@ -0,0 +1,5 @@ +{ + "type": "feature", + "category": "AWSKendraFrontendService", + "description": "Amazon Kendra now supports sorting query results based on document attributes. Amazon Kendra also introduced an option to enclose table and column names with double quotes for database data sources." +} diff --git a/services/kendra/src/main/resources/codegen-resources/service-2.json b/services/kendra/src/main/resources/codegen-resources/service-2.json index 893bba613058..e98a47031a5f 100644 --- a/services/kendra/src/main/resources/codegen-resources/service-2.json +++ b/services/kendra/src/main/resources/codegen-resources/service-2.json @@ -1006,7 +1006,7 @@ }, "DataSourceInclusionsExclusionsStringsMember":{ "type":"string", - "max":50, + "max":150, "min":1 }, "DataSourceName":{ @@ -1244,6 +1244,10 @@ "AclConfiguration":{ "shape":"AclConfiguration", "documentation":"Information about the database column that provides information for user context filtering.
" + }, + "SqlConfiguration":{ + "shape":"SqlConfiguration", + "documentation":"Provides information about how Amazon Kendra uses quote marks around SQL identifiers when querying a database data source.
" } }, "documentation":"Provides the information necessary to connect a database to an index.
" @@ -1611,7 +1615,7 @@ }, "DateValue":{ "shape":"Timestamp", - "documentation":"A date value expressed as seconds from the Unix epoch.
" + "documentation":"A date expressed as an ISO 8601 string.
" } }, "documentation":"The value of a custom document attribute. You can only provide one value for a custom attribute.
" @@ -2274,6 +2278,13 @@ "max":36, "min":1 }, + "QueryIdentifiersEnclosingOption":{ + "type":"string", + "enum":[ + "DOUBLE_QUOTES", + "NONE" + ] + }, "QueryRequest":{ "type":"structure", "required":[ @@ -2312,6 +2323,10 @@ "PageSize":{ "shape":"Integer", "documentation":"Sets the number of results that are returned in each page of results. The default page size is 10. The maximum number of results returned is 100. If you ask for more than 100 results, only 100 are returned.
" + }, + "SortingConfiguration":{ + "shape":"SortingConfiguration", + "documentation":"Provides information that determines how the results of the query are sorted. You can set the field that Amazon Kendra should sort the results on, and specify whether the results should be sorted in ascending or descending order. In the case of ties in sorting the results, the results are sorted by relevance.
If you don't provide sorting configuration, the results are sorted by the relevance that Amazon Kendra determines for the result.
" } } }, @@ -2805,6 +2820,10 @@ "Displayable":{ "shape":"Boolean", "documentation":"Determines whether the field is returned in the query response. The default is true.
Determines whether the field can be used to sort the results of a query. If you specify sorting on a field that does not have Sortable set to true, Amazon Kendra returns an exception. The default is false.
Provides information about how a custom index field is used during a search.
" @@ -2979,7 +2998,7 @@ }, "ExclusionPatterns":{ "shape":"DataSourceInclusionsExclusionsStrings", - "documentation":"A list of regulary expression patterns. Documents that match the patterns are excluded from the index. Documents that don't match the patterns are included in the index. If a document matches both an exclusion pattern and an inclusion pattern, the document is not included in the index.
The regex is applied to the display URL of the SharePoint document.
" + "documentation":"A list of regular expression patterns. Documents that match the patterns are excluded from the index. Documents that don't match the patterns are included in the index. If a document matches both an exclusion pattern and an inclusion pattern, the document is not included in the index.
The regex is applied to the display URL of the SharePoint document.
" }, "VpcConfiguration":{"shape":"DataSourceVpcConfiguration"}, "FieldMappings":{ @@ -3003,6 +3022,41 @@ "type":"string", "enum":["SHAREPOINT_ONLINE"] }, + "SortOrder":{ + "type":"string", + "enum":[ + "DESC", + "ASC" + ] + }, + "SortingConfiguration":{ + "type":"structure", + "required":[ + "DocumentAttributeKey", + "SortOrder" + ], + "members":{ + "DocumentAttributeKey":{ + "shape":"DocumentAttributeKey", + "documentation":"The name of the document attribute used to sort the response. You can use any field that has the Sortable flag set to true.
You can also sort by any of the following built-in attributes:
_category
_created_at
_last_updated_at
_version
_view_count
The order that the results should be returned in. In case of ties, the relevance assigned to the result by Amazon Kendra is used as the tie-breaker.
" + } + }, + "documentation":"Specifies the document attribute to use to sort the response to a Amazon Kendra query. You can specify a single attribute for sorting. The attribute must have the Sortable flag set to true, otherwise Amazon Kendra returns an exception.
Determines whether Amazon Kendra encloses SQL identifiers in double quotes (\") when making a database query.
By default, Amazon Kendra passes SQL identifiers the way that they are entered into the data source configuration. It does not change the case of identifiers or enclose them in quotes.
PostgreSQL internally converts uppercase characters to lower case characters in identifiers unless they are quoted. Choosing this option encloses identifiers in quotes so that PostgreSQL does not convert the character's case.
For MySQL databases, you must enable the ansi_quotes option when you choose this option.
Provides information that configures Amazon Kendra to use a SQL database.
" + }, "StartDataSourceSyncJobRequest":{ "type":"structure", "required":[ From f4efd52434f2db83bbd814d1a723cf57bbc2d542 Mon Sep 17 00:00:00 2001 From: AWS <> Date: Fri, 24 Jul 2020 18:04:36 +0000 Subject: [PATCH 05/11] Amazon CloudWatch Update: AWS CloudWatch ListMetrics now supports an optional parameter (RecentlyActive) to filter results by only metrics that have received new datapoints in the past 3 hours. This enables more targeted metric data retrieval through the Get APIs --- .../feature-AmazonCloudWatch-2a2deee.json | 5 ++ .../codegen-resources/service-2.json | 70 +++++++++++-------- 2 files changed, 44 insertions(+), 31 deletions(-) create mode 100644 .changes/next-release/feature-AmazonCloudWatch-2a2deee.json diff --git a/.changes/next-release/feature-AmazonCloudWatch-2a2deee.json b/.changes/next-release/feature-AmazonCloudWatch-2a2deee.json new file mode 100644 index 000000000000..13b1b25112f4 --- /dev/null +++ b/.changes/next-release/feature-AmazonCloudWatch-2a2deee.json @@ -0,0 +1,5 @@ +{ + "type": "feature", + "category": "Amazon CloudWatch", + "description": "AWS CloudWatch ListMetrics now supports an optional parameter (RecentlyActive) to filter results by only metrics that have received new datapoints in the past 3 hours. This enables more targeted metric data retrieval through the Get APIs" +} diff --git a/services/cloudwatch/src/main/resources/codegen-resources/service-2.json b/services/cloudwatch/src/main/resources/codegen-resources/service-2.json index db4eb5670cea..70cfd28330c1 100644 --- a/services/cloudwatch/src/main/resources/codegen-resources/service-2.json +++ b/services/cloudwatch/src/main/resources/codegen-resources/service-2.json @@ -59,7 +59,7 @@ {"shape":"DashboardNotFoundError"}, {"shape":"InternalServiceFault"} ], - "documentation":"Deletes all dashboards that you specify. You may specify up to 100 dashboards to delete. If there is an error during this call, no dashboards are deleted.
" + "documentation":"Deletes all dashboards that you specify. You can specify up to 100 dashboards to delete. If there is an error during this call, no dashboards are deleted.
" }, "DeleteInsightRules":{ "name":"DeleteInsightRules", @@ -76,7 +76,7 @@ {"shape":"InvalidParameterValueException"}, {"shape":"MissingRequiredParameterException"} ], - "documentation":"Permanently deletes the specified Contributor Insights rules.
If you create a rule, delete it, and then re-create it with the same name, historical data from the first time the rule was created may or may not be available.
" + "documentation":"Permanently deletes the specified Contributor Insights rules.
If you create a rule, delete it, and then re-create it with the same name, historical data from the first time the rule was created might not be available.
" }, "DescribeAlarmHistory":{ "name":"DescribeAlarmHistory", @@ -244,7 +244,7 @@ {"shape":"MissingRequiredParameterException"}, {"shape":"ResourceNotFoundException"} ], - "documentation":"This operation returns the time series data collected by a Contributor Insights rule. The data includes the identity and number of contributors to the log group.
You can also optionally return one or more statistics about each data point in the time series. These statistics can include the following:
UniqueContributors -- the number of unique contributors for each data point.
MaxContributorValue -- the value of the top contributor for each data point. The identity of the contributor may change for each data point in the graph.
If this rule aggregates by COUNT, the top contributor for each data point is the contributor with the most occurrences in that period. If the rule aggregates by SUM, the top contributor is the contributor with the highest sum in the log field specified by the rule's Value, during that period.
SampleCount -- the number of data points matched by the rule.
Sum -- the sum of the values from all contributors during the time period represented by that data point.
Minimum -- the minimum value from a single observation during the time period represented by that data point.
Maximum -- the maximum value from a single observation during the time period represented by that data point.
Average -- the average value from all contributors during the time period represented by that data point.
This operation returns the time series data collected by a Contributor Insights rule. The data includes the identity and number of contributors to the log group.
You can also optionally return one or more statistics about each data point in the time series. These statistics can include the following:
UniqueContributors -- the number of unique contributors for each data point.
MaxContributorValue -- the value of the top contributor for each data point. The identity of the contributor might change for each data point in the graph.
If this rule aggregates by COUNT, the top contributor for each data point is the contributor with the most occurrences in that period. If the rule aggregates by SUM, the top contributor is the contributor with the highest sum in the log field specified by the rule's Value, during that period.
SampleCount -- the number of data points matched by the rule.
Sum -- the sum of the values from all contributors during the time period represented by that data point.
Minimum -- the minimum value from a single observation during the time period represented by that data point.
Maximum -- the maximum value from a single observation during the time period represented by that data point.
Average -- the average value from all contributors during the time period represented by that data point.
You can use the GetMetricData API to retrieve as many as 500 different metrics in a single request, with a total of as many as 100,800 data points. You can also optionally perform math expressions on the values of the returned statistics, to create new time series that represent new insights into your data. For example, using Lambda metrics, you could divide the Errors metric by the Invocations metric to get an error rate time series. For more information about metric math expressions, see Metric Math Syntax and Functions in the Amazon CloudWatch User Guide.
Calls to the GetMetricData API have a different pricing structure than calls to GetMetricStatistics. For more information about pricing, see Amazon CloudWatch Pricing.
Amazon CloudWatch retains metric data as follows:
Data points with a period of less than 60 seconds are available for 3 hours. These data points are high-resolution metrics and are available only for custom metrics that have been defined with a StorageResolution of 1.
Data points with a period of 60 seconds (1-minute) are available for 15 days.
Data points with a period of 300 seconds (5-minute) are available for 63 days.
Data points with a period of 3600 seconds (1 hour) are available for 455 days (15 months).
Data points that are initially published with a shorter period are aggregated together for long-term storage. For example, if you collect data using a period of 1 minute, the data remains available for 15 days with 1-minute resolution. After 15 days, this data is still available, but is aggregated and retrievable only with a resolution of 5 minutes. After 63 days, the data is further aggregated and is available with a resolution of 1 hour.
If you omit Unit in your request, all data that was collected with any unit is returned, along with the corresponding units that were specified when the data was reported to CloudWatch. If you specify a unit, the operation returns only data data that was collected with that unit specified. If you specify a unit that does not match the data collected, the results of the operation are null. CloudWatch does not perform unit conversions.
You can use the GetMetricData API to retrieve as many as 500 different metrics in a single request, with a total of as many as 100,800 data points. You can also optionally perform math expressions on the values of the returned statistics, to create new time series that represent new insights into your data. For example, using Lambda metrics, you could divide the Errors metric by the Invocations metric to get an error rate time series. For more information about metric math expressions, see Metric Math Syntax and Functions in the Amazon CloudWatch User Guide.
Calls to the GetMetricData API have a different pricing structure than calls to GetMetricStatistics. For more information about pricing, see Amazon CloudWatch Pricing.
Amazon CloudWatch retains metric data as follows:
Data points with a period of less than 60 seconds are available for 3 hours. These data points are high-resolution metrics and are available only for custom metrics that have been defined with a StorageResolution of 1.
Data points with a period of 60 seconds (1-minute) are available for 15 days.
Data points with a period of 300 seconds (5-minute) are available for 63 days.
Data points with a period of 3600 seconds (1 hour) are available for 455 days (15 months).
Data points that are initially published with a shorter period are aggregated together for long-term storage. For example, if you collect data using a period of 1 minute, the data remains available for 15 days with 1-minute resolution. After 15 days, this data is still available, but is aggregated and retrievable only with a resolution of 5 minutes. After 63 days, the data is further aggregated and is available with a resolution of 1 hour.
If you omit Unit in your request, all data that was collected with any unit is returned, along with the corresponding units that were specified when the data was reported to CloudWatch. If you specify a unit, the operation returns only data that was collected with that unit specified. If you specify a unit that does not match the data collected, the results of the operation are null. CloudWatch does not perform unit conversions.
List the specified metrics. You can use the returned metrics with GetMetricData or GetMetricStatistics to obtain statistical data.
Up to 500 results are returned for any one call. To retrieve additional results, use the returned token with subsequent calls.
After you create a metric, allow up to fifteen minutes before the metric appears. Statistics about the metric, however, are available sooner using GetMetricData or GetMetricStatistics.
" + "documentation":"List the specified metrics. You can use the returned metrics with GetMetricData or GetMetricStatistics to obtain statistical data.
Up to 500 results are returned for any one call. To retrieve additional results, use the returned token with subsequent calls.
After you create a metric, allow up to 15 minutes before the metric appears. You can see statistics about the metric sooner by using GetMetricData or GetMetricStatistics.
ListMetrics doesn't return information about metrics if those metrics haven't reported data in the past two weeks. To retrieve those metrics, use GetMetricData or GetMetricStatistics.
Creates a Contributor Insights rule. Rules evaluate log events in a CloudWatch Logs log group, enabling you to find contributor data for the log events in that log group. For more information, see Using Contributor Insights to Analyze High-Cardinality Data.
If you create a rule, delete it, and then re-create it with the same name, historical data from the first time the rule was created may or may not be available.
" + "documentation":"Creates a Contributor Insights rule. Rules evaluate log events in a CloudWatch Logs log group, enabling you to find contributor data for the log events in that log group. For more information, see Using Contributor Insights to Analyze High-Cardinality Data.
If you create a rule, delete it, and then re-create it with the same name, historical data from the first time the rule was created might not be available.
" }, "PutMetricAlarm":{ "name":"PutMetricAlarm", @@ -450,7 +450,7 @@ {"shape":"ResourceNotFound"}, {"shape":"InvalidFormatFault"} ], - "documentation":"Temporarily sets the state of an alarm for testing purposes. When the updated state differs from the previous value, the action configured for the appropriate state is invoked. For example, if your alarm is configured to send an Amazon SNS message when an alarm is triggered, temporarily changing the alarm state to ALARM sends an SNS message.
Metric alarms returns to their actual state quickly, often within seconds. Because the metric alarm state change happens quickly, it is typically only visible in the alarm's History tab in the Amazon CloudWatch console or through DescribeAlarmHistory.
If you use SetAlarmState on a composite alarm, the composite alarm is not guaranteed to return to its actual state. It will return to its actual state only once any of its children alarms change state. It is also re-evaluated if you update its configuration.
If an alarm triggers EC2 Auto Scaling policies or application Auto Scaling policies, you must include information in the StateReasonData parameter to enable the policy to take the correct action.
Temporarily sets the state of an alarm for testing purposes. When the updated state differs from the previous value, the action configured for the appropriate state is invoked. For example, if your alarm is configured to send an Amazon SNS message when an alarm is triggered, temporarily changing the alarm state to ALARM sends an SNS message.
Metric alarms returns to their actual state quickly, often within seconds. Because the metric alarm state change happens quickly, it is typically only visible in the alarm's History tab in the Amazon CloudWatch console or through DescribeAlarmHistory.
If you use SetAlarmState on a composite alarm, the composite alarm is not guaranteed to return to its actual state. It returns to its actual state only once any of its children alarms change state. It is also reevaluated if you update its configuration.
If an alarm triggers EC2 Auto Scaling policies or application Auto Scaling policies, you must include information in the StateReasonData parameter to enable the policy to take the correct action.
Assigns one or more tags (key-value pairs) to the specified CloudWatch resource. Currently, the only CloudWatch resources that can be tagged are alarms and Contributor Insights rules.
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 resources with certain tag values.
Tags don't have any semantic meaning to AWS and are interpreted strictly as strings of characters.
You can use the TagResource action with an alarm that already has tags. If you specify a new tag key for the alarm, this tag is appended to the list of tags associated with the alarm. If you specify a tag key that is already associated with the alarm, the new tag value that you specify replaces the previous value for that tag.
You can associate as many as 50 tags with a CloudWatch resource.
" + "documentation":"Assigns one or more tags (key-value pairs) to the specified CloudWatch resource. Currently, the only CloudWatch resources that can be tagged are alarms and Contributor Insights rules.
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 resources with certain tag values.
Tags don't have any semantic meaning to AWS and are interpreted strictly as strings of characters.
You can use the TagResource action with an alarm that already has tags. If you specify a new tag key for the alarm, this tag is appended to the list of tags associated with the alarm. If you specify a tag key that is already associated with the alarm, the new tag value that you specify replaces the previous value for that tag.
You can associate as many as 50 tags with a CloudWatch resource.
" }, "UntagResource":{ "name":"UntagResource", @@ -1092,11 +1092,11 @@ }, "ChildrenOfAlarmName":{ "shape":"AlarmName", - "documentation":"If you use this parameter and specify the name of a composite alarm, the operation returns information about the \"children\" alarms of the alarm you specify. These are the metric alarms and composite alarms referenced in the AlarmRule field of the composite alarm that you specify in ChildrenOfAlarmName. Information about the composite alarm that you name in ChildrenOfAlarmName is not returned.
If you specify ChildrenOfAlarmName, you cannot specify any other parameters in the request except for MaxRecords and NextToken. If you do so, you will receive a validation error.
Only the Alarm Name, ARN, StateValue (OK/ALARM/INSUFFICIENT_DATA), and StateUpdatedTimestamp information are returned by this operation when you use this parameter. To get complete information about these alarms, perform another DescribeAlarms operation and specify the parent alarm names in the AlarmNames parameter.
If you use this parameter and specify the name of a composite alarm, the operation returns information about the \"children\" alarms of the alarm you specify. These are the metric alarms and composite alarms referenced in the AlarmRule field of the composite alarm that you specify in ChildrenOfAlarmName. Information about the composite alarm that you name in ChildrenOfAlarmName is not returned.
If you specify ChildrenOfAlarmName, you cannot specify any other parameters in the request except for MaxRecords and NextToken. If you do so, you receive a validation error.
Only the Alarm Name, ARN, StateValue (OK/ALARM/INSUFFICIENT_DATA), and StateUpdatedTimestamp information are returned by this operation when you use this parameter. To get complete information about these alarms, perform another DescribeAlarms operation and specify the parent alarm names in the AlarmNames parameter.
If you use this parameter and specify the name of a metric or composite alarm, the operation returns information about the \"parent\" alarms of the alarm you specify. These are the composite alarms that have AlarmRule parameters that reference the alarm named in ParentsOfAlarmName. Information about the alarm that you specify in ParentsOfAlarmName is not returned.
If you specify ParentsOfAlarmName, you cannot specify any other parameters in the request except for MaxRecords and NextToken. If you do so, you will receive a validation error.
Only the Alarm Name and ARN are returned by this operation when you use this parameter. To get complete information about these alarms, perform another DescribeAlarms operation and specify the parent alarm names in the AlarmNames parameter.
If you use this parameter and specify the name of a metric or composite alarm, the operation returns information about the \"parent\" alarms of the alarm you specify. These are the composite alarms that have AlarmRule parameters that reference the alarm named in ParentsOfAlarmName. Information about the alarm that you specify in ParentsOfAlarmName is not returned.
If you specify ParentsOfAlarmName, you cannot specify any other parameters in the request except for MaxRecords and NextToken. If you do so, you receive a validation error.
Only the Alarm Name and ARN are returned by this operation when you use this parameter. To get complete information about these alarms, perform another DescribeAlarms operation and specify the parent alarm names in the AlarmNames parameter.
This parameter is not currently used. Reserved for future use. If it is used in the future, the maximum value may be different.
" + "documentation":"This parameter is not currently used. Reserved for future use. If it is used in the future, the maximum value might be different.
" } } }, @@ -1206,14 +1206,14 @@ "members":{ "Name":{ "shape":"DimensionName", - "documentation":"The name of the dimension.
" + "documentation":"The name of the dimension. Dimension names cannot contain blank spaces or non-ASCII characters.
" }, "Value":{ "shape":"DimensionValue", - "documentation":"The value representing the dimension measurement.
" + "documentation":"The value of the dimension.
" } }, - "documentation":"Expands the identity of a metric.
", + "documentation":"A dimension is a name/value pair that is part of the identity of a metric. You can assign up to 10 dimensions to a metric. Because dimensions are part of the unique identifier for a metric, whenever you add a unique name/value pair to one of your metrics, you are creating a new variation of that metric.
", "xmlOrder":[ "Name", "Value" @@ -1399,7 +1399,7 @@ }, "Metrics":{ "shape":"InsightRuleMetricList", - "documentation":"Specifies which metrics to use for aggregation of contributor values for the report. You can specify one or more of the following metrics:
UniqueContributors -- the number of unique contributors for each data point.
MaxContributorValue -- the value of the top contributor for each data point. The identity of the contributor may change for each data point in the graph.
If this rule aggregates by COUNT, the top contributor for each data point is the contributor with the most occurrences in that period. If the rule aggregates by SUM, the top contributor is the contributor with the highest sum in the log field specified by the rule's Value, during that period.
SampleCount -- the number of data points matched by the rule.
Sum -- the sum of the values from all contributors during the time period represented by that data point.
Minimum -- the minimum value from a single observation during the time period represented by that data point.
Maximum -- the maximum value from a single observation during the time period represented by that data point.
Average -- the average value from all contributors during the time period represented by that data point.
Specifies which metrics to use for aggregation of contributor values for the report. You can specify one or more of the following metrics:
UniqueContributors -- the number of unique contributors for each data point.
MaxContributorValue -- the value of the top contributor for each data point. The identity of the contributor might change for each data point in the graph.
If this rule aggregates by COUNT, the top contributor for each data point is the contributor with the most occurrences in that period. If the rule aggregates by SUM, the top contributor is the contributor with the highest sum in the log field specified by the rule's Value, during that period.
SampleCount -- the number of data points matched by the rule.
Sum -- the sum of the values from all contributors during the time period represented by that data point.
Minimum -- the minimum value from a single observation during the time period represented by that data point.
Maximum -- the maximum value from a single observation during the time period represented by that data point.
Average -- the average value from all contributors during the time period represented by that data point.
Contains a message about this GetMetricData operation, if the operation results in such a message. An example of a message that may be returned is Maximum number of allowed metrics exceeded. If there is a message, as much of the operation as possible is still executed.
A message appears here only if it is related to the global GetMetricData operation. Any message about a specific metric returned by the operation appears in the MetricDataResult object returned for that metric.
Contains a message about this GetMetricData operation, if the operation results in such a message. An example of a message that might be returned is Maximum number of allowed metrics exceeded. If there is a message, as much of the operation as possible is still executed.
A message appears here only if it is related to the global GetMetricData operation. Any message about a specific metric returned by the operation appears in the MetricDataResult object returned for that metric.
The unit for a given metric. If you omit Unit, all data that was collected with any unit is returned, along with the corresponding units that were specified when the data was reported to CloudWatch. If you specify a unit, the operation returns only data data that was collected with that unit specified. If you specify a unit that does not match the data collected, the results of the operation are null. CloudWatch does not perform unit conversions.
The unit for a given metric. If you omit Unit, all data that was collected with any unit is returned, along with the corresponding units that were specified when the data was reported to CloudWatch. If you specify a unit, the operation returns only data that was collected with that unit specified. If you specify a unit that does not match the data collected, the results of the operation are null. CloudWatch does not perform unit conversions.
The image of the graph, in the output format specified.
" + "documentation":"The image of the graph, in the output format specified. The output is base64-encoded.
" } } }, @@ -1927,6 +1927,10 @@ "NextToken":{ "shape":"NextToken", "documentation":"The token returned by a previous call to indicate that there is more data available.
" + }, + "RecentlyActive":{ + "shape":"RecentlyActive", + "documentation":"To filter the results to show only metrics that have had data points published in the past three hours, specify this parameter with a value of PT3H. This is the only valid value for this parameter.
The results that are returned are an approximation of the value you specify. There is a low probability that the returned results include metrics with last published data as much as 40 minutes more than the specified time interval.
" } } }, @@ -1935,11 +1939,11 @@ "members":{ "Metrics":{ "shape":"Metrics", - "documentation":"The metrics.
" + "documentation":"The metrics that match your request.
" }, "NextToken":{ "shape":"NextToken", - "documentation":"The token that marks the start of the next batch of returned results.
" + "documentation":"The token that marks the start of the next batch of returned results.
" } }, "xmlOrder":[ @@ -1953,7 +1957,7 @@ "members":{ "ResourceARN":{ "shape":"AmazonResourceName", - "documentation":"The ARN of the CloudWatch resource that you want to view tags for.
The ARN format of an alarm is arn:aws:cloudwatch:Region:account-id:alarm:alarm-name
The ARN format of a Contributor Insights rule is arn:aws:cloudwatch:Region:account-id:insight-rule:insight-rule-name
For more information on ARN format, see Resource Types Defined by Amazon CloudWatch in the Amazon Web Services General Reference.
" + "documentation":"The ARN of the CloudWatch resource that you want to view tags for.
The ARN format of an alarm is arn:aws:cloudwatch:Region:account-id:alarm:alarm-name
The ARN format of a Contributor Insights rule is arn:aws:cloudwatch:Region:account-id:insight-rule:insight-rule-name
For more information about ARN format, see Resource Types Defined by Amazon CloudWatch in the Amazon Web Services General Reference.
" } } }, @@ -2320,7 +2324,7 @@ }, "Unit":{ "shape":"StandardUnit", - "documentation":"When you are using a Put operation, this defines what unit you want to use when storing the metric.
In a Get operation, if you omit Unit then all data that was collected with any unit is returned, along with the corresponding units that were specified when the data was reported to CloudWatch. If you specify a unit, the operation returns only data data that was collected with that unit specified. If you specify a unit that does not match the data collected, the results of the operation are null. CloudWatch does not perform unit conversions.
When you are using a Put operation, this defines what unit you want to use when storing the metric.
In a Get operation, if you omit Unit then all data that was collected with any unit is returned, along with the corresponding units that were specified when the data was reported to CloudWatch. If you specify a unit, the operation returns only data that was collected with that unit specified. If you specify a unit that does not match the data collected, the results of the operation are null. CloudWatch does not perform unit conversions.
This structure defines the metric to be returned, along with the statistics, period, and units.
" @@ -2438,7 +2442,7 @@ }, "AlarmName":{ "shape":"AlarmName", - "documentation":"The name for the composite alarm. This name must be unique within your AWS account.
" + "documentation":"The name for the composite alarm. This name must be unique within the Region.
" }, "AlarmRule":{ "shape":"AlarmRule", @@ -2480,7 +2484,7 @@ "members":{ "DashboardValidationMessages":{ "shape":"DashboardValidationMessages", - "documentation":"If the input for PutDashboard was correct and the dashboard was successfully created or modified, this result is empty.
If this result includes only warning messages, then the input was valid enough for the dashboard to be created or modified, but some elements of the dashboard may not render.
If this result includes error messages, the input was not valid and the operation failed.
" + "documentation":"If the input for PutDashboard was correct and the dashboard was successfully created or modified, this result is empty.
If this result includes only warning messages, then the input was valid enough for the dashboard to be created or modified, but some elements of the dashboard might not render.
If this result includes error messages, the input was not valid and the operation failed.
" } } }, @@ -2524,7 +2528,7 @@ "members":{ "AlarmName":{ "shape":"AlarmName", - "documentation":"The name for the alarm. This name must be unique within your AWS account.
" + "documentation":"The name for the alarm. This name must be unique within the Region.
" }, "AlarmDescription":{ "shape":"AlarmDescription", @@ -2568,11 +2572,11 @@ }, "Period":{ "shape":"Period", - "documentation":"The length, in seconds, used each time the metric specified in MetricName is evaluated. Valid values are 10, 30, and any multiple of 60.
Period is required for alarms based on static thresholds. If you are creating an alarm based on a metric math expression, you specify the period for each metric within the objects in the Metrics array.
Be sure to specify 10 or 30 only for metrics that are stored by a PutMetricData call with a StorageResolution of 1. If you specify a period of 10 or 30 for a metric that does not have sub-minute resolution, the alarm still attempts to gather data at the period rate that you specify. In this case, it does not receive data for the attempts that do not correspond to a one-minute data resolution, and the alarm may often lapse into INSUFFICENT_DATA status. Specifying 10 or 30 also sets this alarm as a high-resolution alarm, which has a higher charge than other alarms. For more information about pricing, see Amazon CloudWatch Pricing.
An alarm's total current evaluation period can be no longer than one day, so Period multiplied by EvaluationPeriods cannot be more than 86,400 seconds.
The length, in seconds, used each time the metric specified in MetricName is evaluated. Valid values are 10, 30, and any multiple of 60.
Period is required for alarms based on static thresholds. If you are creating an alarm based on a metric math expression, you specify the period for each metric within the objects in the Metrics array.
Be sure to specify 10 or 30 only for metrics that are stored by a PutMetricData call with a StorageResolution of 1. If you specify a period of 10 or 30 for a metric that does not have sub-minute resolution, the alarm still attempts to gather data at the period rate that you specify. In this case, it does not receive data for the attempts that do not correspond to a one-minute data resolution, and the alarm might often lapse into INSUFFICENT_DATA status. Specifying 10 or 30 also sets this alarm as a high-resolution alarm, which has a higher charge than other alarms. For more information about pricing, see Amazon CloudWatch Pricing.
An alarm's total current evaluation period can be no longer than one day, so Period multiplied by EvaluationPeriods cannot be more than 86,400 seconds.
The unit of measure for the statistic. For example, the units for the Amazon EC2 NetworkIn metric are Bytes because NetworkIn tracks the number of bytes that an instance receives on all network interfaces. You can also specify a unit when you create a custom metric. Units help provide conceptual meaning to your data. Metric data points that specify a unit of measure, such as Percent, are aggregated separately.
If you don't specify Unit, CloudWatch retrieves all unit types that have been published for the metric and attempts to evaluate the alarm. Usually metrics are published with only one unit, so the alarm will work as intended.
However, if the metric is published with multiple types of units and you don't specify a unit, the alarm's behavior is not defined and will behave un-predictably.
We recommend omitting Unit so that you don't inadvertently specify an incorrect unit that is not published for this metric. Doing so causes the alarm to be stuck in the INSUFFICIENT DATA state.
The unit of measure for the statistic. For example, the units for the Amazon EC2 NetworkIn metric are Bytes because NetworkIn tracks the number of bytes that an instance receives on all network interfaces. You can also specify a unit when you create a custom metric. Units help provide conceptual meaning to your data. Metric data points that specify a unit of measure, such as Percent, are aggregated separately.
If you don't specify Unit, CloudWatch retrieves all unit types that have been published for the metric and attempts to evaluate the alarm. Usually, metrics are published with only one unit, so the alarm works as intended.
However, if the metric is published with multiple types of units and you don't specify a unit, the alarm's behavior is not defined and it behaves predictably.
We recommend omitting Unit so that you don't inadvertently specify an incorrect unit that is not published for this metric. Doing so causes the alarm to be stuck in the INSUFFICIENT DATA state.
A list of key-value pairs to associate with the alarm. You can associate as many as 50 tags with an alarm.
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 resources with certain tag values.
" + "documentation":"A list of key-value pairs to associate with the alarm. You can associate as many as 50 tags with an alarm.
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 resources with certain tag values.
" }, "ThresholdMetricId":{ "shape":"MetricId", @@ -2651,6 +2655,10 @@ "EndTime" ] }, + "RecentlyActive":{ + "type":"string", + "enum":["PT3H"] + }, "ResourceId":{"type":"string"}, "ResourceList":{ "type":"list", @@ -2711,7 +2719,7 @@ "members":{ "AlarmName":{ "shape":"AlarmName", - "documentation":"The name for the alarm. This name must be unique within the AWS account. The maximum length is 255 characters.
" + "documentation":"The name of the alarm.
" }, "StateValue":{ "shape":"StateValue", @@ -2875,7 +2883,7 @@ "members":{ "ResourceARN":{ "shape":"AmazonResourceName", - "documentation":"The ARN of the CloudWatch resource that you're adding tags to.
The ARN format of an alarm is arn:aws:cloudwatch:Region:account-id:alarm:alarm-name
The ARN format of a Contributor Insights rule is arn:aws:cloudwatch:Region:account-id:insight-rule:insight-rule-name
For more information on ARN format, see Resource Types Defined by Amazon CloudWatch in the Amazon Web Services General Reference.
" + "documentation":"The ARN of the CloudWatch resource that you're adding tags to.
The ARN format of an alarm is arn:aws:cloudwatch:Region:account-id:alarm:alarm-name
The ARN format of a Contributor Insights rule is arn:aws:cloudwatch:Region:account-id:insight-rule:insight-rule-name
For more information about ARN format, see Resource Types Defined by Amazon CloudWatch in the Amazon Web Services General Reference.
" }, "Tags":{ "shape":"TagList", @@ -2913,7 +2921,7 @@ "members":{ "ResourceARN":{ "shape":"AmazonResourceName", - "documentation":"The ARN of the CloudWatch resource that you're removing tags from.
The ARN format of an alarm is arn:aws:cloudwatch:Region:account-id:alarm:alarm-name
The ARN format of a Contributor Insights rule is arn:aws:cloudwatch:Region:account-id:insight-rule:insight-rule-name
For more information on ARN format, see Resource Types Defined by Amazon CloudWatch in the Amazon Web Services General Reference.
" + "documentation":"The ARN of the CloudWatch resource that you're removing tags from.
The ARN format of an alarm is arn:aws:cloudwatch:Region:account-id:alarm:alarm-name
The ARN format of a Contributor Insights rule is arn:aws:cloudwatch:Region:account-id:insight-rule:insight-rule-name
For more information about ARN format, see Resource Types Defined by Amazon CloudWatch in the Amazon Web Services General Reference.
" }, "TagKeys":{ "shape":"TagKeyList", From 10db1fe184d431ef5723521a2ef83a916db61a2b Mon Sep 17 00:00:00 2001 From: AWS <> Date: Fri, 24 Jul 2020 18:04:36 +0000 Subject: [PATCH 06/11] AWS MediaConnect Update: You can now disable an entitlement to stop streaming content to the subscriber's flow temporarily. When you are ready to allow content to start streaming to the subscriber's flow again, you can enable the entitlement. --- .../feature-AWSMediaConnect-74bbe29.json | 5 +++++ .../codegen-resources/service-2.json | 22 +++++++++++++++++++ 2 files changed, 27 insertions(+) create mode 100644 .changes/next-release/feature-AWSMediaConnect-74bbe29.json diff --git a/.changes/next-release/feature-AWSMediaConnect-74bbe29.json b/.changes/next-release/feature-AWSMediaConnect-74bbe29.json new file mode 100644 index 000000000000..790e494736f8 --- /dev/null +++ b/.changes/next-release/feature-AWSMediaConnect-74bbe29.json @@ -0,0 +1,5 @@ +{ + "type": "feature", + "category": "AWS MediaConnect", + "description": "You can now disable an entitlement to stop streaming content to the subscriber's flow temporarily. When you are ready to allow content to start streaming to the subscriber's flow again, you can enable the entitlement." +} diff --git a/services/mediaconnect/src/main/resources/codegen-resources/service-2.json b/services/mediaconnect/src/main/resources/codegen-resources/service-2.json index 910ab221f94d..a343090e5fe3 100644 --- a/services/mediaconnect/src/main/resources/codegen-resources/service-2.json +++ b/services/mediaconnect/src/main/resources/codegen-resources/service-2.json @@ -1313,6 +1313,11 @@ "locationName": "entitlementArn", "documentation": "The ARN of the entitlement." }, + "EntitlementStatus": { + "shape": "EntitlementStatus", + "locationName": "entitlementStatus", + "documentation": "An indication of whether the entitlement is enabled." + }, "Name": { "shape": "__string", "locationName": "name", @@ -1331,6 +1336,13 @@ "Name" ] }, + "EntitlementStatus": { + "type": "string", + "enum": [ + "ENABLED", + "DISABLED" + ] + }, "FailoverConfig": { "type": "structure", "members": { @@ -1454,6 +1466,11 @@ "locationName": "encryption", "documentation": "The type of encryption that will be used on the output that is associated with this entitlement." }, + "EntitlementStatus": { + "shape": "EntitlementStatus", + "locationName": "entitlementStatus", + "documentation": "An indication of whether the new entitlement should be enabled or disabled as soon as it is created. If you don\u2019t specify the entitlementStatus field in your request, MediaConnect sets it to ENABLED." + }, "Name": { "shape": "__string", "locationName": "name", @@ -2398,6 +2415,11 @@ "locationName": "entitlementArn", "documentation": "The ARN of the entitlement that you want to update." }, + "EntitlementStatus": { + "shape": "EntitlementStatus", + "locationName": "entitlementStatus", + "documentation": "An indication of whether you want to enable the entitlement to allow access, or disable it to stop streaming content to the subscriber\u2019s flow temporarily. If you don\u2019t specify the entitlementStatus field in your request, MediaConnect leaves the value unchanged." + }, "FlowArn": { "shape": "__string", "location": "uri", From 8ac9bb2042301d918383deef36a07fbab6192174 Mon Sep 17 00:00:00 2001 From: AWS <> Date: Fri, 24 Jul 2020 18:04:38 +0000 Subject: [PATCH 07/11] Amazon SageMaker Service Update: Sagemaker Ground Truth:Added support for OIDC (OpenID Connect) to authenticate workers via their own identity provider instead of through Amazon Cognito. This release adds new APIs (CreateWorkforce, DeleteWorkforce, and ListWorkforces) to SageMaker Ground Truth service. Sagemaker Neo: Added support for detailed target device description by using TargetPlatform fields - OS, architecture, and accelerator. Added support for additional compilation parameters by using JSON field CompilerOptions. Sagemaker Search: SageMaker Search supports transform job details in trial components. --- ...eature-AmazonSageMakerService-6151fd1.json | 5 + .../codegen-resources/paginators-1.json | 6 + .../codegen-resources/service-2.json | 536 ++++++++++++++++-- 3 files changed, 503 insertions(+), 44 deletions(-) create mode 100644 .changes/next-release/feature-AmazonSageMakerService-6151fd1.json diff --git a/.changes/next-release/feature-AmazonSageMakerService-6151fd1.json b/.changes/next-release/feature-AmazonSageMakerService-6151fd1.json new file mode 100644 index 000000000000..ed6daf6b629f --- /dev/null +++ b/.changes/next-release/feature-AmazonSageMakerService-6151fd1.json @@ -0,0 +1,5 @@ +{ + "type": "feature", + "category": "Amazon SageMaker Service", + "description": "Sagemaker Ground Truth:Added support for OIDC (OpenID Connect) to authenticate workers via their own identity provider instead of through Amazon Cognito. This release adds new APIs (CreateWorkforce, DeleteWorkforce, and ListWorkforces) to SageMaker Ground Truth service. Sagemaker Neo: Added support for detailed target device description by using TargetPlatform fields - OS, architecture, and accelerator. Added support for additional compilation parameters by using JSON field CompilerOptions. Sagemaker Search: SageMaker Search supports transform job details in trial components." +} diff --git a/services/sagemaker/src/main/resources/codegen-resources/paginators-1.json b/services/sagemaker/src/main/resources/codegen-resources/paginators-1.json index 0d5eb8803924..7f87ca77493b 100644 --- a/services/sagemaker/src/main/resources/codegen-resources/paginators-1.json +++ b/services/sagemaker/src/main/resources/codegen-resources/paginators-1.json @@ -180,6 +180,12 @@ "limit_key": "MaxResults", "result_key": "UserProfiles" }, + "ListWorkforces": { + "input_token": "NextToken", + "output_token": "NextToken", + "limit_key": "MaxResults", + "result_key": "Workforces" + }, "ListWorkteams": { "input_token": "NextToken", "output_token": "NextToken", diff --git a/services/sagemaker/src/main/resources/codegen-resources/service-2.json b/services/sagemaker/src/main/resources/codegen-resources/service-2.json index 7388ca20754a..21995bee7566 100644 --- a/services/sagemaker/src/main/resources/codegen-resources/service-2.json +++ b/services/sagemaker/src/main/resources/codegen-resources/service-2.json @@ -98,7 +98,7 @@ {"shape":"ResourceInUse"}, {"shape":"ResourceLimitExceeded"} ], - "documentation":"Starts a model compilation job. After the model has been compiled, Amazon SageMaker saves the resulting model artifacts to an Amazon Simple Storage Service (Amazon S3) bucket that you specify.
If you choose to host your model using Amazon SageMaker hosting services, you can use the resulting model artifacts as part of the model. You can also use the artifacts with AWS IoT Greengrass. In that case, deploy them as an ML resource.
In the request body, you provide the following:
A name for the compilation job
Information about the input model artifacts
The output location for the compiled model and the device (target) that the model runs on
The Amazon Resource Name (ARN) of the IAM role that Amazon SageMaker assumes to perform the model compilation job
You can also provide a Tag to track the model compilation job's resource use and costs. The response body contains the CompilationJobArn for the compiled job.
To stop a model compilation job, use StopCompilationJob. To get information about a particular model compilation job, use DescribeCompilationJob. To get information about multiple model compilation jobs, use ListCompilationJobs.
" + "documentation":"Starts a model compilation job. After the model has been compiled, Amazon SageMaker saves the resulting model artifacts to an Amazon Simple Storage Service (Amazon S3) bucket that you specify.
If you choose to host your model using Amazon SageMaker hosting services, you can use the resulting model artifacts as part of the model. You can also use the artifacts with AWS IoT Greengrass. In that case, deploy them as an ML resource.
In the request body, you provide the following:
A name for the compilation job
Information about the input model artifacts
The output location for the compiled model and the device (target) that the model runs on
The Amazon Resource Name (ARN) of the IAM role that Amazon SageMaker assumes to perform the model compilation job.
You can also provide a Tag to track the model compilation job's resource use and costs. The response body contains the CompilationJobArn for the compiled job.
To stop a model compilation job, use StopCompilationJob. To get information about a particular model compilation job, use DescribeCompilationJob. To get information about multiple model compilation jobs, use ListCompilationJobs.
" }, "CreateDomain":{ "name":"CreateDomain", @@ -151,7 +151,7 @@ "errors":[ {"shape":"ResourceLimitExceeded"} ], - "documentation":"Creates an Amazon SageMaker experiment. An experiment is a collection of trials that are observed, compared and evaluated as a group. A trial is a set of steps, called trial components, that produce a machine learning model.
The goal of an experiment is to determine the components that produce the best model. Multiple trials are performed, each one isolating and measuring the impact of a change to one or more inputs, while keeping the remaining inputs constant.
When you use Amazon SageMaker Studio or the Amazon SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the AWS SDK for Python (Boto), you must use the logging APIs provided by the SDK.
You can add tags to experiments, trials, trial components and then use the Search API to search for the tags.
To add a description to an experiment, specify the optional Description parameter. To add a description later, or to change the description, call the UpdateExperiment API.
To get a list of all your experiments, call the ListExperiments API. To view an experiment's properties, call the DescribeExperiment API. To get a list of all the trials associated with an experiment, call the ListTrials API. To create a trial call the CreateTrial API.
" + "documentation":"Creates an SageMaker experiment. An experiment is a collection of trials that are observed, compared and evaluated as a group. A trial is a set of steps, called trial components, that produce a machine learning model.
The goal of an experiment is to determine the components that produce the best model. Multiple trials are performed, each one isolating and measuring the impact of a change to one or more inputs, while keeping the remaining inputs constant.
When you use Amazon SageMaker Studio or the Amazon SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the AWS SDK for Python (Boto), you must use the logging APIs provided by the SDK.
You can add tags to experiments, trials, trial components and then use the Search API to search for the tags.
To add a description to an experiment, specify the optional Description parameter. To add a description later, or to change the description, call the UpdateExperiment API.
To get a list of all your experiments, call the ListExperiments API. To view an experiment's properties, call the DescribeExperiment API. To get a list of all the trials associated with an experiment, call the ListTrials API. To create a trial call the CreateTrial API.
" }, "CreateFlowDefinition":{ "name":"CreateFlowDefinition", @@ -381,6 +381,16 @@ ], "documentation":"Creates a user profile. A user profile represents a single user within a domain, and is the main way to reference a \"person\" for the purposes of sharing, reporting, and other user-oriented features. This entity is created when a user onboards to Amazon SageMaker Studio. If an administrator invites a person by email or imports them from SSO, a user profile is automatically created. A user profile is the primary holder of settings for an individual user and has a reference to the user's private Amazon Elastic File System (EFS) home directory.
" }, + "CreateWorkforce":{ + "name":"CreateWorkforce", + "http":{ + "method":"POST", + "requestUri":"/" + }, + "input":{"shape":"CreateWorkforceRequest"}, + "output":{"shape":"CreateWorkforceResponse"}, + "documentation":"Use this operation to create a workforce. This operation will return an error if a workforce already exists in the AWS Region that you specify. You can only create one workforce in each AWS Region.
If you want to create a new workforce in an AWS Region where the a workforce already exists, use the API operation to delete the existing workforce and then use this operation to create a new workforce.
To create a private workforce using Amazon Cognito, you must specify a Cognito user pool in CognitoConfig. You can also create an Amazon Cognito workforce using the Amazon SageMaker console. For more information, see Create a Private Workforce (Amazon Cognito).
To create a private workforce using your own OIDC Identity Provider (IdP), specify your IdP configuration in OidcConfig. You must create a OIDC IdP workforce using this API operation. For more information, see Create a Private Workforce (OIDC IdP).
Deletes the specified flow definition.
" @@ -494,7 +505,7 @@ "errors":[ {"shape":"ResourceNotFound"} ], - "documentation":"Use this operation to delete a worker task template (HumanTaskUi).
To see a list of human task user interfaces (work task templates) in your account, use . When you delete a worker task template, it no longer appears when you call ListHumanTaskUis.
Use this operation to delete a human task user interface (worker task template).
To see a list of human task user interfaces (work task templates) in your account, use . When you delete a worker task template, it no longer appears when you call ListHumanTaskUis.
Deletes a user profile. When a user profile is deleted, the user loses access to their EFS volume, including data, notebooks, and other artifacts.
" }, + "DeleteWorkforce":{ + "name":"DeleteWorkforce", + "http":{ + "method":"POST", + "requestUri":"/" + }, + "input":{"shape":"DeleteWorkforceRequest"}, + "output":{"shape":"DeleteWorkforceResponse"}, + "documentation":"Use this operation to delete a workforce.
If you want to create a new workforce in an AWS Region where the a workforce already exists, use this operation to delete the existing workforce and then use to create a new workforce.
" + }, "DeleteWorkteam":{ "name":"DeleteWorkteam", "http":{ @@ -1262,6 +1283,16 @@ "output":{"shape":"ListUserProfilesResponse"}, "documentation":"Lists user profiles.
" }, + "ListWorkforces":{ + "name":"ListWorkforces", + "http":{ + "method":"POST", + "requestUri":"/" + }, + "input":{"shape":"ListWorkforcesRequest"}, + "output":{"shape":"ListWorkforcesResponse"}, + "documentation":"Use this operation to list all private and vendor workforces in an AWS Region. Note that you can only have one private workforce per AWS Region.
" + }, "ListWorkteams":{ "name":"ListWorkteams", "http":{ @@ -1280,6 +1311,9 @@ }, "input":{"shape":"RenderUiTemplateRequest"}, "output":{"shape":"RenderUiTemplateResponse"}, + "errors":[ + {"shape":"ResourceNotFound"} + ], "documentation":"Renders the UI template so that you can preview the worker's experience.
" }, "Search":{ @@ -1817,7 +1851,7 @@ "members":{ "AnnotationConsolidationLambdaArn":{ "shape":"LambdaFunctionArn", - "documentation":"The Amazon Resource Name (ARN) of a Lambda function implements the logic for annotation consolidation and to process output data.
This parameter is required for all labeling jobs. For built-in task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for AnnotationConsolidationLambdaArn. For custom labeling workflows, see Post-annotation Lambda.
Bounding box - Finds the most similar boxes from different workers based on the Jaccard index of the boxes.
arn:aws:lambda:us-east-1:432418664414:function:ACS-BoundingBox
arn:aws:lambda:us-east-2:266458841044:function:ACS-BoundingBox
arn:aws:lambda:us-west-2:081040173940:function:ACS-BoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:ACS-BoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-BoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-BoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:ACS-BoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:ACS-BoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-BoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:ACS-BoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-BoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:ACS-BoundingBox
Image classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClass
arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClass
arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClass
Multi-label image classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClassMultiLabel
Semantic segmentation - Treats each pixel in an image as a multi-class classification and treats pixel annotations from workers as \"votes\" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:ACS-SemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-SemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-SemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-SemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-SemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-SemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-SemanticSegmentation
Text classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClass
arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClass
arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClass
Multi-label text classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClassMultiLabel
Named entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label.
arn:aws:lambda:us-east-1:432418664414:function:ACS-NamedEntityRecognition
arn:aws:lambda:us-east-2:266458841044:function:ACS-NamedEntityRecognition
arn:aws:lambda:us-west-2:081040173940:function:ACS-NamedEntityRecognition
arn:aws:lambda:eu-west-1:568282634449:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-south-1:565803892007:function:ACS-NamedEntityRecognition
arn:aws:lambda:eu-central-1:203001061592:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-NamedEntityRecognition
arn:aws:lambda:eu-west-2:487402164563:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-NamedEntityRecognition
arn:aws:lambda:ca-central-1:918755190332:function:ACS-NamedEntityRecognition
3D point cloud object detection - Use this task type when you want workers to classify objects in a 3D point cloud by drawing 3D cuboids around objects. For example, you can use this task type to ask workers to identify different types of objects in a point cloud, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectDetection
3D point cloud object tracking - Use this task type when you want workers to draw 3D cuboids around objects that appear in a sequence of 3D point cloud frames. For example, you can use this task type to ask workers to track the movement of vehicles across multiple point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectTracking
3D point cloud semantic segmentation - Use this task type when you want workers to create a point-level semantic segmentation masks by painting objects in a 3D point cloud using different colors where each color is assigned to one of the classes you specify.
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudSemanticSegmentation
Use the following ARNs for Label Verification and Adjustment Jobs
Use label verification and adjustment jobs to review and adjust labels. To learn more, see Verify and Adjust Labels .
Semantic segmentation adjustment - Treats each pixel in an image as a multi-class classification and treats pixel adjusted annotations from workers as \"votes\" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentSemanticSegmentation
Semantic segmentation verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgment for semantic segmentation labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationSemanticSegmentation
Bounding box verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgement for bounding box labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationBoundingBox
arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationBoundingBox
arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationBoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationBoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationBoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationBoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationBoundingBox
Bounding box adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations.
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentBoundingBox
3D point cloud object detection adjustment - Use this task type when you want workers to adjust 3D cuboids around objects in a 3D point cloud.
arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectDetection
3D point cloud object tracking adjustment - Use this task type when you want workers to adjust 3D cuboids around objects that appear in a sequence of 3D point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectTracking
3D point cloud semantic segmentation adjustment - Use this task type when you want workers to adjust a point-level semantic segmentation masks using a paint tool.
arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudSemanticSegmentation
The Amazon Resource Name (ARN) of a Lambda function implements the logic for annotation consolidation and to process output data.
This parameter is required for all labeling jobs. For built-in task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for AnnotationConsolidationLambdaArn. For custom labeling workflows, see Post-annotation Lambda.
Bounding box - Finds the most similar boxes from different workers based on the Jaccard index of the boxes.
arn:aws:lambda:us-east-1:432418664414:function:ACS-BoundingBox
arn:aws:lambda:us-east-2:266458841044:function:ACS-BoundingBox
arn:aws:lambda:us-west-2:081040173940:function:ACS-BoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:ACS-BoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-BoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-BoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:ACS-BoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:ACS-BoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-BoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:ACS-BoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-BoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:ACS-BoundingBox
Image classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClass
arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClass
arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClass
Multi-label image classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClassMultiLabel
Semantic segmentation - Treats each pixel in an image as a multi-class classification and treats pixel annotations from workers as \"votes\" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:ACS-SemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-SemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-SemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-SemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-SemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-SemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-SemanticSegmentation
Text classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClass
arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClass
arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClass
Multi-label text classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClassMultiLabel
Named entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label.
arn:aws:lambda:us-east-1:432418664414:function:ACS-NamedEntityRecognition
arn:aws:lambda:us-east-2:266458841044:function:ACS-NamedEntityRecognition
arn:aws:lambda:us-west-2:081040173940:function:ACS-NamedEntityRecognition
arn:aws:lambda:eu-west-1:568282634449:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-south-1:565803892007:function:ACS-NamedEntityRecognition
arn:aws:lambda:eu-central-1:203001061592:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-NamedEntityRecognition
arn:aws:lambda:eu-west-2:487402164563:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-NamedEntityRecognition
arn:aws:lambda:ca-central-1:918755190332:function:ACS-NamedEntityRecognition
Named entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label.
arn:aws:lambda:us-east-1:432418664414:function:ACS-NamedEntityRecognition
arn:aws:lambda:us-east-2:266458841044:function:ACS-NamedEntityRecognition
arn:aws:lambda:us-west-2:081040173940:function:ACS-NamedEntityRecognition
arn:aws:lambda:eu-west-1:568282634449:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-south-1:565803892007:function:ACS-NamedEntityRecognition
arn:aws:lambda:eu-central-1:203001061592:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-NamedEntityRecognition
arn:aws:lambda:eu-west-2:487402164563:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-NamedEntityRecognition
arn:aws:lambda:ca-central-1:918755190332:function:ACS-NamedEntityRecognition
Video Classification - Use this task type when you need workers to classify videos using predefined labels that you specify. Workers are shown videos and are asked to choose one label for each video.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoMultiClass
arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoMultiClass
arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoMultiClass
Video Frame Object Detection - Use this task type to have workers identify and locate objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to identify and localize various objects in a series of video frames, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectDetection
Video Frame Object Tracking - Use this task type to have workers track the movement of objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to track the movement of objects, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectTracking
3D point cloud object detection - Use this task type when you want workers to classify objects in a 3D point cloud by drawing 3D cuboids around objects. For example, you can use this task type to ask workers to identify different types of objects in a point cloud, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectDetection
3D point cloud object tracking - Use this task type when you want workers to draw 3D cuboids around objects that appear in a sequence of 3D point cloud frames. For example, you can use this task type to ask workers to track the movement of vehicles across multiple point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectTracking
3D point cloud semantic segmentation - Use this task type when you want workers to create a point-level semantic segmentation masks by painting objects in a 3D point cloud using different colors where each color is assigned to one of the classes you specify.
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudSemanticSegmentation
Use the following ARNs for Label Verification and Adjustment Jobs
Use label verification and adjustment jobs to review and adjust labels. To learn more, see Verify and Adjust Labels .
Semantic segmentation adjustment - Treats each pixel in an image as a multi-class classification and treats pixel adjusted annotations from workers as \"votes\" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentSemanticSegmentation
Semantic segmentation verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgment for semantic segmentation labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationSemanticSegmentation
Bounding box verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgement for bounding box labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationBoundingBox
arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationBoundingBox
arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationBoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationBoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationBoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationBoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationBoundingBox
Bounding box adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations.
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentBoundingBox
Video Frame Object Detection Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to classify and localize objects in a sequence of video frames.
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectDetection
Video Frame Object Tracking Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to track object movement across a sequence of video frames.
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectTracking
3D point cloud object detection adjustment - Use this task type when you want workers to adjust 3D cuboids around objects in a 3D point cloud.
arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectDetection
3D point cloud object tracking adjustment - Use this task type when you want workers to adjust 3D cuboids around objects that appear in a sequence of 3D point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectTracking
3D point cloud semantic segmentation adjustment - Use this task type when you want workers to adjust a point-level semantic segmentation masks using a paint tool.
arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudSemanticSegmentation
Configures how labels are consolidated across human workers and processes output data.
" @@ -2113,7 +2147,7 @@ ], "members":{ "Image":{ - "shape":"Image", + "shape":"ContainerImage", "documentation":"The ECR path of the container. Refer to ContainerDefinition for more details.
" }, "ModelDataUrl":{ @@ -2674,6 +2708,19 @@ "type":"list", "member":{"shape":"Cidr"} }, + "ClientId":{ + "type":"string", + "max":128, + "min":1, + "pattern":"[\\w+-]+" + }, + "ClientSecret":{ + "type":"string", + "max":64, + "min":1, + "pattern":"[\\w+=/-]+", + "sensitive":true + }, "CodeRepositoryArn":{ "type":"string", "max":2048, @@ -2747,11 +2794,23 @@ "type":"list", "member":{"shape":"CodeRepositorySummary"} }, - "CognitoClientId":{ - "type":"string", - "max":128, - "min":1, - "pattern":"[\\w+]+" + "CognitoConfig":{ + "type":"structure", + "required":[ + "UserPool", + "ClientId" + ], + "members":{ + "UserPool":{ + "shape":"CognitoUserPool", + "documentation":"A user pool is a user directory in Amazon Cognito. With a user pool, your users can sign in to your web or mobile app through Amazon Cognito. Your users can also sign in through social identity providers like Google, Facebook, Amazon, or Apple, and through SAML identity providers.
" + }, + "ClientId":{ + "shape":"ClientId", + "documentation":"The client ID for your Amazon Cognito user pool.
" + } + }, + "documentation":"Use this parameter to configure your Amazon Cognito workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool.
" }, "CognitoMemberDefinition":{ "type":"structure", @@ -2770,7 +2829,7 @@ "documentation":"An identifier for a user group.
" }, "ClientId":{ - "shape":"CognitoClientId", + "shape":"ClientId", "documentation":"An identifier for an application client. You must create the app client ID using Amazon Cognito.
" } }, @@ -2847,7 +2906,6 @@ "CompilationJobName", "CompilationJobArn", "CreationTime", - "CompilationTargetDevice", "CompilationJobStatus" ], "members":{ @@ -2873,7 +2931,19 @@ }, "CompilationTargetDevice":{ "shape":"TargetDevice", - "documentation":"The type of device that the model will run on after compilation has completed.
" + "documentation":"The type of device that the model will run on after the compilation job has completed.
" + }, + "CompilationTargetPlatformOs":{ + "shape":"TargetPlatformOs", + "documentation":"The type of OS that the model will run on after the compilation job has completed.
" + }, + "CompilationTargetPlatformArch":{ + "shape":"TargetPlatformArch", + "documentation":"The type of architecture that the model will run on after the compilation job has completed.
" + }, + "CompilationTargetPlatformAccelerator":{ + "shape":"TargetPlatformAccelerator", + "documentation":"The type of accelerator that the model will run on after the compilation job has completed.
" }, "LastModifiedTime":{ "shape":"LastModifiedTime", @@ -2886,6 +2956,12 @@ }, "documentation":"A summary of a model compilation job.
" }, + "CompilerOptions":{ + "type":"string", + "max":1024, + "min":7, + "pattern":"^\\{.+\\}$" + }, "CompressionType":{ "type":"string", "enum":[ @@ -2935,7 +3011,7 @@ "documentation":"This parameter is ignored for models that contain only a PrimaryContainer.
When a ContainerDefinition is part of an inference pipeline, the value of the parameter uniquely identifies the container for the purposes of logging and metrics. For information, see Use Logs and Metrics to Monitor an Inference Pipeline. If you don't specify a value for this parameter for a ContainerDefinition that is part of an inference pipeline, a unique name is automatically assigned based on the position of the ContainerDefinition in the pipeline. If you specify a value for the ContainerHostName for any ContainerDefinition that is part of an inference pipeline, you must specify a value for the ContainerHostName parameter of every ContainerDefinition in that pipeline.
The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored. If you are using your own custom algorithm instead of an algorithm provided by Amazon SageMaker, the inference code must meet Amazon SageMaker requirements. Amazon SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker
Use this parameter to configure an Amazon Cognito private workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool.
Do not use OidcConfig if you specify values for CognitoConfig.
Use this parameter to configure a private workforce using your own OIDC Identity Provider. Do not use CognitoConfig if you specify values for OidcConfig.
The name of the private workforce.
" + }, + "Tags":{ + "shape":"TagList", + "documentation":"An array of key-value pairs that contain metadata to help you categorize and organize our workforce. Each tag consists of a key and a value, both of which you define.
" + } + } + }, + "CreateWorkforceResponse":{ + "type":"structure", + "required":["WorkforceArn"], + "members":{ + "WorkforceArn":{ + "shape":"WorkforceArn", + "documentation":"The Amazon Resource Name (ARN) of the workforce.
" + } + } + }, "CreateWorkteamRequest":{ "type":"structure", "required":[ @@ -4235,6 +4349,10 @@ "shape":"WorkteamName", "documentation":"The name of the work team. Use this name to identify the work team.
" }, + "WorkforceName":{ + "shape":"WorkforceName", + "documentation":"The name of the workforce.
" + }, "MemberDefinitions":{ "shape":"MemberDefinitions", "documentation":"A list of MemberDefinition objects that contains objects that identify the Amazon Cognito user pool that makes up the work team. For more information, see Amazon Cognito User Pools.
All of the CognitoMemberDefinition objects that make up the member definition must have the same ClientId and UserPool values.
The name of the workforce.
" + } + } + }, + "DeleteWorkforceResponse":{ + "type":"structure", + "members":{ + } + }, "DeleteWorkteamRequest":{ "type":"structure", "required":["WorkteamName"], @@ -4765,11 +4898,11 @@ "type":"structure", "members":{ "SpecifiedImage":{ - "shape":"Image", + "shape":"ContainerImage", "documentation":"The image path you specified when you created the model.
" }, "ResolvedImage":{ - "shape":"Image", + "shape":"ContainerImage", "documentation":"The specific digest path of the image hosted in this ProductionVariant.
The name of the experiment.
" + "documentation":"The name of an existing experiment to associate the trial component with.
" }, "TrialName":{ "shape":"ExperimentEntityName", - "documentation":"The name of the trial.
" + "documentation":"The name of an existing trial to associate the trial component with. If not specified, a new trial is created.
" }, "TrialComponentDisplayName":{ "shape":"ExperimentEntityName", - "documentation":"Display name for the trial component.
" + "documentation":"The display name for the trial component. If this key isn't specified, the display name is the trial component name.
" } }, - "documentation":"Configuration for the experiment.
" + "documentation":"Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:
" }, "ExperimentDescription":{ "type":"string", @@ -7364,6 +7497,18 @@ "type":"string", "pattern":"^https://([^/]+)/?(.*)$" }, + "Group":{ + "type":"string", + "max":63, + "min":1, + "pattern":"[\\p{L}\\p{M}\\p{S}\\p{N}\\p{P}]+" + }, + "Groups":{ + "type":"list", + "member":{"shape":"Group"}, + "max":10, + "min":1 + }, "HookParameters":{ "type":"map", "key":{"shape":"ConfigKey"}, @@ -7478,7 +7623,7 @@ }, "PreHumanTaskLambdaArn":{ "shape":"LambdaFunctionArn", - "documentation":"The Amazon Resource Name (ARN) of a Lambda function that is run before a data object is sent to a human worker. Use this function to provide input to a custom labeling job.
For built-in task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for PreHumanTaskLambdaArn. For custom labeling workflows, see Pre-annotation Lambda.
Bounding box - Finds the most similar boxes from different workers based on the Jaccard index of the boxes.
arn:aws:lambda:us-east-1:432418664414:function:PRE-BoundingBox
arn:aws:lambda:us-east-2:266458841044:function:PRE-BoundingBox
arn:aws:lambda:us-west-2:081040173940:function:PRE-BoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:PRE-BoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:PRE-BoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:PRE-BoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:PRE-BoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-BoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-BoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:PRE-BoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-BoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-BoundingBox
Image classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClass
arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClass
arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClass
Multi-label image classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClassMultiLabel
Semantic segmentation - Treats each pixel in an image as a multi-class classification and treats pixel annotations from workers as \"votes\" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:PRE-SemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-SemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-SemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-SemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-SemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-SemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-SemanticSegmentation
Text classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClass
arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClass
arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClass
Multi-label text classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClassMultiLabel
Named entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label.
arn:aws:lambda:us-east-1:432418664414:function:PRE-NamedEntityRecognition
arn:aws:lambda:us-east-2:266458841044:function:PRE-NamedEntityRecognition
arn:aws:lambda:us-west-2:081040173940:function:PRE-NamedEntityRecognition
arn:aws:lambda:ca-central-1:918755190332:function:PRE-NamedEntityRecognition
arn:aws:lambda:eu-west-1:568282634449:function:PRE-NamedEntityRecognition
arn:aws:lambda:eu-west-2:487402164563:function:PRE-NamedEntityRecognition
arn:aws:lambda:eu-central-1:203001061592:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-south-1:565803892007:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-NamedEntityRecognition
3D Point Cloud Modalities
Use the following pre-annotation lambdas for 3D point cloud labeling modality tasks. See 3D Point Cloud Task types to learn more.
3D Point Cloud Object Detection - Use this task type when you want workers to classify objects in a 3D point cloud by drawing 3D cuboids around objects. For example, you can use this task type to ask workers to identify different types of objects in a point cloud, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectDetection
3D Point Cloud Object Tracking - Use this task type when you want workers to draw 3D cuboids around objects that appear in a sequence of 3D point cloud frames. For example, you can use this task type to ask workers to track the movement of vehicles across multiple point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectTracking
3D Point Cloud Semantic Segmentation - Use this task type when you want workers to create a point-level semantic segmentation masks by painting objects in a 3D point cloud using different colors where each color is assigned to one of the classes you specify.
arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudSemanticSegmentation
Use the following ARNs for Label Verification and Adjustment Jobs
Use label verification and adjustment jobs to review and adjust labels. To learn more, see Verify and Adjust Labels .
Bounding box verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgement for bounding box labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectTracking
Bounding box adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations.
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentBoundingBox
Semantic segmentation verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgment for semantic segmentation labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationSemanticSegmentation
Semantic segmentation adjustment - Treats each pixel in an image as a multi-class classification and treats pixel adjusted annotations from workers as \"votes\" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentSemanticSegmentation
3D point cloud object detection adjustment - Adjust 3D cuboids in a point cloud frame.
arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectDetection
3D point cloud object tracking adjustment - Adjust 3D cuboids across a sequence of point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectTracking
3D point cloud semantic segmentation adjustment - Adjust semantic segmentation masks in a 3D point cloud.
arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudSemanticSegmentation
The Amazon Resource Name (ARN) of a Lambda function that is run before a data object is sent to a human worker. Use this function to provide input to a custom labeling job.
For built-in task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for PreHumanTaskLambdaArn. For custom labeling workflows, see Pre-annotation Lambda.
Bounding box - Finds the most similar boxes from different workers based on the Jaccard index of the boxes.
arn:aws:lambda:us-east-1:432418664414:function:PRE-BoundingBox
arn:aws:lambda:us-east-2:266458841044:function:PRE-BoundingBox
arn:aws:lambda:us-west-2:081040173940:function:PRE-BoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:PRE-BoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:PRE-BoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:PRE-BoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:PRE-BoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-BoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-BoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:PRE-BoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-BoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-BoundingBox
Image classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClass
arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClass
arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClass
Multi-label image classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClassMultiLabel
Semantic segmentation - Treats each pixel in an image as a multi-class classification and treats pixel annotations from workers as \"votes\" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:PRE-SemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-SemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-SemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-SemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-SemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-SemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-SemanticSegmentation
Text classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClass
arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClass
arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClass
Multi-label text classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClassMultiLabel
Named entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label.
arn:aws:lambda:us-east-1:432418664414:function:PRE-NamedEntityRecognition
arn:aws:lambda:us-east-2:266458841044:function:PRE-NamedEntityRecognition
arn:aws:lambda:us-west-2:081040173940:function:PRE-NamedEntityRecognition
arn:aws:lambda:ca-central-1:918755190332:function:PRE-NamedEntityRecognition
arn:aws:lambda:eu-west-1:568282634449:function:PRE-NamedEntityRecognition
arn:aws:lambda:eu-west-2:487402164563:function:PRE-NamedEntityRecognition
arn:aws:lambda:eu-central-1:203001061592:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-south-1:565803892007:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-NamedEntityRecognition
Video Classification - Use this task type when you need workers to classify videos using predefined labels that you specify. Workers are shown videos and are asked to choose one label for each video.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoMultiClass
arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoMultiClass
arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoMultiClass
Video Frame Object Detection - Use this task type to have workers identify and locate objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to identify and localize various objects in a series of video frames, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectDetection
Video Frame Object Tracking - Use this task type to have workers track the movement of objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to track the movement of objects, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectTracking
3D Point Cloud Modalities
Use the following pre-annotation lambdas for 3D point cloud labeling modality tasks. See 3D Point Cloud Task types to learn more.
3D Point Cloud Object Detection - Use this task type when you want workers to classify objects in a 3D point cloud by drawing 3D cuboids around objects. For example, you can use this task type to ask workers to identify different types of objects in a point cloud, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectDetection
3D Point Cloud Object Tracking - Use this task type when you want workers to draw 3D cuboids around objects that appear in a sequence of 3D point cloud frames. For example, you can use this task type to ask workers to track the movement of vehicles across multiple point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectTracking
3D Point Cloud Semantic Segmentation - Use this task type when you want workers to create a point-level semantic segmentation masks by painting objects in a 3D point cloud using different colors where each color is assigned to one of the classes you specify.
arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudSemanticSegmentation
Use the following ARNs for Label Verification and Adjustment Jobs
Use label verification and adjustment jobs to review and adjust labels. To learn more, see Verify and Adjust Labels .
Bounding box verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgement for bounding box labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectTracking
Bounding box adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations.
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentBoundingBox
Semantic segmentation verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgment for semantic segmentation labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationSemanticSegmentation
Semantic segmentation adjustment - Treats each pixel in an image as a multi-class classification and treats pixel adjusted annotations from workers as \"votes\" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentSemanticSegmentation
Video Frame Object Detection Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to classify and localize objects in a sequence of video frames.
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectDetection
Video Frame Object Tracking Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to track object movement across a sequence of video frames.
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectTracking
3D point cloud object detection adjustment - Adjust 3D cuboids in a point cloud frame.
arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectDetection
3D point cloud object tracking adjustment - Adjust 3D cuboids across a sequence of point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectTracking
3D point cloud semantic segmentation adjustment - Adjust semantic segmentation masks in a 3D point cloud.
arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudSemanticSegmentation
Sort workforces using the workforce name or creation date.
" + }, + "SortOrder":{ + "shape":"SortOrder", + "documentation":"Sort workforces in ascending or descending order.
" + }, + "NameContains":{ + "shape":"WorkforceName", + "documentation":"A filter you can use to search for workforces using part of the workforce name.
" + }, + "NextToken":{ + "shape":"NextToken", + "documentation":"A token to resume pagination.
" + }, + "MaxResults":{ + "shape":"MaxResults", + "documentation":"The maximum number of workforces returned in the response.
", + "box":true + } + } + }, + "ListWorkforcesResponse":{ + "type":"structure", + "required":["Workforces"], + "members":{ + "Workforces":{ + "shape":"Workforces", + "documentation":"A list containing information about your workforce.
" + }, + "NextToken":{ + "shape":"NextToken", + "documentation":"A token to resume pagination.
" + } + } + }, + "ListWorkforcesSortByOptions":{ + "type":"string", + "enum":[ + "Name", + "CreateDate" + ] + }, "ListWorkteamsRequest":{ "type":"structure", "members":{ @@ -10186,6 +10378,10 @@ "CognitoMemberDefinition":{ "shape":"CognitoMemberDefinition", "documentation":"The Amazon Cognito user group that is part of the work team.
" + }, + "OidcMemberDefinition":{ + "shape":"OidcMemberDefinition", + "documentation":"A list user groups that exist in your OIDC Identity Provider (IdP). One to ten groups can be used to create a single private work team. When you add a user group to the list of Groups, you can add that user group to one or more private work teams. If you add a user group to a private work team, all workers in that user group are added to the work team.
Defines the Amazon Cognito user group that is part of a work team.
" @@ -10307,7 +10503,7 @@ "documentation":"The DNS host name for the Docker container.
" }, "Image":{ - "shape":"Image", + "shape":"ContainerImage", "documentation":"The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.
If you are using your own custom algorithm instead of an algorithm provided by Amazon SageMaker, the inference code must meet Amazon SageMaker requirements. Amazon SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker.
Specifies the number of training jobs that this hyperparameter tuning job launched, categorized by the status of their objective metric. The objective metric status shows whether the final objective metric for the training job has been evaluated by the tuning job and used in the hyperparameter tuning process.
" }, + "OidcConfig":{ + "type":"structure", + "required":[ + "ClientId", + "ClientSecret", + "Issuer", + "AuthorizationEndpoint", + "TokenEndpoint", + "UserInfoEndpoint", + "LogoutEndpoint", + "JwksUri" + ], + "members":{ + "ClientId":{ + "shape":"ClientId", + "documentation":"The OIDC IdP client ID used to configure your private workforce.
" + }, + "ClientSecret":{ + "shape":"ClientSecret", + "documentation":"The OIDC IdP client secret used to configure your private workforce.
" + }, + "Issuer":{ + "shape":"OidcEndpoint", + "documentation":"The OIDC IdP issuer used to configure your private workforce.
" + }, + "AuthorizationEndpoint":{ + "shape":"OidcEndpoint", + "documentation":"The OIDC IdP authorization endpoint used to configure your private workforce.
" + }, + "TokenEndpoint":{ + "shape":"OidcEndpoint", + "documentation":"The OIDC IdP token endpoint used to configure your private workforce.
" + }, + "UserInfoEndpoint":{ + "shape":"OidcEndpoint", + "documentation":"The OIDC IdP user information endpoint used to configure your private workforce.
" + }, + "LogoutEndpoint":{ + "shape":"OidcEndpoint", + "documentation":"The OIDC IdP logout endpoint used to configure your private workforce.
" + }, + "JwksUri":{ + "shape":"OidcEndpoint", + "documentation":"The OIDC IdP JSON Web Key Set (Jwks) URI used to configure your private workforce.
" + } + }, + "documentation":"Use this parameter to configure your OIDC Identity Provider (IdP).
" + }, + "OidcConfigForResponse":{ + "type":"structure", + "members":{ + "ClientId":{ + "shape":"ClientId", + "documentation":"The OIDC IdP client ID used to configure your private workforce.
" + }, + "Issuer":{ + "shape":"OidcEndpoint", + "documentation":"The OIDC IdP issuer used to configure your private workforce.
" + }, + "AuthorizationEndpoint":{ + "shape":"OidcEndpoint", + "documentation":"The OIDC IdP authorization endpoint used to configure your private workforce.
" + }, + "TokenEndpoint":{ + "shape":"OidcEndpoint", + "documentation":"The OIDC IdP token endpoint used to configure your private workforce.
" + }, + "UserInfoEndpoint":{ + "shape":"OidcEndpoint", + "documentation":"The OIDC IdP user information endpoint used to configure your private workforce.
" + }, + "LogoutEndpoint":{ + "shape":"OidcEndpoint", + "documentation":"The OIDC IdP logout endpoint used to configure your private workforce.
" + }, + "JwksUri":{ + "shape":"OidcEndpoint", + "documentation":"The OIDC IdP JSON Web Key Set (Jwks) URI used to configure your private workforce.
" + } + }, + "documentation":"Your Amazon Cognito workforce configuration.
" + }, + "OidcEndpoint":{ + "type":"string", + "max":500, + "pattern":"https://\\S+" + }, + "OidcMemberDefinition":{ + "type":"structure", + "required":["Groups"], + "members":{ + "Groups":{ + "shape":"Groups", + "documentation":"A list of comma seperated strings that identifies user groups in your OIDC IdP. Each user group is made up of a group of private workers.
" + } + }, + "documentation":"A list user groups that exist in your OIDC Identity Provider (IdP). One to ten groups can be used to create a single private work team. When you add a user group to the list of Groups, you can add that user group to one or more private work teams. If you add a user group to a private work team, all workers in that user group are added to the work team.
Identifies the S3 path where you want Amazon SageMaker to store the model artifacts. For example, s3://bucket-name/key-name-prefix.
" + "documentation":"Identifies the S3 bucket where you want Amazon SageMaker to store the model artifacts. For example, s3://bucket-name/key-name-prefix.
Identifies the device that you want to run your model on after it has been compiled. For example: ml_c5.
" + "documentation":"Identifies the target device or the machine learning instance that you want to run your model on after the compilation has completed. Alternatively, you can specify OS, architecture, and accelerator using TargetPlatform fields. It can be used instead of TargetPlatform.
Contains information about a target platform that you want your model to run on, such as OS, architecture, and accelerators. It is an alternative of TargetDevice.
The following examples show how to configure the TargetPlatform and CompilerOptions JSON strings for popular target platforms:
Raspberry Pi 3 Model B+
\"TargetPlatform\": {\"Os\": \"LINUX\", \"Arch\": \"ARM_EABIHF\"},
\"CompilerOptions\": {'mattr': ['+neon']}
Jetson TX2
\"TargetPlatform\": {\"Os\": \"LINUX\", \"Arch\": \"ARM64\", \"Accelerator\": \"NVIDIA\"},
\"CompilerOptions\": {'gpu-code': 'sm_62', 'trt-ver': '6.0.1', 'cuda-ver': '10.0'}
EC2 m5.2xlarge instance OS
\"TargetPlatform\": {\"Os\": \"LINUX\", \"Arch\": \"X86_64\", \"Accelerator\": \"NVIDIA\"},
\"CompilerOptions\": {'mcpu': 'skylake-avx512'}
RK3399
\"TargetPlatform\": {\"Os\": \"LINUX\", \"Arch\": \"ARM64\", \"Accelerator\": \"MALI\"}
ARMv7 phone (CPU)
\"TargetPlatform\": {\"Os\": \"ANDROID\", \"Arch\": \"ARM_EABI\"},
\"CompilerOptions\": {'ANDROID_PLATFORM': 25, 'mattr': ['+neon']}
ARMv8 phone (CPU)
\"TargetPlatform\": {\"Os\": \"ANDROID\", \"Arch\": \"ARM64\"},
\"CompilerOptions\": {'ANDROID_PLATFORM': 29}
Specifies additional parameters for compiler options in JSON format. The compiler options are TargetPlatform specific. It is required for NVIDIA accelerators and highly recommended for CPU compliations. For any other cases, it is optional to specify CompilerOptions.
CPU: Compilation for CPU supports the following compiler options.
mcpu: CPU micro-architecture. For example, {'mcpu': 'skylake-avx512'}
mattr: CPU flags. For example, {'mattr': ['+neon', '+vfpv4']}
ARM: Details of ARM CPU compilations.
NEON: NEON is an implementation of the Advanced SIMD extension used in ARMv7 processors.
For example, add {'mattr': ['+neon']} to the compiler options if compiling for ARM 32-bit platform with the NEON support.
NVIDIA: Compilation for NVIDIA GPU supports the following compiler options.
gpu_code: Specifies the targeted architecture.
trt-ver: Specifies the TensorRT versions in x.y.z. format.
cuda-ver: Specifies the CUDA version in x.y format.
For example, {'gpu-code': 'sm_72', 'trt-ver': '6.0.1', 'cuda-ver': '10.1'}
ANDROID: Compilation for the Android OS supports the following compiler options:
ANDROID_PLATFORM: Specifies the Android API levels. Available levels range from 21 to 29. For example, {'ANDROID_PLATFORM': 28}.
mattr: Add {'mattr': ['+neon']} to compiler options if compiling for ARM 32-bit platform with NEON support.
Contains information about the output location for the compiled model and the device (target) that the model runs on.
" + "documentation":"Contains information about the output location for the compiled model and the target device that the model runs on. TargetDevice and TargetPlatform are mutually exclusive, so you need to choose one between the two to specify your target device or platform. If you cannot find your device you want to use from the TargetDevice list, use TargetPlatform to describe the platform of your edge device and CompilerOptions if there are specific settings that are required or recommended to use for particular TargetPlatform.
The Amazon Resource Name (ARN) of the SageMaker image created on the instance.
" }, "InstanceType":{ @@ -12316,11 +12615,6 @@ "max":1024, "pattern":"^(https|s3)://([^/]+)/?(.*)$" }, - "SageMakerImageArn":{ - "type":"string", - "max":256, - "pattern":"^arn:aws(-[\\w]+)*:sagemaker:.+:[0-9]{12}:image/[a-z0-9]([-.]?[a-z0-9])*$" - }, "SamplingPercentage":{ "type":"integer", "max":100, @@ -12911,6 +13205,7 @@ "ml_c5", "ml_p2", "ml_p3", + "ml_g4dn", "ml_inf1", "jetson_tx1", "jetson_tx2", @@ -12926,10 +13221,59 @@ "qcs605", "qcs603", "sitara_am57x", - "amba_cv22" + "amba_cv22", + "x86_win32", + "x86_win64" ] }, "TargetObjectiveMetricValue":{"type":"float"}, + "TargetPlatform":{ + "type":"structure", + "required":[ + "Os", + "Arch" + ], + "members":{ + "Os":{ + "shape":"TargetPlatformOs", + "documentation":"Specifies a target platform OS.
LINUX: Linux-based operating systems.
ANDROID: Android operating systems. Android API level can be specified using the ANDROID_PLATFORM compiler option. For example, \"CompilerOptions\": {'ANDROID_PLATFORM': 28}
Specifies a target platform architecture.
X86_64: 64-bit version of the x86 instruction set.
X86: 32-bit version of the x86 instruction set.
ARM64: ARMv8 64-bit CPU.
ARM_EABIHF: ARMv7 32-bit, Hard Float.
ARM_EABI: ARMv7 32-bit, Soft Float. Used by Android 32-bit ARM platform.
Specifies a target platform accelerator (optional).
NVIDIA: Nvidia graphics processing unit. It also requires gpu-code, trt-ver, cuda-ver compiler options
MALI: ARM Mali graphics processor
INTEL_GRAPHICS: Integrated Intel graphics
Contains information about a target platform that you want your model to run on, such as OS, architecture, and accelerators. It is an alternative of TargetDevice.
The Amazon ECR registry path of the Docker image that contains the training algorithm.
" }, "TrainingImageDigest":{ @@ -13494,6 +13838,78 @@ "member":{"shape":"TransformInstanceType"}, "min":1 }, + "TransformJob":{ + "type":"structure", + "members":{ + "TransformJobName":{ + "shape":"TransformJobName", + "documentation":"The name of the transform job.
" + }, + "TransformJobArn":{ + "shape":"TransformJobArn", + "documentation":"The Amazon Resource Name (ARN) of the transform job.
" + }, + "TransformJobStatus":{ + "shape":"TransformJobStatus", + "documentation":"The status of the transform job.
Transform job statuses are:
InProgress - The job is in progress.
Completed - The job has completed.
Failed - The transform job has failed. To see the reason for the failure, see the FailureReason field in the response to a DescribeTransformJob call.
Stopping - The transform job is stopping.
Stopped - The transform job has stopped.
If the transform job failed, the reason it failed.
" + }, + "ModelName":{ + "shape":"ModelName", + "documentation":"The name of the model associated with the transform job.
" + }, + "MaxConcurrentTransforms":{ + "shape":"MaxConcurrentTransforms", + "documentation":"The maximum number of parallel requests that can be sent to each instance in a transform job. If MaxConcurrentTransforms is set to 0 or left unset, SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is 1. For built-in algorithms, you don't need to set a value for MaxConcurrentTransforms.
The maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in MaxPayloadInMB must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is 6 MB. For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to 0. This feature works only in supported algorithms. Currently, SageMaker built-in algorithms do not support HTTP chunked encoding.
Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.
" + }, + "Environment":{ + "shape":"TransformEnvironmentMap", + "documentation":"The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
" + }, + "TransformInput":{"shape":"TransformInput"}, + "TransformOutput":{"shape":"TransformOutput"}, + "TransformResources":{"shape":"TransformResources"}, + "CreationTime":{ + "shape":"Timestamp", + "documentation":"A timestamp that shows when the transform Job was created.
" + }, + "TransformStartTime":{ + "shape":"Timestamp", + "documentation":"Indicates when the transform job starts on ML instances. You are billed for the time interval between this time and the value of TransformEndTime.
Indicates when the transform job has been completed, or has stopped or failed. You are billed for the time interval between this time and the value of TransformStartTime.
The Amazon Resource Name (ARN) of the labeling job that created the transform job.
" + }, + "AutoMLJobArn":{ + "shape":"AutoMLJobArn", + "documentation":"The Amazon Resource Name (ARN) of the AutoML job that created the transform job.
" + }, + "DataProcessing":{"shape":"DataProcessing"}, + "ExperimentConfig":{"shape":"ExperimentConfig"}, + "Tags":{ + "shape":"TagList", + "documentation":"A list of tags associated with the transform job.
" + } + }, + "documentation":"A batch transform job. For information about SageMaker batch transform, see Use Batch Transform.
" + }, "TransformJobArn":{ "type":"string", "max":256, @@ -13656,7 +14072,7 @@ }, "S3Uri":{ "shape":"S3Uri", - "documentation":"Depending on the value specified for the S3DataType, identifies either a key name prefix or a manifest. For example:
A key name prefix might look like this: s3://bucketname/exampleprefix.
A manifest might look like this: s3://bucketname/example.manifest
The manifest is an S3 object which is a JSON file with the following format:
[ {\"prefix\": \"s3://customer_bucket/some/prefix/\"},
\"relative/path/to/custdata-1\",
\"relative/path/custdata-2\",
...
\"relative/path/custdata-N\"
]
The preceding JSON matches the following s3Uris:
s3://customer_bucket/some/prefix/relative/path/to/custdata-1
s3://customer_bucket/some/prefix/relative/path/custdata-2
...
s3://customer_bucket/some/prefix/relative/path/custdata-N
The complete set of S3Uris in this manifest constitutes the input data for the channel for this datasource. The object that each S3Uris points to must be readable by the IAM role that Amazon SageMaker uses to perform tasks on your behalf.
Depending on the value specified for the S3DataType, identifies either a key name prefix or a manifest. For example:
A key name prefix might look like this: s3://bucketname/exampleprefix.
A manifest might look like this: s3://bucketname/example.manifest
The manifest is an S3 object which is a JSON file with the following format:
[ {\"prefix\": \"s3://customer_bucket/some/prefix/\"},
\"relative/path/to/custdata-1\",
\"relative/path/custdata-2\",
...
\"relative/path/custdata-N\"
]
The preceding JSON matches the following S3Uris:
s3://customer_bucket/some/prefix/relative/path/to/custdata-1
s3://customer_bucket/some/prefix/relative/path/custdata-2
...
s3://customer_bucket/some/prefix/relative/path/custdata-N
The complete set of S3Uris in this manifest constitutes the input data for the channel for this datasource. The object that each S3Uris points to must be readable by the IAM role that Amazon SageMaker uses to perform tasks on your behalf.
Describes the S3 data source.
" @@ -13951,6 +14367,10 @@ "ProcessingJob":{ "shape":"ProcessingJob", "documentation":"Information about a processing job that's the source of a trial component.
" + }, + "TransformJob":{ + "shape":"TransformJob", + "documentation":"Information about a transform job that's the source of the trial component.
" } }, "documentation":"Detailed information about the source of a trial component. Either ProcessingJob or TrainingJob is returned.
The ARN of the worker task template used to render the worker UI and tools for labeling job tasks.
Use this parameter when you are creating a labeling job for 3D point cloud labeling modalities. Use your labeling job task type to select one of the following ARN's and use it with this parameter when you create a labeling job. Replace aws-region with the AWS region you are creating your labeling job in.
Use this HumanTaskUiArn for 3D point cloud object detection and 3D point cloud object detection adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectDetection
Use this HumanTaskUiArn for 3D point cloud object tracking and 3D point cloud object tracking adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectTracking
Use this HumanTaskUiArn for 3D point cloud semantic segmentation and 3D point cloud semantic segmentation adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudSemanticSegmentation
The ARN of the worker task template used to render the worker UI and tools for labeling job tasks.
Use this parameter when you are creating a labeling job for 3D point cloud and video fram labeling jobs. Use your labeling job task type to select one of the following ARN's and use it with this parameter when you create a labeling job. Replace aws-region with the AWS region you are creating your labeling job in.
3D Point Cloud HumanTaskUiArns
Use this HumanTaskUiArn for 3D point cloud object detection and 3D point cloud object detection adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectDetection
Use this HumanTaskUiArn for 3D point cloud object tracking and 3D point cloud object tracking adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectTracking
Use this HumanTaskUiArn for 3D point cloud semantic segmentation and 3D point cloud semantic segmentation adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudSemanticSegmentation
Video Frame HumanTaskUiArns
Use this HumanTaskUiArn for video frame object detection and video frame object detection adjustment labeling jobs.
arn:aws:sagemaker:region:394669845002:human-task-ui/VideoObjectDetection
Use this HumanTaskUiArn for video frame object tracking and video frame object tracking adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/VideoObjectTracking
Provided configuration information for the worker UI for a labeling job.
" @@ -14516,6 +14936,10 @@ "SourceIpConfig":{ "shape":"SourceIpConfig", "documentation":"A list of one to ten worker IP address ranges (CIDRs) that can be used to access tasks assigned to this workforce.
Maximum: Ten CIDR values
" + }, + "OidcConfig":{ + "shape":"OidcConfig", + "documentation":"Use this parameter to update your OIDC Identity Provider (IdP) configuration for a workforce made using your own IdP.
" } } }, @@ -14746,7 +15170,7 @@ "members":{ "WorkforceName":{ "shape":"WorkforceName", - "documentation":"The name of the private workforce whose access you want to restrict. WorkforceName is automatically set to default when a workforce is created and cannot be modified.
The name of the private workforce.
" }, "WorkforceArn":{ "shape":"WorkforceArn", @@ -14759,6 +15183,22 @@ "SourceIpConfig":{ "shape":"SourceIpConfig", "documentation":"A list of one to ten IP address ranges (CIDRs) to be added to the workforce allow list.
" + }, + "SubDomain":{ + "shape":"String", + "documentation":"The subdomain for your OIDC Identity Provider.
" + }, + "CognitoConfig":{ + "shape":"CognitoConfig", + "documentation":"The configuration of an Amazon Cognito workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool.
" + }, + "OidcConfig":{ + "shape":"OidcConfigForResponse", + "documentation":"The configuration of an OIDC Identity Provider (IdP) private workforce.
" + }, + "CreateDate":{ + "shape":"Timestamp", + "documentation":"The date that the workforce is created.
" } }, "documentation":"A single private workforce, which is automatically created when you create your first private work team. You can create one private work force in each AWS Region. By default, any workforce-related API operation used in a specific region will apply to the workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.
" @@ -14774,6 +15214,10 @@ "min":1, "pattern":"^[a-zA-Z0-9]([a-zA-Z0-9\\-])*$" }, + "Workforces":{ + "type":"list", + "member":{"shape":"Workforce"} + }, "Workteam":{ "type":"structure", "required":[ @@ -14795,6 +15239,10 @@ "shape":"WorkteamArn", "documentation":"The Amazon Resource Name (ARN) that identifies the work team.
" }, + "WorkforceArn":{ + "shape":"WorkforceArn", + "documentation":"The Amazon Resource Name (ARN) of the workforce.
" + }, "ProductListingIds":{ "shape":"ProductListings", "documentation":"The Amazon Marketplace identifier for a vendor's work team.
" From 90783a2c42be0f939ba0b116e573552e2e100702 Mon Sep 17 00:00:00 2001 From: AWS <> Date: Fri, 24 Jul 2020 18:04:38 +0000 Subject: [PATCH 08/11] Amazon FSx Update: Documentation update for FSx for Lustre --- .../feature-AmazonFSx-9200a31.json | 5 +++++ .../codegen-resources/service-2.json | 20 +++++++++---------- 2 files changed, 15 insertions(+), 10 deletions(-) create mode 100644 .changes/next-release/feature-AmazonFSx-9200a31.json diff --git a/.changes/next-release/feature-AmazonFSx-9200a31.json b/.changes/next-release/feature-AmazonFSx-9200a31.json new file mode 100644 index 000000000000..42319c87691e --- /dev/null +++ b/.changes/next-release/feature-AmazonFSx-9200a31.json @@ -0,0 +1,5 @@ +{ + "type": "feature", + "category": "Amazon FSx", + "description": "Documentation update for FSx for Lustre" +} diff --git a/services/fsx/src/main/resources/codegen-resources/service-2.json b/services/fsx/src/main/resources/codegen-resources/service-2.json index 4ca5a49e55d8..b1b576fa0cbd 100644 --- a/services/fsx/src/main/resources/codegen-resources/service-2.json +++ b/services/fsx/src/main/resources/codegen-resources/service-2.json @@ -48,7 +48,7 @@ {"shape":"ServiceLimitExceeded"}, {"shape":"InternalServerError"} ], - "documentation":"Creates a backup of an existing Amazon FSx file system. Creating regular backups for your file system is a best practice, enabling you to restore a file system from a backup if an issue arises with the original file system.
For Amazon FSx for Lustre file systems, you can create a backup only for file systems with the following configuration:
a Persistent deployment type
is not linked to an Amazon S3 data respository.
For more information, see https://docs.aws.amazon.com/fsx/latest/LustreGuide/lustre-backups.html.
If a backup with the specified client request token exists, and the parameters match, this operation returns the description of the existing backup. If a backup specified client request token exists, and the parameters don't match, this operation returns IncompatibleParameterError. If a backup with the specified client request token doesn't exist, CreateBackup does the following:
Creates a new Amazon FSx backup with an assigned ID, and an initial lifecycle state of CREATING.
Returns the description of the backup.
By using the idempotent operation, you can retry a CreateBackup operation without the risk of creating an extra backup. This approach can be useful when an initial call fails in a way that makes it unclear whether a backup was created. If you use the same client request token and the initial call created a backup, the operation returns a successful result because all the parameters are the same.
The CreateBackup operation returns while the backup's lifecycle state is still CREATING. You can check the backup creation status by calling the DescribeBackups operation, which returns the backup state along with other information.
Creates a backup of an existing Amazon FSx file system. Creating regular backups for your file system is a best practice, enabling you to restore a file system from a backup if an issue arises with the original file system.
For Amazon FSx for Lustre file systems, you can create a backup only for file systems with the following configuration:
a Persistent deployment type
is not linked to an Amazon S3 data respository.
For more information about backing up Amazon FSx for Lustre file systems, see Working with FSx for Lustre backups.
For more information about backing up Amazon FSx for Lustre file systems, see Working with FSx for Windows backups.
If a backup with the specified client request token exists, and the parameters match, this operation returns the description of the existing backup. If a backup specified client request token exists, and the parameters don't match, this operation returns IncompatibleParameterError. If a backup with the specified client request token doesn't exist, CreateBackup does the following:
Creates a new Amazon FSx backup with an assigned ID, and an initial lifecycle state of CREATING.
Returns the description of the backup.
By using the idempotent operation, you can retry a CreateBackup operation without the risk of creating an extra backup. This approach can be useful when an initial call fails in a way that makes it unclear whether a backup was created. If you use the same client request token and the initial call created a backup, the operation returns a successful result because all the parameters are the same.
The CreateBackup operation returns while the backup's lifecycle state is still CREATING. You can check the backup creation status by calling the DescribeBackups operation, which returns the backup state along with other information.
Use this operation to update the configuration of an existing Amazon FSx file system. For an Amazon FSx for Lustre file system, you can update only the WeeklyMaintenanceStartTime. For an Amazon for Windows File Server file system, you can update the following properties:
AutomaticBackupRetentionDays
DailyAutomaticBackupStartTime
SelfManagedActiveDirectoryConfiguration
StorageCapacity
ThroughputCapacity
WeeklyMaintenanceStartTime
You can update multiple properties in a single request.
" + "documentation":"Use this operation to update the configuration of an existing Amazon FSx file system. You can update multiple properties in a single request.
For Amazon FSx for Windows File Server file systems, you can update the following properties:
AutomaticBackupRetentionDays
DailyAutomaticBackupStartTime
SelfManagedActiveDirectoryConfiguration
StorageCapacity
ThroughputCapacity
WeeklyMaintenanceStartTime
For Amazon FSx for Lustre file systems, you can update the following properties:
AutoImportPolicy
AutomaticBackupRetentionDays
DailyAutomaticBackupStartTime
WeeklyMaintenanceStartTime
The type of the backup.
" + "documentation":"The type of the file system backup.
" }, "ProgressPercent":{"shape":"ProgressPercent"}, "CreationTime":{ @@ -519,7 +519,7 @@ "Backups":{ "type":"list", "member":{"shape":"Backup"}, - "documentation":"A list of backups.
", + "documentation":"A list of file system backups.
", "max":50 }, "BadRequest":{ @@ -719,11 +719,11 @@ }, "DeploymentType":{ "shape":"LustreDeploymentType", - "documentation":" Choose SCRATCH_1 and SCRATCH_2 deployment types when you need temporary storage and shorter-term processing of data. The SCRATCH_2 deployment type provides in-transit encryption of data and higher burst throughput capacity than SCRATCH_1.
This option can only be set for for PERSISTENT_1 deployments types.
Choose PERSISTENT_1 deployment type for longer-term storage and workloads and encryption of data in transit. To learn more about deployment types, see FSx for Lustre Deployment Options.
Encryption of data in-transit is automatically enabled when you access a SCRATCH_2 or PERSISTENT_1 file system from Amazon EC2 instances that support this feature. (Default = SCRATCH_1)
Encryption of data in-transit for SCRATCH_2 and PERSISTENT_1 deployment types is supported when accessed from supported instance types in supported AWS Regions. To learn more, Encrypting Data in Transit.
Choose SCRATCH_1 and SCRATCH_2 deployment types when you need temporary storage and shorter-term processing of data. The SCRATCH_2 deployment type provides in-transit encryption of data and higher burst throughput capacity than SCRATCH_1.
Choose PERSISTENT_1 deployment type for longer-term storage and workloads and encryption of data in transit. To learn more about deployment types, see FSx for Lustre Deployment Options.
Encryption of data in-transit is automatically enabled when you access a SCRATCH_2 or PERSISTENT_1 file system from Amazon EC2 instances that support this feature. (Default = SCRATCH_1)
Encryption of data in-transit for SCRATCH_2 and PERSISTENT_1 deployment types is supported when accessed from supported instance types in supported AWS Regions. To learn more, Encrypting Data in Transit.
Use this property to turn the Autoimport feature on and off. AutoImport enables your FSx for Lustre file system to automatically update its contents with changes that have been made to its linked Amazon S3 data repository. You can set the policy to have one the following values:
NONE - (Default) Autoimport is turned off. Changes to your S3 repository will not be reflected on the FSx file system.
NEW - Autoimport is turned on; only new files in the linked S3 repository will be imported to the FSx file system. Updates to existing files and deleted files will not be imported to the FSx file system.
NEW_CHANGED - Autoimport is turned on; new files and changes to existing files in the linked S3 repository will be imported to the FSx file system. Files deleted in S3 are not deleted in the FSx file system.
NEW_CHANGED_DELETED - Autoimport is turned on; new files, changes to existing files, and deleted files in the linked S3 repository will be imported to the FSx file system.
(Optional) Use this property to configure the AutoImport feature on the file system's linked Amazon S3 data repository. You use AutoImport to update the contents of your FSx for Lustre file system automatically with changes that occur in the linked S3 data repository. AutoImportPolicy can have the following values:
NONE - (Default) AutoImport is off. Changes in the linked data repository are not reflected on the FSx file system.
NEW - AutoImport is on. New files in the linked data repository that do not currently exist in the FSx file system are automatically imported. Updates to existing FSx files are not imported to the FSx file system. Files deleted from the linked data repository are not deleted from the FSx file system.
NEW_CHANGED - AutoImport is on. New files in the linked S3 data repository that do not currently exist in the FSx file system are automatically imported. Changes to existing FSx files in the linked repository are also automatically imported to the FSx file system. Files deleted from the linked data repository are not deleted from the FSx file system.
For more information, see Automatically import updates from your S3 bucket.
" }, "PerUnitStorageThroughput":{ "shape":"PerUnitStorageThroughput", @@ -733,7 +733,7 @@ "AutomaticBackupRetentionDays":{"shape":"AutomaticBackupRetentionDays"}, "CopyTagsToBackups":{ "shape":"Flag", - "documentation":"A boolean flag indicating whether tags for the file system should be copied to backups. This value defaults to false. If it's set to true, all tags for the file system are copied to all automatic and user-initiated backups where the user doesn't specify tags. If this value is true, and you specify one or more tags, only the specified tags are copied to backups. If you specify one or more tags when creating a user-initiated backup, no tags are copied from the file system, regardless of this value.
" + "documentation":"A boolean flag indicating whether tags for the file system should be copied to backups. This value defaults to false. If it's set to true, all tags for the file system are copied to all automatic and user-initiated backups where the user doesn't specify tags. If this value is true, and you specify one or more tags, only the specified tags are copied to backups. If you specify one or more tags when creating a user-initiated backup, no tags are copied from the file system, regardless of this value.
For more information, see Working with backups.
" } }, "documentation":"The Lustre configuration for the file system being created.
" @@ -857,7 +857,7 @@ "members":{ "Lifecycle":{ "shape":"DataRepositoryLifecycle", - "documentation":"Describes the state of the file system's S3 durable data repository, if it is configured with an S3 repository. The lifecycle can have the following values:
CREATING - Amazon FSx is creating the new data repository.
AVAILABLE - The data repository is available for use.
MISCONFIGURED - The data repository is in a failed but recoverable state.
UPDATING - The data repository is undergoing a customer initiated update.
Describes the state of the file system's S3 durable data repository, if it is configured with an S3 repository. The lifecycle can have the following values:
CREATING - The data repository configuration between the FSx file system and the linked S3 data repository is being created. The data repository is unavailable.
AVAILABLE - The data repository is available for use.
MISCONFIGURED - Amazon FSx cannot automatically import updates from the S3 bucket until the data repository configuration is corrected. For more information, see Troubleshooting a Misconfigured linked S3 bucket.
UPDATING - The data repository is undergoing a customer initiated update and availability may be impacted.
Describes the data repository's AutoImportPolicy. AutoImport enables your FSx for Lustre file system to automatically update its contents with changes that have been made to its linked Amazon S3 data repository. The policy can have the following values:
NONE - (Default) Autoimport is turned off, Changes to your S3 repository will not be reflected on the FSx file system.
NEW - Autoimport is turned on; only new files in the linked S3 repository will be imported to the FSx file system. Updates to existing files and deleted files will not be imported to the FSx file system.
NEW_CHANGED - Autoimport is turned on; new files and changes to existing files in the linked S3 repository will be imported to the FSx file system. Files deleted in S3 are not deleted in the FSx file system.
NEW_CHANGED_DELETED - Autoimport is turned on; new files, changes to existing files, and deleted files in the linked S3 repository will be imported to the FSx file system.
Describes the file system's linked S3 data repository's AutoImportPolicy. The AutoImportPolicy configures how your FSx for Lustre file system automatically updates its contents with changes that occur in the linked S3 data repository. AutoImportPolicy can have the following values:
NONE - (Default) AutoImport is off. Changes in the linked data repository are not reflected on the FSx file system.
NEW - AutoImport is on. New files in the linked data repository that do not currently exist in the FSx file system are automatically imported. Updates to existing FSx files are not imported to the FSx file system. Files deleted from the linked data repository are not deleted from the FSx file system.
NEW_CHANGED - AutoImport is on. New files in the linked S3 data repository that do not currently exist in the FSx file system are automatically imported. Changes to existing FSx files in the linked repository are also automatically imported to the FSx file system. Files deleted from the linked data repository are not deleted from the FSx file system.
For more information, see Automatically import updates from your S3 bucket.
" }, "FailureDetails":{"shape":"DataRepositoryFailureDetails"} }, @@ -2053,7 +2053,7 @@ "AutomaticBackupRetentionDays":{"shape":"AutomaticBackupRetentionDays"}, "AutoImportPolicy":{ "shape":"AutoImportPolicyType", - "documentation":"Use this property to turn the Autoimport feature on and off. AutoImport enables your FSx for Lustre file system to automatically update its contents with changes that have been made to its linked Amazon S3 data repository. You can set the policy to have one the following values:
NONE - (Default) Autoimport is turned off. Changes to your S3 repository will not be reflected on the FSx file system.
NEW - Autoimport is turned on; only new files in the linked S3 repository will be imported to the FSx file system. Updates to existing files and deleted files will not be imported to the FSx file system.
NEW_CHANGED - Autoimport is turned on; new files and changes to existing files in the linked S3 repository will be imported to the FSx file system. Files deleted in S3 are not deleted in the FSx file system.
NEW_CHANGED_DELETED - Autoimport is turned on; new files, changes to existing files, and deleted files in the linked S3 repository will be imported to the FSx file system.
(Optional) Use this property to configure the AutoImport feature on the file system's linked Amazon S3 data repository. You use AutoImport to update the contents of your FSx for Lustre file system automatically with changes that occur in the linked S3 data repository. AutoImportPolicy can have the following values:
NONE - (Default) AutoImport is off. Changes in the linked data repository are not reflected on the FSx file system.
NEW - AutoImport is on. New files in the linked data repository that do not currently exist in the FSx file system are automatically imported. Updates to existing FSx files are not imported to the FSx file system. Files deleted from the linked data repository are not deleted from the FSx file system.
NEW_CHANGED - AutoImport is on. New files in the linked S3 data repository that do not currently exist in the FSx file system are automatically imported. Changes to existing FSx files in the linked repository are also automatically imported to the FSx file system. Files deleted from the linked data repository are not deleted from the FSx file system.
For more information, see Automatically import updates from your S3 bucket.
" } }, "documentation":"The configuration object for Amazon FSx for Lustre file systems used in the UpdateFileSystem operation.
Gets one or more outcomes. This is a paginated API. If you provide a null maxResults, this actions retrieves a maximum of 100 records per page. If you provide a maxResults, the value must be between 50 and 100. To get the next page results, provide the pagination token from the GetOutcomesResult as part of your request. A null pagination token fetches the records from the beginning.
Evaluates an event against a detector version. If a version ID is not provided, the detector’s (ACTIVE) version is used.
The variable type.
Valid Values: AUTH_CODE | AVS | BILLING_ADDRESS_L1 | BILLING_ADDRESS_L2 | BILLING_CITY | BILLING_COUNTRY | BILLING_NAME | BILLING_PHONE | BILLING_STATE | BILLING_ZIP | CARD_BIN | CATEGORICAL | CURRENCY_CODE | EMAIL_ADDRESS | FINGERPRINT | FRAUD_LABEL | FREE_FORM_TEXT | IP_ADDRESS | NUMERIC | ORDER_ID | PAYMENT_TYPE | PHONE_NUMBER | PRICE | PRODUCT_CATEGORY | SHIPPING_ADDRESS_L1 | SHIPPING_ADDRESS_L2 | SHIPPING_CITY | SHIPPING_COUNTRY | SHIPPING_NAME | SHIPPING_PHONE | SHIPPING_STATE | SHIPPING_ZIP | USERAGENT | SHIPPING_ZIP | USERAGENT
The variable type. For more information see Variable types.
Valid Values: AUTH_CODE | AVS | BILLING_ADDRESS_L1 | BILLING_ADDRESS_L2 | BILLING_CITY | BILLING_COUNTRY | BILLING_NAME | BILLING_PHONE | BILLING_STATE | BILLING_ZIP | CARD_BIN | CATEGORICAL | CURRENCY_CODE | EMAIL_ADDRESS | FINGERPRINT | FRAUD_LABEL | FREE_FORM_TEXT | IP_ADDRESS | NUMERIC | ORDER_ID | PAYMENT_TYPE | PHONE_NUMBER | PRICE | PRODUCT_CATEGORY | SHIPPING_ADDRESS_L1 | SHIPPING_ADDRESS_L2 | SHIPPING_CITY | SHIPPING_COUNTRY | SHIPPING_NAME | SHIPPING_PHONE | SHIPPING_STATE | SHIPPING_ZIP | USERAGENT | SHIPPING_ZIP | USERAGENT
The entity type details.
" }, - "EventAttributeMap":{ - "type":"map", - "key":{"shape":"attributeKey"}, - "value":{"shape":"attributeValue"} - }, "EventType":{ "type":"structure", "members":{ @@ -1491,8 +1469,8 @@ "shape":"ModelSource", "documentation":"The source of the model.
" }, - "role":{ - "shape":"Role", + "invokeModelEndpointRoleArn":{ + "shape":"string", "documentation":"The role used to invoke the model.
" }, "inputConfiguration":{ @@ -1724,7 +1702,7 @@ "documentation":"The detector ID.
" }, "detectorVersionId":{ - "shape":"string", + "shape":"wholeNumberVersionString", "documentation":"The detector version ID.
" }, "eventId":{ @@ -1988,52 +1966,6 @@ } } }, - "GetPredictionRequest":{ - "type":"structure", - "required":[ - "detectorId", - "eventId" - ], - "members":{ - "detectorId":{ - "shape":"string", - "documentation":"The detector ID.
" - }, - "detectorVersionId":{ - "shape":"string", - "documentation":"The detector version ID.
" - }, - "eventId":{ - "shape":"string", - "documentation":"The unique ID used to identify the event.
" - }, - "eventAttributes":{ - "shape":"EventAttributeMap", - "documentation":"Names of variables you defined in Amazon Fraud Detector to represent event data elements and their corresponding values for the event you are sending for evaluation.
" - }, - "externalModelEndpointDataBlobs":{ - "shape":"ExternalModelEndpointDataBlobMap", - "documentation":"The Amazon SageMaker model endpoint input data blobs.
" - } - } - }, - "GetPredictionResult":{ - "type":"structure", - "members":{ - "outcomes":{ - "shape":"ListOfStrings", - "documentation":"The prediction outcomes.
" - }, - "modelScores":{ - "shape":"ListOfModelScores", - "documentation":"The model scores for models used in the detector version.
" - }, - "ruleResults":{ - "shape":"ListOfRuleResults", - "documentation":"The rule results in the prediction.
" - } - } - }, "GetRulesRequest":{ "type":"structure", "required":["detectorId"], @@ -2462,16 +2394,8 @@ "ModelVersionStatus":{ "type":"string", "enum":[ - "TRAINING_IN_PROGRESS", - "TRAINING_COMPLETE", - "ACTIVATE_REQUESTED", - "ACTIVATE_IN_PROGRESS", "ACTIVE", - "INACTIVATE_IN_PROGRESS", - "INACTIVE", - "DELETE_REQUESTED", - "DELETE_IN_PROGRESS", - "ERROR" + "INACTIVE" ] }, "NameList":{ @@ -2618,7 +2542,7 @@ "required":[ "modelEndpoint", "modelSource", - "role", + "invokeModelEndpointRoleArn", "inputConfiguration", "outputConfiguration", "modelEndpointStatus" @@ -2636,8 +2560,8 @@ "shape":"ModelSource", "documentation":"The source of the model.
" }, - "role":{ - "shape":"Role", + "invokeModelEndpointRoleArn":{ + "shape":"string", "documentation":"The IAM role used to invoke the model endpoint.
" }, "inputConfiguration":{ @@ -2733,24 +2657,6 @@ "documentation":"An exception indicating the specified resource was not found.
", "exception":true }, - "Role":{ - "type":"structure", - "required":[ - "arn", - "name" - ], - "members":{ - "arn":{ - "shape":"string", - "documentation":"The role ARN.
" - }, - "name":{ - "shape":"string", - "documentation":"The role name.
" - } - }, - "documentation":"The role used to invoke external model endpoints.
" - }, "Rule":{ "type":"structure", "required":[ @@ -3270,7 +3176,7 @@ }, "variableType":{ "shape":"string", - "documentation":"The variable type.
" + "documentation":"The variable type. For more information see Variable types.
" } } }, @@ -3298,7 +3204,7 @@ }, "dataType":{ "shape":"DataType", - "documentation":"The data type of the variable.
" + "documentation":"The data type of the variable. For more information see Variable types.
" }, "dataSource":{ "shape":"DataSource", @@ -3356,7 +3262,7 @@ }, "variableType":{ "shape":"string", - "documentation":"The type of the variable.
Valid Values: AUTH_CODE | AVS | BILLING_ADDRESS_L1 | BILLING_ADDRESS_L2 | BILLING_CITY | BILLING_COUNTRY | BILLING_NAME | BILLING_PHONE | BILLING_STATE | BILLING_ZIP | CARD_BIN | CATEGORICAL | CURRENCY_CODE | EMAIL_ADDRESS | FINGERPRINT | FRAUD_LABEL | FREE_FORM_TEXT | IP_ADDRESS | NUMERIC | ORDER_ID | PAYMENT_TYPE | PHONE_NUMBER | PRICE | PRODUCT_CATEGORY | SHIPPING_ADDRESS_L1 | SHIPPING_ADDRESS_L2 | SHIPPING_CITY | SHIPPING_COUNTRY | SHIPPING_NAME | SHIPPING_PHONE | SHIPPING_STATE | SHIPPING_ZIP | USERAGENT | SHIPPING_ZIP | USERAGENT
The type of the variable. For more information see Variable types.
Valid Values: AUTH_CODE | AVS | BILLING_ADDRESS_L1 | BILLING_ADDRESS_L2 | BILLING_CITY | BILLING_COUNTRY | BILLING_NAME | BILLING_PHONE | BILLING_STATE | BILLING_ZIP | CARD_BIN | CATEGORICAL | CURRENCY_CODE | EMAIL_ADDRESS | FINGERPRINT | FRAUD_LABEL | FREE_FORM_TEXT | IP_ADDRESS | NUMERIC | ORDER_ID | PAYMENT_TYPE | PHONE_NUMBER | PRICE | PRODUCT_CATEGORY | SHIPPING_ADDRESS_L1 | SHIPPING_ADDRESS_L2 | SHIPPING_CITY | SHIPPING_COUNTRY | SHIPPING_NAME | SHIPPING_PHONE | SHIPPING_STATE | SHIPPING_ZIP | USERAGENT | SHIPPING_ZIP | USERAGENT
A variable in the list of variables for the batch create variable request.
" @@ -3377,17 +3283,6 @@ "max":100, "min":50 }, - "attributeKey":{ - "type":"string", - "max":64, - "min":1 - }, - "attributeValue":{ - "type":"string", - "max":256, - "min":1, - "sensitive":true - }, "blob":{"type":"blob"}, "contentType":{ "type":"string", @@ -3430,6 +3325,8 @@ "float":{"type":"float"}, "floatVersionString":{ "type":"string", + "max":7, + "min":3, "pattern":"^[1-9][0-9]{0,3}\\.[0-9]{1,2}$" }, "fraudDetectorArn":{ @@ -3548,6 +3445,8 @@ }, "wholeNumberVersionString":{ "type":"string", + "max":5, + "min":1, "pattern":"^([1-9][0-9]*)$" } }, From 252b6d7f32260553cc9b4a5c157dc6791e884a6f Mon Sep 17 00:00:00 2001 From: AWS <> Date: Fri, 24 Jul 2020 18:06:36 +0000 Subject: [PATCH 11/11] Release 2.13.61. Updated CHANGELOG.md, README.md and all pom.xml. --- .changes/2.13.61.json | 51 +++++++++++++++++++ ...ture-AWSElementalMediaPackage-ce03cb1.json | 5 -- ...ture-AWSKendraFrontendService-a938d0c.json | 5 -- .../feature-AWSMediaConnect-74bbe29.json | 5 -- .../feature-AmazonCloudWatch-2a2deee.json | 5 -- .../feature-AmazonFSx-9200a31.json | 5 -- .../feature-AmazonFraudDetector-7c81945.json | 5 -- .../feature-AmazonMQ-58085ea.json | 5 -- .../feature-AmazonMacie2-3d07eea.json | 5 -- ...eature-AmazonSageMakerService-6151fd1.json | 5 -- CHANGELOG.md | 37 ++++++++++++++ README.md | 8 +-- archetypes/archetype-lambda/pom.xml | 2 +- archetypes/pom.xml | 2 +- aws-sdk-java/pom.xml | 2 +- bom-internal/pom.xml | 2 +- bom/pom.xml | 2 +- bundle/pom.xml | 2 +- codegen-lite-maven-plugin/pom.xml | 2 +- codegen-lite/pom.xml | 2 +- codegen-maven-plugin/pom.xml | 2 +- codegen/pom.xml | 2 +- core/annotations/pom.xml | 2 +- core/arns/pom.xml | 2 +- core/auth/pom.xml | 2 +- core/aws-core/pom.xml | 2 +- core/metrics-spi/pom.xml | 2 +- core/pom.xml | 2 +- core/profiles/pom.xml | 2 +- core/protocols/aws-cbor-protocol/pom.xml | 2 +- core/protocols/aws-ion-protocol/pom.xml | 2 +- core/protocols/aws-json-protocol/pom.xml | 2 +- core/protocols/aws-query-protocol/pom.xml | 2 +- core/protocols/aws-xml-protocol/pom.xml | 2 +- core/protocols/pom.xml | 2 +- core/protocols/protocol-core/pom.xml | 2 +- core/regions/pom.xml | 2 +- core/sdk-core/pom.xml | 2 +- http-client-spi/pom.xml | 2 +- http-clients/apache-client/pom.xml | 2 +- http-clients/netty-nio-client/pom.xml | 2 +- http-clients/pom.xml | 2 +- http-clients/url-connection-client/pom.xml | 2 +- .../cloudwatch-metric-publisher/pom.xml | 2 +- metric-publishers/pom.xml | 2 +- pom.xml | 2 +- release-scripts/pom.xml | 2 +- services-custom/dynamodb-enhanced/pom.xml | 2 +- services-custom/pom.xml | 2 +- services/accessanalyzer/pom.xml | 2 +- services/acm/pom.xml | 2 +- services/acmpca/pom.xml | 2 +- services/alexaforbusiness/pom.xml | 2 +- services/amplify/pom.xml | 2 +- services/apigateway/pom.xml | 2 +- services/apigatewaymanagementapi/pom.xml | 2 +- services/apigatewayv2/pom.xml | 2 +- services/appconfig/pom.xml | 2 +- services/applicationautoscaling/pom.xml | 2 +- services/applicationdiscovery/pom.xml | 2 +- services/applicationinsights/pom.xml | 2 +- services/appmesh/pom.xml | 2 +- services/appstream/pom.xml | 2 +- services/appsync/pom.xml | 2 +- services/athena/pom.xml | 2 +- services/autoscaling/pom.xml | 2 +- services/autoscalingplans/pom.xml | 2 +- services/backup/pom.xml | 2 +- services/batch/pom.xml | 2 +- services/budgets/pom.xml | 2 +- services/chime/pom.xml | 2 +- services/cloud9/pom.xml | 2 +- services/clouddirectory/pom.xml | 2 +- services/cloudformation/pom.xml | 2 +- services/cloudfront/pom.xml | 2 +- services/cloudhsm/pom.xml | 2 +- services/cloudhsmv2/pom.xml | 2 +- services/cloudsearch/pom.xml | 2 +- services/cloudsearchdomain/pom.xml | 2 +- services/cloudtrail/pom.xml | 2 +- services/cloudwatch/pom.xml | 2 +- services/cloudwatchevents/pom.xml | 2 +- services/cloudwatchlogs/pom.xml | 2 +- services/codeartifact/pom.xml | 2 +- services/codebuild/pom.xml | 2 +- services/codecommit/pom.xml | 2 +- services/codedeploy/pom.xml | 2 +- services/codeguruprofiler/pom.xml | 2 +- services/codegurureviewer/pom.xml | 2 +- services/codepipeline/pom.xml | 2 +- services/codestar/pom.xml | 2 +- services/codestarconnections/pom.xml | 2 +- services/codestarnotifications/pom.xml | 2 +- services/cognitoidentity/pom.xml | 2 +- services/cognitoidentityprovider/pom.xml | 2 +- services/cognitosync/pom.xml | 2 +- services/comprehend/pom.xml | 2 +- services/comprehendmedical/pom.xml | 2 +- services/computeoptimizer/pom.xml | 2 +- services/config/pom.xml | 2 +- services/connect/pom.xml | 2 +- services/connectparticipant/pom.xml | 2 +- services/costandusagereport/pom.xml | 2 +- services/costexplorer/pom.xml | 2 +- services/databasemigration/pom.xml | 2 +- services/dataexchange/pom.xml | 2 +- services/datapipeline/pom.xml | 2 +- services/datasync/pom.xml | 2 +- services/dax/pom.xml | 2 +- services/detective/pom.xml | 2 +- services/devicefarm/pom.xml | 2 +- services/directconnect/pom.xml | 2 +- services/directory/pom.xml | 2 +- services/dlm/pom.xml | 2 +- services/docdb/pom.xml | 2 +- services/dynamodb/pom.xml | 2 +- services/ebs/pom.xml | 2 +- services/ec2/pom.xml | 2 +- services/ec2instanceconnect/pom.xml | 2 +- services/ecr/pom.xml | 2 +- services/ecs/pom.xml | 2 +- services/efs/pom.xml | 2 +- services/eks/pom.xml | 2 +- services/elasticache/pom.xml | 2 +- services/elasticbeanstalk/pom.xml | 2 +- services/elasticinference/pom.xml | 2 +- services/elasticloadbalancing/pom.xml | 2 +- services/elasticloadbalancingv2/pom.xml | 2 +- services/elasticsearch/pom.xml | 2 +- services/elastictranscoder/pom.xml | 2 +- services/emr/pom.xml | 2 +- services/eventbridge/pom.xml | 2 +- services/firehose/pom.xml | 2 +- services/fms/pom.xml | 2 +- services/forecast/pom.xml | 2 +- services/forecastquery/pom.xml | 2 +- services/frauddetector/pom.xml | 2 +- services/fsx/pom.xml | 2 +- services/gamelift/pom.xml | 2 +- services/glacier/pom.xml | 2 +- services/globalaccelerator/pom.xml | 2 +- services/glue/pom.xml | 2 +- services/greengrass/pom.xml | 2 +- services/groundstation/pom.xml | 2 +- services/guardduty/pom.xml | 2 +- services/health/pom.xml | 2 +- services/honeycode/pom.xml | 2 +- services/iam/pom.xml | 2 +- services/imagebuilder/pom.xml | 2 +- services/inspector/pom.xml | 2 +- services/iot/pom.xml | 2 +- services/iot1clickdevices/pom.xml | 2 +- services/iot1clickprojects/pom.xml | 2 +- services/iotanalytics/pom.xml | 2 +- services/iotdataplane/pom.xml | 2 +- services/iotevents/pom.xml | 2 +- services/ioteventsdata/pom.xml | 2 +- services/iotjobsdataplane/pom.xml | 2 +- services/iotsecuretunneling/pom.xml | 2 +- services/iotsitewise/pom.xml | 2 +- services/iotthingsgraph/pom.xml | 2 +- services/ivs/pom.xml | 2 +- services/kafka/pom.xml | 2 +- services/kendra/pom.xml | 2 +- services/kinesis/pom.xml | 2 +- services/kinesisanalytics/pom.xml | 2 +- services/kinesisanalyticsv2/pom.xml | 2 +- services/kinesisvideo/pom.xml | 2 +- services/kinesisvideoarchivedmedia/pom.xml | 2 +- services/kinesisvideomedia/pom.xml | 2 +- services/kinesisvideosignaling/pom.xml | 2 +- services/kms/pom.xml | 2 +- services/lakeformation/pom.xml | 2 +- services/lambda/pom.xml | 2 +- services/lexmodelbuilding/pom.xml | 2 +- services/lexruntime/pom.xml | 2 +- services/licensemanager/pom.xml | 2 +- services/lightsail/pom.xml | 2 +- services/machinelearning/pom.xml | 2 +- services/macie/pom.xml | 2 +- services/macie2/pom.xml | 2 +- services/managedblockchain/pom.xml | 2 +- services/marketplacecatalog/pom.xml | 2 +- services/marketplacecommerceanalytics/pom.xml | 2 +- services/marketplaceentitlement/pom.xml | 2 +- services/marketplacemetering/pom.xml | 2 +- services/mediaconnect/pom.xml | 2 +- services/mediaconvert/pom.xml | 2 +- services/medialive/pom.xml | 2 +- services/mediapackage/pom.xml | 2 +- services/mediapackagevod/pom.xml | 2 +- services/mediastore/pom.xml | 2 +- services/mediastoredata/pom.xml | 2 +- services/mediatailor/pom.xml | 2 +- services/migrationhub/pom.xml | 2 +- services/migrationhubconfig/pom.xml | 2 +- services/mobile/pom.xml | 2 +- services/mq/pom.xml | 2 +- services/mturk/pom.xml | 2 +- services/neptune/pom.xml | 2 +- services/networkmanager/pom.xml | 2 +- services/opsworks/pom.xml | 2 +- services/opsworkscm/pom.xml | 2 +- services/organizations/pom.xml | 2 +- services/outposts/pom.xml | 2 +- services/personalize/pom.xml | 2 +- services/personalizeevents/pom.xml | 2 +- services/personalizeruntime/pom.xml | 2 +- services/pi/pom.xml | 2 +- services/pinpoint/pom.xml | 2 +- services/pinpointemail/pom.xml | 2 +- services/pinpointsmsvoice/pom.xml | 2 +- services/polly/pom.xml | 2 +- services/pom.xml | 2 +- services/pricing/pom.xml | 2 +- services/qldb/pom.xml | 2 +- services/qldbsession/pom.xml | 2 +- services/quicksight/pom.xml | 2 +- services/ram/pom.xml | 2 +- services/rds/pom.xml | 2 +- services/rdsdata/pom.xml | 2 +- services/redshift/pom.xml | 2 +- services/rekognition/pom.xml | 2 +- services/resourcegroups/pom.xml | 2 +- services/resourcegroupstaggingapi/pom.xml | 2 +- services/robomaker/pom.xml | 2 +- services/route53/pom.xml | 2 +- services/route53domains/pom.xml | 2 +- services/route53resolver/pom.xml | 2 +- services/s3/pom.xml | 2 +- services/s3control/pom.xml | 2 +- services/sagemaker/pom.xml | 2 +- services/sagemakera2iruntime/pom.xml | 2 +- services/sagemakerruntime/pom.xml | 2 +- services/savingsplans/pom.xml | 2 +- services/schemas/pom.xml | 2 +- services/secretsmanager/pom.xml | 2 +- services/securityhub/pom.xml | 2 +- .../serverlessapplicationrepository/pom.xml | 2 +- services/servicecatalog/pom.xml | 2 +- services/servicediscovery/pom.xml | 2 +- services/servicequotas/pom.xml | 2 +- services/ses/pom.xml | 2 +- services/sesv2/pom.xml | 2 +- services/sfn/pom.xml | 2 +- services/shield/pom.xml | 2 +- services/signer/pom.xml | 2 +- services/sms/pom.xml | 2 +- services/snowball/pom.xml | 2 +- services/sns/pom.xml | 2 +- services/sqs/pom.xml | 2 +- services/ssm/pom.xml | 2 +- services/sso/pom.xml | 2 +- services/ssooidc/pom.xml | 2 +- services/storagegateway/pom.xml | 2 +- services/sts/pom.xml | 2 +- services/support/pom.xml | 2 +- services/swf/pom.xml | 2 +- services/synthetics/pom.xml | 2 +- services/textract/pom.xml | 2 +- services/transcribe/pom.xml | 2 +- services/transcribestreaming/pom.xml | 2 +- services/transfer/pom.xml | 2 +- services/translate/pom.xml | 2 +- services/waf/pom.xml | 2 +- services/wafv2/pom.xml | 2 +- services/workdocs/pom.xml | 2 +- services/worklink/pom.xml | 2 +- services/workmail/pom.xml | 2 +- services/workmailmessageflow/pom.xml | 2 +- services/workspaces/pom.xml | 2 +- services/xray/pom.xml | 2 +- test/codegen-generated-classes-test/pom.xml | 2 +- test/http-client-tests/pom.xml | 2 +- test/module-path-tests/pom.xml | 2 +- test/protocol-tests-core/pom.xml | 2 +- test/protocol-tests/pom.xml | 2 +- test/sdk-benchmarks/pom.xml | 2 +- test/service-test-utils/pom.xml | 2 +- test/stability-tests/pom.xml | 2 +- test/test-utils/pom.xml | 2 +- test/tests-coverage-reporting/pom.xml | 2 +- utils/pom.xml | 2 +- 283 files changed, 363 insertions(+), 320 deletions(-) create mode 100644 .changes/2.13.61.json delete mode 100644 .changes/next-release/feature-AWSElementalMediaPackage-ce03cb1.json delete mode 100644 .changes/next-release/feature-AWSKendraFrontendService-a938d0c.json delete mode 100644 .changes/next-release/feature-AWSMediaConnect-74bbe29.json delete mode 100644 .changes/next-release/feature-AmazonCloudWatch-2a2deee.json delete mode 100644 .changes/next-release/feature-AmazonFSx-9200a31.json delete mode 100644 .changes/next-release/feature-AmazonFraudDetector-7c81945.json delete mode 100644 .changes/next-release/feature-AmazonMQ-58085ea.json delete mode 100644 .changes/next-release/feature-AmazonMacie2-3d07eea.json delete mode 100644 .changes/next-release/feature-AmazonSageMakerService-6151fd1.json diff --git a/.changes/2.13.61.json b/.changes/2.13.61.json new file mode 100644 index 000000000000..cc8dcde50247 --- /dev/null +++ b/.changes/2.13.61.json @@ -0,0 +1,51 @@ +{ + "version": "2.13.61", + "date": "2020-07-24", + "entries": [ + { + "type": "feature", + "category": "Amazon Fraud Detector", + "description": "GetPrediction has been replaced with GetEventPrediction. PutExternalModel has been simplified to accept a role ARN." + }, + { + "type": "feature", + "category": "AWSKendraFrontendService", + "description": "Amazon Kendra now supports sorting query results based on document attributes. Amazon Kendra also introduced an option to enclose table and column names with double quotes for database data sources." + }, + { + "type": "feature", + "category": "AWS Elemental MediaPackage", + "description": "The release adds daterange as a new ad marker option. This option enables MediaPackage to insert EXT-X-DATERANGE tags in HLS and CMAF manifests. The EXT-X-DATERANGE tag is used to signal ad and program transition events." + }, + { + "type": "feature", + "category": "AmazonMQ", + "description": "Amazon MQ now supports LDAP (Lightweight Directory Access Protocol), providing authentication and authorization of Amazon MQ users via a customer designated LDAP server." + }, + { + "type": "feature", + "category": "Amazon Macie 2", + "description": "This release of the Amazon Macie API introduces additional criteria for sorting and filtering query results for account quotas and usage statistics." + }, + { + "type": "feature", + "category": "Amazon SageMaker Service", + "description": "Sagemaker Ground Truth:Added support for OIDC (OpenID Connect) to authenticate workers via their own identity provider instead of through Amazon Cognito. This release adds new APIs (CreateWorkforce, DeleteWorkforce, and ListWorkforces) to SageMaker Ground Truth service. Sagemaker Neo: Added support for detailed target device description by using TargetPlatform fields - OS, architecture, and accelerator. Added support for additional compilation parameters by using JSON field CompilerOptions. Sagemaker Search: SageMaker Search supports transform job details in trial components." + }, + { + "type": "feature", + "category": "Amazon CloudWatch", + "description": "AWS CloudWatch ListMetrics now supports an optional parameter (RecentlyActive) to filter results by only metrics that have received new datapoints in the past 3 hours. This enables more targeted metric data retrieval through the Get APIs" + }, + { + "type": "feature", + "category": "Amazon FSx", + "description": "Documentation update for FSx for Lustre" + }, + { + "type": "feature", + "category": "AWS MediaConnect", + "description": "You can now disable an entitlement to stop streaming content to the subscriber's flow temporarily. When you are ready to allow content to start streaming to the subscriber's flow again, you can enable the entitlement." + } + ] +} \ No newline at end of file diff --git a/.changes/next-release/feature-AWSElementalMediaPackage-ce03cb1.json b/.changes/next-release/feature-AWSElementalMediaPackage-ce03cb1.json deleted file mode 100644 index 0d430479e242..000000000000 --- a/.changes/next-release/feature-AWSElementalMediaPackage-ce03cb1.json +++ /dev/null @@ -1,5 +0,0 @@ -{ - "type": "feature", - "category": "AWS Elemental MediaPackage", - "description": "The release adds daterange as a new ad marker option. This option enables MediaPackage to insert EXT-X-DATERANGE tags in HLS and CMAF manifests. The EXT-X-DATERANGE tag is used to signal ad and program transition events." -} diff --git a/.changes/next-release/feature-AWSKendraFrontendService-a938d0c.json b/.changes/next-release/feature-AWSKendraFrontendService-a938d0c.json deleted file mode 100644 index 367178402e83..000000000000 --- a/.changes/next-release/feature-AWSKendraFrontendService-a938d0c.json +++ /dev/null @@ -1,5 +0,0 @@ -{ - "type": "feature", - "category": "AWSKendraFrontendService", - "description": "Amazon Kendra now supports sorting query results based on document attributes. Amazon Kendra also introduced an option to enclose table and column names with double quotes for database data sources." -} diff --git a/.changes/next-release/feature-AWSMediaConnect-74bbe29.json b/.changes/next-release/feature-AWSMediaConnect-74bbe29.json deleted file mode 100644 index 790e494736f8..000000000000 --- a/.changes/next-release/feature-AWSMediaConnect-74bbe29.json +++ /dev/null @@ -1,5 +0,0 @@ -{ - "type": "feature", - "category": "AWS MediaConnect", - "description": "You can now disable an entitlement to stop streaming content to the subscriber's flow temporarily. When you are ready to allow content to start streaming to the subscriber's flow again, you can enable the entitlement." -} diff --git a/.changes/next-release/feature-AmazonCloudWatch-2a2deee.json b/.changes/next-release/feature-AmazonCloudWatch-2a2deee.json deleted file mode 100644 index 13b1b25112f4..000000000000 --- a/.changes/next-release/feature-AmazonCloudWatch-2a2deee.json +++ /dev/null @@ -1,5 +0,0 @@ -{ - "type": "feature", - "category": "Amazon CloudWatch", - "description": "AWS CloudWatch ListMetrics now supports an optional parameter (RecentlyActive) to filter results by only metrics that have received new datapoints in the past 3 hours. This enables more targeted metric data retrieval through the Get APIs" -} diff --git a/.changes/next-release/feature-AmazonFSx-9200a31.json b/.changes/next-release/feature-AmazonFSx-9200a31.json deleted file mode 100644 index 42319c87691e..000000000000 --- a/.changes/next-release/feature-AmazonFSx-9200a31.json +++ /dev/null @@ -1,5 +0,0 @@ -{ - "type": "feature", - "category": "Amazon FSx", - "description": "Documentation update for FSx for Lustre" -} diff --git a/.changes/next-release/feature-AmazonFraudDetector-7c81945.json b/.changes/next-release/feature-AmazonFraudDetector-7c81945.json deleted file mode 100644 index 26bac39b75c3..000000000000 --- a/.changes/next-release/feature-AmazonFraudDetector-7c81945.json +++ /dev/null @@ -1,5 +0,0 @@ -{ - "type": "feature", - "category": "Amazon Fraud Detector", - "description": "GetPrediction has been replaced with GetEventPrediction. PutExternalModel has been simplified to accept a role ARN." -} diff --git a/.changes/next-release/feature-AmazonMQ-58085ea.json b/.changes/next-release/feature-AmazonMQ-58085ea.json deleted file mode 100644 index f12821fd2e7e..000000000000 --- a/.changes/next-release/feature-AmazonMQ-58085ea.json +++ /dev/null @@ -1,5 +0,0 @@ -{ - "type": "feature", - "category": "AmazonMQ", - "description": "Amazon MQ now supports LDAP (Lightweight Directory Access Protocol), providing authentication and authorization of Amazon MQ users via a customer designated LDAP server." -} diff --git a/.changes/next-release/feature-AmazonMacie2-3d07eea.json b/.changes/next-release/feature-AmazonMacie2-3d07eea.json deleted file mode 100644 index 6187229e06f0..000000000000 --- a/.changes/next-release/feature-AmazonMacie2-3d07eea.json +++ /dev/null @@ -1,5 +0,0 @@ -{ - "type": "feature", - "category": "Amazon Macie 2", - "description": "This release of the Amazon Macie API introduces additional criteria for sorting and filtering query results for account quotas and usage statistics." -} diff --git a/.changes/next-release/feature-AmazonSageMakerService-6151fd1.json b/.changes/next-release/feature-AmazonSageMakerService-6151fd1.json deleted file mode 100644 index ed6daf6b629f..000000000000 --- a/.changes/next-release/feature-AmazonSageMakerService-6151fd1.json +++ /dev/null @@ -1,5 +0,0 @@ -{ - "type": "feature", - "category": "Amazon SageMaker Service", - "description": "Sagemaker Ground Truth:Added support for OIDC (OpenID Connect) to authenticate workers via their own identity provider instead of through Amazon Cognito. This release adds new APIs (CreateWorkforce, DeleteWorkforce, and ListWorkforces) to SageMaker Ground Truth service. Sagemaker Neo: Added support for detailed target device description by using TargetPlatform fields - OS, architecture, and accelerator. Added support for additional compilation parameters by using JSON field CompilerOptions. Sagemaker Search: SageMaker Search supports transform job details in trial components." -} diff --git a/CHANGELOG.md b/CHANGELOG.md index 11976c49650a..c07e2bdd8841 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,3 +1,40 @@ +# __2.13.61__ __2020-07-24__ +## __AWS Elemental MediaPackage__ + - ### Features + - The release adds daterange as a new ad marker option. This option enables MediaPackage to insert EXT-X-DATERANGE tags in HLS and CMAF manifests. The EXT-X-DATERANGE tag is used to signal ad and program transition events. + +## __AWS MediaConnect__ + - ### Features + - You can now disable an entitlement to stop streaming content to the subscriber's flow temporarily. When you are ready to allow content to start streaming to the subscriber's flow again, you can enable the entitlement. + +## __AWSKendraFrontendService__ + - ### Features + - Amazon Kendra now supports sorting query results based on document attributes. Amazon Kendra also introduced an option to enclose table and column names with double quotes for database data sources. + +## __Amazon CloudWatch__ + - ### Features + - AWS CloudWatch ListMetrics now supports an optional parameter (RecentlyActive) to filter results by only metrics that have received new datapoints in the past 3 hours. This enables more targeted metric data retrieval through the Get APIs + +## __Amazon FSx__ + - ### Features + - Documentation update for FSx for Lustre + +## __Amazon Fraud Detector__ + - ### Features + - GetPrediction has been replaced with GetEventPrediction. PutExternalModel has been simplified to accept a role ARN. + +## __Amazon Macie 2__ + - ### Features + - This release of the Amazon Macie API introduces additional criteria for sorting and filtering query results for account quotas and usage statistics. + +## __Amazon SageMaker Service__ + - ### Features + - Sagemaker Ground Truth:Added support for OIDC (OpenID Connect) to authenticate workers via their own identity provider instead of through Amazon Cognito. This release adds new APIs (CreateWorkforce, DeleteWorkforce, and ListWorkforces) to SageMaker Ground Truth service. Sagemaker Neo: Added support for detailed target device description by using TargetPlatform fields - OS, architecture, and accelerator. Added support for additional compilation parameters by using JSON field CompilerOptions. Sagemaker Search: SageMaker Search supports transform job details in trial components. + +## __AmazonMQ__ + - ### Features + - Amazon MQ now supports LDAP (Lightweight Directory Access Protocol), providing authentication and authorization of Amazon MQ users via a customer designated LDAP server. + # __2.13.60__ __2020-07-23__ ## __AWS Config__ - ### Features diff --git a/README.md b/README.md index 4c51fcb9b401..dfae9570f9c5 100644 --- a/README.md +++ b/README.md @@ -49,7 +49,7 @@ To automatically manage module versions (currently all modules have the same ver