diff --git a/README.md b/README.md --- a/README.md +++ b/README.md @@ -8,7 +8,7 @@ ## Version -`1.5.0` +`1.6.0` ## Description diff --git a/amazonka-ml.cabal b/amazonka-ml.cabal --- a/amazonka-ml.cabal +++ b/amazonka-ml.cabal @@ -1,5 +1,5 @@ name: amazonka-ml -version: 1.5.0 +version: 1.6.0 synopsis: Amazon Machine Learning SDK. homepage: https://github.com/brendanhay/amazonka bug-reports: https://github.com/brendanhay/amazonka/issues @@ -7,7 +7,7 @@ license-file: LICENSE author: Brendan Hay maintainer: Brendan Hay -copyright: Copyright (c) 2013-2017 Brendan Hay +copyright: Copyright (c) 2013-2018 Brendan Hay category: Network, AWS, Cloud, Distributed Computing build-type: Simple cabal-version: >= 1.10 @@ -81,7 +81,7 @@ , Network.AWS.MachineLearning.Types.Sum build-depends: - amazonka-core == 1.5.0.* + amazonka-core == 1.6.0.* , base >= 4.7 && < 5 test-suite amazonka-ml-test @@ -101,8 +101,8 @@ , Test.AWS.MachineLearning.Internal build-depends: - amazonka-core == 1.5.0.* - , amazonka-test == 1.5.0.* + amazonka-core == 1.6.0.* + , amazonka-test == 1.6.0.* , amazonka-ml , base , bytestring diff --git a/gen/Network/AWS/MachineLearning.hs b/gen/Network/AWS/MachineLearning.hs --- a/gen/Network/AWS/MachineLearning.hs +++ b/gen/Network/AWS/MachineLearning.hs @@ -5,7 +5,7 @@ -- | -- Module : Network.AWS.MachineLearning --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated diff --git a/gen/Network/AWS/MachineLearning/AddTags.hs b/gen/Network/AWS/MachineLearning/AddTags.hs --- a/gen/Network/AWS/MachineLearning/AddTags.hs +++ b/gen/Network/AWS/MachineLearning/AddTags.hs @@ -12,7 +12,7 @@ -- | -- Module : Network.AWS.MachineLearning.AddTags --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -70,23 +70,23 @@ -> AddTags addTags pResourceId_ pResourceType_ = AddTags' - { _atTags = mempty - , _atResourceId = pResourceId_ - , _atResourceType = pResourceType_ - } + { _atTags = mempty + , _atResourceId = pResourceId_ + , _atResourceType = pResourceType_ + } -- | The key-value pairs to use to create tags. If you specify a key without specifying a value, Amazon ML creates a tag with the specified key and a value of null. atTags :: Lens' AddTags [Tag] -atTags = lens _atTags (\ s a -> s{_atTags = a}) . _Coerce; +atTags = lens _atTags (\ s a -> s{_atTags = a}) . _Coerce -- | The ID of the ML object to tag. For example, @exampleModelId@ . atResourceId :: Lens' AddTags Text -atResourceId = lens _atResourceId (\ s a -> s{_atResourceId = a}); +atResourceId = lens _atResourceId (\ s a -> s{_atResourceId = a}) -- | The type of the ML object to tag. atResourceType :: Lens' AddTags TaggableResourceType -atResourceType = lens _atResourceType (\ s a -> s{_atResourceType = a}); +atResourceType = lens _atResourceType (\ s a -> s{_atResourceType = a}) instance AWSRequest AddTags where type Rs AddTags = AddTagsResponse @@ -151,22 +151,22 @@ -> AddTagsResponse addTagsResponse pResponseStatus_ = AddTagsResponse' - { _atrsResourceId = Nothing - , _atrsResourceType = Nothing - , _atrsResponseStatus = pResponseStatus_ - } + { _atrsResourceId = Nothing + , _atrsResourceType = Nothing + , _atrsResponseStatus = pResponseStatus_ + } -- | The ID of the ML object that was tagged. atrsResourceId :: Lens' AddTagsResponse (Maybe Text) -atrsResourceId = lens _atrsResourceId (\ s a -> s{_atrsResourceId = a}); +atrsResourceId = lens _atrsResourceId (\ s a -> s{_atrsResourceId = a}) -- | The type of the ML object that was tagged. atrsResourceType :: Lens' AddTagsResponse (Maybe TaggableResourceType) -atrsResourceType = lens _atrsResourceType (\ s a -> s{_atrsResourceType = a}); +atrsResourceType = lens _atrsResourceType (\ s a -> s{_atrsResourceType = a}) -- | -- | The response status code. atrsResponseStatus :: Lens' AddTagsResponse Int -atrsResponseStatus = lens _atrsResponseStatus (\ s a -> s{_atrsResponseStatus = a}); +atrsResponseStatus = lens _atrsResponseStatus (\ s a -> s{_atrsResponseStatus = a}) instance NFData AddTagsResponse where diff --git a/gen/Network/AWS/MachineLearning/CreateBatchPrediction.hs b/gen/Network/AWS/MachineLearning/CreateBatchPrediction.hs --- a/gen/Network/AWS/MachineLearning/CreateBatchPrediction.hs +++ b/gen/Network/AWS/MachineLearning/CreateBatchPrediction.hs @@ -12,7 +12,7 @@ -- | -- Module : Network.AWS.MachineLearning.CreateBatchPrediction --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -83,33 +83,33 @@ -> CreateBatchPrediction createBatchPrediction pBatchPredictionId_ pMLModelId_ pBatchPredictionDataSourceId_ pOutputURI_ = CreateBatchPrediction' - { _cbpBatchPredictionName = Nothing - , _cbpBatchPredictionId = pBatchPredictionId_ - , _cbpMLModelId = pMLModelId_ - , _cbpBatchPredictionDataSourceId = pBatchPredictionDataSourceId_ - , _cbpOutputURI = pOutputURI_ - } + { _cbpBatchPredictionName = Nothing + , _cbpBatchPredictionId = pBatchPredictionId_ + , _cbpMLModelId = pMLModelId_ + , _cbpBatchPredictionDataSourceId = pBatchPredictionDataSourceId_ + , _cbpOutputURI = pOutputURI_ + } -- | A user-supplied name or description of the @BatchPrediction@ . @BatchPredictionName@ can only use the UTF-8 character set. cbpBatchPredictionName :: Lens' CreateBatchPrediction (Maybe Text) -cbpBatchPredictionName = lens _cbpBatchPredictionName (\ s a -> s{_cbpBatchPredictionName = a}); +cbpBatchPredictionName = lens _cbpBatchPredictionName (\ s a -> s{_cbpBatchPredictionName = a}) -- | A user-supplied ID that uniquely identifies the @BatchPrediction@ . cbpBatchPredictionId :: Lens' CreateBatchPrediction Text -cbpBatchPredictionId = lens _cbpBatchPredictionId (\ s a -> s{_cbpBatchPredictionId = a}); +cbpBatchPredictionId = lens _cbpBatchPredictionId (\ s a -> s{_cbpBatchPredictionId = a}) -- | The ID of the @MLModel@ that will generate predictions for the group of observations. cbpMLModelId :: Lens' CreateBatchPrediction Text -cbpMLModelId = lens _cbpMLModelId (\ s a -> s{_cbpMLModelId = a}); +cbpMLModelId = lens _cbpMLModelId (\ s a -> s{_cbpMLModelId = a}) -- | The ID of the @DataSource@ that points to the group of observations to predict. cbpBatchPredictionDataSourceId :: Lens' CreateBatchPrediction Text -cbpBatchPredictionDataSourceId = lens _cbpBatchPredictionDataSourceId (\ s a -> s{_cbpBatchPredictionDataSourceId = a}); +cbpBatchPredictionDataSourceId = lens _cbpBatchPredictionDataSourceId (\ s a -> s{_cbpBatchPredictionDataSourceId = a}) -- | The location of an Amazon Simple Storage Service (Amazon S3) bucket or directory to store the batch prediction results. The following substrings are not allowed in the @s3 key@ portion of the @outputURI@ field: ':', '//', '/./', '/../'. Amazon ML needs permissions to store and retrieve the logs on your behalf. For information about how to set permissions, see the . cbpOutputURI :: Lens' CreateBatchPrediction Text -cbpOutputURI = lens _cbpOutputURI (\ s a -> s{_cbpOutputURI = a}); +cbpOutputURI = lens _cbpOutputURI (\ s a -> s{_cbpOutputURI = a}) instance AWSRequest CreateBatchPrediction where type Rs CreateBatchPrediction = @@ -179,15 +179,15 @@ -> CreateBatchPredictionResponse createBatchPredictionResponse pResponseStatus_ = CreateBatchPredictionResponse' - {_cbprsBatchPredictionId = Nothing, _cbprsResponseStatus = pResponseStatus_} + {_cbprsBatchPredictionId = Nothing, _cbprsResponseStatus = pResponseStatus_} -- | A user-supplied ID that uniquely identifies the @BatchPrediction@ . This value is identical to the value of the @BatchPredictionId@ in the request. cbprsBatchPredictionId :: Lens' CreateBatchPredictionResponse (Maybe Text) -cbprsBatchPredictionId = lens _cbprsBatchPredictionId (\ s a -> s{_cbprsBatchPredictionId = a}); +cbprsBatchPredictionId = lens _cbprsBatchPredictionId (\ s a -> s{_cbprsBatchPredictionId = a}) -- | -- | The response status code. cbprsResponseStatus :: Lens' CreateBatchPredictionResponse Int -cbprsResponseStatus = lens _cbprsResponseStatus (\ s a -> s{_cbprsResponseStatus = a}); +cbprsResponseStatus = lens _cbprsResponseStatus (\ s a -> s{_cbprsResponseStatus = a}) instance NFData CreateBatchPredictionResponse where diff --git a/gen/Network/AWS/MachineLearning/CreateDataSourceFromRDS.hs b/gen/Network/AWS/MachineLearning/CreateDataSourceFromRDS.hs --- a/gen/Network/AWS/MachineLearning/CreateDataSourceFromRDS.hs +++ b/gen/Network/AWS/MachineLearning/CreateDataSourceFromRDS.hs @@ -12,7 +12,7 @@ -- | -- Module : Network.AWS.MachineLearning.CreateDataSourceFromRDS --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -82,33 +82,33 @@ -> CreateDataSourceFromRDS createDataSourceFromRDS pDataSourceId_ pRDSData_ pRoleARN_ = CreateDataSourceFromRDS' - { _cdsfrdsDataSourceName = Nothing - , _cdsfrdsComputeStatistics = Nothing - , _cdsfrdsDataSourceId = pDataSourceId_ - , _cdsfrdsRDSData = pRDSData_ - , _cdsfrdsRoleARN = pRoleARN_ - } + { _cdsfrdsDataSourceName = Nothing + , _cdsfrdsComputeStatistics = Nothing + , _cdsfrdsDataSourceId = pDataSourceId_ + , _cdsfrdsRDSData = pRDSData_ + , _cdsfrdsRoleARN = pRoleARN_ + } -- | A user-supplied name or description of the @DataSource@ . cdsfrdsDataSourceName :: Lens' CreateDataSourceFromRDS (Maybe Text) -cdsfrdsDataSourceName = lens _cdsfrdsDataSourceName (\ s a -> s{_cdsfrdsDataSourceName = a}); +cdsfrdsDataSourceName = lens _cdsfrdsDataSourceName (\ s a -> s{_cdsfrdsDataSourceName = a}) -- | The compute statistics for a @DataSource@ . The statistics are generated from the observation data referenced by a @DataSource@ . Amazon ML uses the statistics internally during @MLModel@ training. This parameter must be set to @true@ if the DataSourceneeds to be used for @MLModel@ training. cdsfrdsComputeStatistics :: Lens' CreateDataSourceFromRDS (Maybe Bool) -cdsfrdsComputeStatistics = lens _cdsfrdsComputeStatistics (\ s a -> s{_cdsfrdsComputeStatistics = a}); +cdsfrdsComputeStatistics = lens _cdsfrdsComputeStatistics (\ s a -> s{_cdsfrdsComputeStatistics = a}) -- | A user-supplied ID that uniquely identifies the @DataSource@ . Typically, an Amazon Resource Number (ARN) becomes the ID for a @DataSource@ . cdsfrdsDataSourceId :: Lens' CreateDataSourceFromRDS Text -cdsfrdsDataSourceId = lens _cdsfrdsDataSourceId (\ s a -> s{_cdsfrdsDataSourceId = a}); +cdsfrdsDataSourceId = lens _cdsfrdsDataSourceId (\ s a -> s{_cdsfrdsDataSourceId = a}) -- | The data specification of an Amazon RDS @DataSource@ : * DatabaseInformation - * @DatabaseName@ - The name of the Amazon RDS database. * @InstanceIdentifier @ - A unique identifier for the Amazon RDS database instance. * DatabaseCredentials - AWS Identity and Access Management (IAM) credentials that are used to connect to the Amazon RDS database. * ResourceRole - A role (DataPipelineDefaultResourceRole) assumed by an EC2 instance to carry out the copy task from Amazon RDS to Amazon Simple Storage Service (Amazon S3). For more information, see for data pipelines. * ServiceRole - A role (DataPipelineDefaultRole) assumed by the AWS Data Pipeline service to monitor the progress of the copy task from Amazon RDS to Amazon S3. For more information, see for data pipelines. * SecurityInfo - The security information to use to access an RDS DB instance. You need to set up appropriate ingress rules for the security entity IDs provided to allow access to the Amazon RDS instance. Specify a [@SubnetId@ , @SecurityGroupIds@ ] pair for a VPC-based RDS DB instance. * SelectSqlQuery - A query that is used to retrieve the observation data for the @Datasource@ . * S3StagingLocation - The Amazon S3 location for staging Amazon RDS data. The data retrieved from Amazon RDS using @SelectSqlQuery@ is stored in this location. * DataSchemaUri - The Amazon S3 location of the @DataSchema@ . * DataSchema - A JSON string representing the schema. This is not required if @DataSchemaUri@ is specified. * DataRearrangement - A JSON string that represents the splitting and rearrangement requirements for the @Datasource@ . Sample - @"{\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}"@ cdsfrdsRDSData :: Lens' CreateDataSourceFromRDS RDSDataSpec -cdsfrdsRDSData = lens _cdsfrdsRDSData (\ s a -> s{_cdsfrdsRDSData = a}); +cdsfrdsRDSData = lens _cdsfrdsRDSData (\ s a -> s{_cdsfrdsRDSData = a}) -- | The role that Amazon ML assumes on behalf of the user to create and activate a data pipeline in the user's account and copy data using the @SelectSqlQuery@ query from Amazon RDS to Amazon S3. cdsfrdsRoleARN :: Lens' CreateDataSourceFromRDS Text -cdsfrdsRoleARN = lens _cdsfrdsRoleARN (\ s a -> s{_cdsfrdsRoleARN = a}); +cdsfrdsRoleARN = lens _cdsfrdsRoleARN (\ s a -> s{_cdsfrdsRoleARN = a}) instance AWSRequest CreateDataSourceFromRDS where type Rs CreateDataSourceFromRDS = @@ -176,17 +176,17 @@ -> CreateDataSourceFromRDSResponse createDataSourceFromRDSResponse pResponseStatus_ = CreateDataSourceFromRDSResponse' - { _cdsfrdsrsDataSourceId = Nothing - , _cdsfrdsrsResponseStatus = pResponseStatus_ - } + { _cdsfrdsrsDataSourceId = Nothing + , _cdsfrdsrsResponseStatus = pResponseStatus_ + } -- | A user-supplied ID that uniquely identifies the datasource. This value should be identical to the value of the @DataSourceID@ in the request. cdsfrdsrsDataSourceId :: Lens' CreateDataSourceFromRDSResponse (Maybe Text) -cdsfrdsrsDataSourceId = lens _cdsfrdsrsDataSourceId (\ s a -> s{_cdsfrdsrsDataSourceId = a}); +cdsfrdsrsDataSourceId = lens _cdsfrdsrsDataSourceId (\ s a -> s{_cdsfrdsrsDataSourceId = a}) -- | -- | The response status code. cdsfrdsrsResponseStatus :: Lens' CreateDataSourceFromRDSResponse Int -cdsfrdsrsResponseStatus = lens _cdsfrdsrsResponseStatus (\ s a -> s{_cdsfrdsrsResponseStatus = a}); +cdsfrdsrsResponseStatus = lens _cdsfrdsrsResponseStatus (\ s a -> s{_cdsfrdsrsResponseStatus = a}) instance NFData CreateDataSourceFromRDSResponse where diff --git a/gen/Network/AWS/MachineLearning/CreateDataSourceFromRedshift.hs b/gen/Network/AWS/MachineLearning/CreateDataSourceFromRedshift.hs --- a/gen/Network/AWS/MachineLearning/CreateDataSourceFromRedshift.hs +++ b/gen/Network/AWS/MachineLearning/CreateDataSourceFromRedshift.hs @@ -12,7 +12,7 @@ -- | -- Module : Network.AWS.MachineLearning.CreateDataSourceFromRedshift --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -88,33 +88,33 @@ -> CreateDataSourceFromRedshift createDataSourceFromRedshift pDataSourceId_ pDataSpec_ pRoleARN_ = CreateDataSourceFromRedshift' - { _cdsfrDataSourceName = Nothing - , _cdsfrComputeStatistics = Nothing - , _cdsfrDataSourceId = pDataSourceId_ - , _cdsfrDataSpec = pDataSpec_ - , _cdsfrRoleARN = pRoleARN_ - } + { _cdsfrDataSourceName = Nothing + , _cdsfrComputeStatistics = Nothing + , _cdsfrDataSourceId = pDataSourceId_ + , _cdsfrDataSpec = pDataSpec_ + , _cdsfrRoleARN = pRoleARN_ + } -- | A user-supplied name or description of the @DataSource@ . cdsfrDataSourceName :: Lens' CreateDataSourceFromRedshift (Maybe Text) -cdsfrDataSourceName = lens _cdsfrDataSourceName (\ s a -> s{_cdsfrDataSourceName = a}); +cdsfrDataSourceName = lens _cdsfrDataSourceName (\ s a -> s{_cdsfrDataSourceName = a}) -- | The compute statistics for a @DataSource@ . The statistics are generated from the observation data referenced by a @DataSource@ . Amazon ML uses the statistics internally during @MLModel@ training. This parameter must be set to @true@ if the @DataSource@ needs to be used for @MLModel@ training. cdsfrComputeStatistics :: Lens' CreateDataSourceFromRedshift (Maybe Bool) -cdsfrComputeStatistics = lens _cdsfrComputeStatistics (\ s a -> s{_cdsfrComputeStatistics = a}); +cdsfrComputeStatistics = lens _cdsfrComputeStatistics (\ s a -> s{_cdsfrComputeStatistics = a}) -- | A user-supplied ID that uniquely identifies the @DataSource@ . cdsfrDataSourceId :: Lens' CreateDataSourceFromRedshift Text -cdsfrDataSourceId = lens _cdsfrDataSourceId (\ s a -> s{_cdsfrDataSourceId = a}); +cdsfrDataSourceId = lens _cdsfrDataSourceId (\ s a -> s{_cdsfrDataSourceId = a}) -- | The data specification of an Amazon Redshift @DataSource@ : * DatabaseInformation - * @DatabaseName@ - The name of the Amazon Redshift database. * @ClusterIdentifier@ - The unique ID for the Amazon Redshift cluster. * DatabaseCredentials - The AWS Identity and Access Management (IAM) credentials that are used to connect to the Amazon Redshift database. * SelectSqlQuery - The query that is used to retrieve the observation data for the @Datasource@ . * S3StagingLocation - The Amazon Simple Storage Service (Amazon S3) location for staging Amazon Redshift data. The data retrieved from Amazon Redshift using the @SelectSqlQuery@ query is stored in this location. * DataSchemaUri - The Amazon S3 location of the @DataSchema@ . * DataSchema - A JSON string representing the schema. This is not required if @DataSchemaUri@ is specified. * DataRearrangement - A JSON string that represents the splitting and rearrangement requirements for the @DataSource@ . Sample - @"{\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}"@ cdsfrDataSpec :: Lens' CreateDataSourceFromRedshift RedshiftDataSpec -cdsfrDataSpec = lens _cdsfrDataSpec (\ s a -> s{_cdsfrDataSpec = a}); +cdsfrDataSpec = lens _cdsfrDataSpec (\ s a -> s{_cdsfrDataSpec = a}) -- | A fully specified role Amazon Resource Name (ARN). Amazon ML assumes the role on behalf of the user to create the following: * A security group to allow Amazon ML to execute the @SelectSqlQuery@ query on an Amazon Redshift cluster * An Amazon S3 bucket policy to grant Amazon ML read/write permissions on the @S3StagingLocation@ cdsfrRoleARN :: Lens' CreateDataSourceFromRedshift Text -cdsfrRoleARN = lens _cdsfrRoleARN (\ s a -> s{_cdsfrRoleARN = a}); +cdsfrRoleARN = lens _cdsfrRoleARN (\ s a -> s{_cdsfrRoleARN = a}) instance AWSRequest CreateDataSourceFromRedshift where @@ -182,16 +182,16 @@ -> CreateDataSourceFromRedshiftResponse createDataSourceFromRedshiftResponse pResponseStatus_ = CreateDataSourceFromRedshiftResponse' - {_cdsfrrsDataSourceId = Nothing, _cdsfrrsResponseStatus = pResponseStatus_} + {_cdsfrrsDataSourceId = Nothing, _cdsfrrsResponseStatus = pResponseStatus_} -- | A user-supplied ID that uniquely identifies the datasource. This value should be identical to the value of the @DataSourceID@ in the request. cdsfrrsDataSourceId :: Lens' CreateDataSourceFromRedshiftResponse (Maybe Text) -cdsfrrsDataSourceId = lens _cdsfrrsDataSourceId (\ s a -> s{_cdsfrrsDataSourceId = a}); +cdsfrrsDataSourceId = lens _cdsfrrsDataSourceId (\ s a -> s{_cdsfrrsDataSourceId = a}) -- | -- | The response status code. cdsfrrsResponseStatus :: Lens' CreateDataSourceFromRedshiftResponse Int -cdsfrrsResponseStatus = lens _cdsfrrsResponseStatus (\ s a -> s{_cdsfrrsResponseStatus = a}); +cdsfrrsResponseStatus = lens _cdsfrrsResponseStatus (\ s a -> s{_cdsfrrsResponseStatus = a}) instance NFData CreateDataSourceFromRedshiftResponse where diff --git a/gen/Network/AWS/MachineLearning/CreateDataSourceFromS3.hs b/gen/Network/AWS/MachineLearning/CreateDataSourceFromS3.hs --- a/gen/Network/AWS/MachineLearning/CreateDataSourceFromS3.hs +++ b/gen/Network/AWS/MachineLearning/CreateDataSourceFromS3.hs @@ -12,7 +12,7 @@ -- | -- Module : Network.AWS.MachineLearning.CreateDataSourceFromS3 --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -81,28 +81,28 @@ -> CreateDataSourceFromS3 createDataSourceFromS3 pDataSourceId_ pDataSpec_ = CreateDataSourceFromS3' - { _cdsfsDataSourceName = Nothing - , _cdsfsComputeStatistics = Nothing - , _cdsfsDataSourceId = pDataSourceId_ - , _cdsfsDataSpec = pDataSpec_ - } + { _cdsfsDataSourceName = Nothing + , _cdsfsComputeStatistics = Nothing + , _cdsfsDataSourceId = pDataSourceId_ + , _cdsfsDataSpec = pDataSpec_ + } -- | A user-supplied name or description of the @DataSource@ . cdsfsDataSourceName :: Lens' CreateDataSourceFromS3 (Maybe Text) -cdsfsDataSourceName = lens _cdsfsDataSourceName (\ s a -> s{_cdsfsDataSourceName = a}); +cdsfsDataSourceName = lens _cdsfsDataSourceName (\ s a -> s{_cdsfsDataSourceName = a}) -- | The compute statistics for a @DataSource@ . The statistics are generated from the observation data referenced by a @DataSource@ . Amazon ML uses the statistics internally during @MLModel@ training. This parameter must be set to @true@ if the DataSourceneeds to be used for @MLModel@ training. cdsfsComputeStatistics :: Lens' CreateDataSourceFromS3 (Maybe Bool) -cdsfsComputeStatistics = lens _cdsfsComputeStatistics (\ s a -> s{_cdsfsComputeStatistics = a}); +cdsfsComputeStatistics = lens _cdsfsComputeStatistics (\ s a -> s{_cdsfsComputeStatistics = a}) -- | A user-supplied identifier that uniquely identifies the @DataSource@ . cdsfsDataSourceId :: Lens' CreateDataSourceFromS3 Text -cdsfsDataSourceId = lens _cdsfsDataSourceId (\ s a -> s{_cdsfsDataSourceId = a}); +cdsfsDataSourceId = lens _cdsfsDataSourceId (\ s a -> s{_cdsfsDataSourceId = a}) -- | The data specification of a @DataSource@ : * DataLocationS3 - The Amazon S3 location of the observation data. * DataSchemaLocationS3 - The Amazon S3 location of the @DataSchema@ . * DataSchema - A JSON string representing the schema. This is not required if @DataSchemaUri@ is specified. * DataRearrangement - A JSON string that represents the splitting and rearrangement requirements for the @Datasource@ . Sample - @"{\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}"@ cdsfsDataSpec :: Lens' CreateDataSourceFromS3 S3DataSpec -cdsfsDataSpec = lens _cdsfsDataSpec (\ s a -> s{_cdsfsDataSpec = a}); +cdsfsDataSpec = lens _cdsfsDataSpec (\ s a -> s{_cdsfsDataSpec = a}) instance AWSRequest CreateDataSourceFromS3 where type Rs CreateDataSourceFromS3 = @@ -168,15 +168,15 @@ -> CreateDataSourceFromS3Response createDataSourceFromS3Response pResponseStatus_ = CreateDataSourceFromS3Response' - {_cdsfsrsDataSourceId = Nothing, _cdsfsrsResponseStatus = pResponseStatus_} + {_cdsfsrsDataSourceId = Nothing, _cdsfsrsResponseStatus = pResponseStatus_} -- | A user-supplied ID that uniquely identifies the @DataSource@ . This value should be identical to the value of the @DataSourceID@ in the request. cdsfsrsDataSourceId :: Lens' CreateDataSourceFromS3Response (Maybe Text) -cdsfsrsDataSourceId = lens _cdsfsrsDataSourceId (\ s a -> s{_cdsfsrsDataSourceId = a}); +cdsfsrsDataSourceId = lens _cdsfsrsDataSourceId (\ s a -> s{_cdsfsrsDataSourceId = a}) -- | -- | The response status code. cdsfsrsResponseStatus :: Lens' CreateDataSourceFromS3Response Int -cdsfsrsResponseStatus = lens _cdsfsrsResponseStatus (\ s a -> s{_cdsfsrsResponseStatus = a}); +cdsfsrsResponseStatus = lens _cdsfsrsResponseStatus (\ s a -> s{_cdsfsrsResponseStatus = a}) instance NFData CreateDataSourceFromS3Response where diff --git a/gen/Network/AWS/MachineLearning/CreateEvaluation.hs b/gen/Network/AWS/MachineLearning/CreateEvaluation.hs --- a/gen/Network/AWS/MachineLearning/CreateEvaluation.hs +++ b/gen/Network/AWS/MachineLearning/CreateEvaluation.hs @@ -12,7 +12,7 @@ -- | -- Module : Network.AWS.MachineLearning.CreateEvaluation --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -78,28 +78,28 @@ -> CreateEvaluation createEvaluation pEvaluationId_ pMLModelId_ pEvaluationDataSourceId_ = CreateEvaluation' - { _ceEvaluationName = Nothing - , _ceEvaluationId = pEvaluationId_ - , _ceMLModelId = pMLModelId_ - , _ceEvaluationDataSourceId = pEvaluationDataSourceId_ - } + { _ceEvaluationName = Nothing + , _ceEvaluationId = pEvaluationId_ + , _ceMLModelId = pMLModelId_ + , _ceEvaluationDataSourceId = pEvaluationDataSourceId_ + } -- | A user-supplied name or description of the @Evaluation@ . ceEvaluationName :: Lens' CreateEvaluation (Maybe Text) -ceEvaluationName = lens _ceEvaluationName (\ s a -> s{_ceEvaluationName = a}); +ceEvaluationName = lens _ceEvaluationName (\ s a -> s{_ceEvaluationName = a}) -- | A user-supplied ID that uniquely identifies the @Evaluation@ . ceEvaluationId :: Lens' CreateEvaluation Text -ceEvaluationId = lens _ceEvaluationId (\ s a -> s{_ceEvaluationId = a}); +ceEvaluationId = lens _ceEvaluationId (\ s a -> s{_ceEvaluationId = a}) -- | The ID of the @MLModel@ to evaluate. The schema used in creating the @MLModel@ must match the schema of the @DataSource@ used in the @Evaluation@ . ceMLModelId :: Lens' CreateEvaluation Text -ceMLModelId = lens _ceMLModelId (\ s a -> s{_ceMLModelId = a}); +ceMLModelId = lens _ceMLModelId (\ s a -> s{_ceMLModelId = a}) -- | The ID of the @DataSource@ for the evaluation. The schema of the @DataSource@ must match the schema used to create the @MLModel@ . ceEvaluationDataSourceId :: Lens' CreateEvaluation Text -ceEvaluationDataSourceId = lens _ceEvaluationDataSourceId (\ s a -> s{_ceEvaluationDataSourceId = a}); +ceEvaluationDataSourceId = lens _ceEvaluationDataSourceId (\ s a -> s{_ceEvaluationDataSourceId = a}) instance AWSRequest CreateEvaluation where type Rs CreateEvaluation = CreateEvaluationResponse @@ -165,15 +165,15 @@ -> CreateEvaluationResponse createEvaluationResponse pResponseStatus_ = CreateEvaluationResponse' - {_cersEvaluationId = Nothing, _cersResponseStatus = pResponseStatus_} + {_cersEvaluationId = Nothing, _cersResponseStatus = pResponseStatus_} -- | The user-supplied ID that uniquely identifies the @Evaluation@ . This value should be identical to the value of the @EvaluationId@ in the request. cersEvaluationId :: Lens' CreateEvaluationResponse (Maybe Text) -cersEvaluationId = lens _cersEvaluationId (\ s a -> s{_cersEvaluationId = a}); +cersEvaluationId = lens _cersEvaluationId (\ s a -> s{_cersEvaluationId = a}) -- | -- | The response status code. cersResponseStatus :: Lens' CreateEvaluationResponse Int -cersResponseStatus = lens _cersResponseStatus (\ s a -> s{_cersResponseStatus = a}); +cersResponseStatus = lens _cersResponseStatus (\ s a -> s{_cersResponseStatus = a}) instance NFData CreateEvaluationResponse where diff --git a/gen/Network/AWS/MachineLearning/CreateMLModel.hs b/gen/Network/AWS/MachineLearning/CreateMLModel.hs --- a/gen/Network/AWS/MachineLearning/CreateMLModel.hs +++ b/gen/Network/AWS/MachineLearning/CreateMLModel.hs @@ -12,7 +12,7 @@ -- | -- Module : Network.AWS.MachineLearning.CreateMLModel --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -94,43 +94,43 @@ -> CreateMLModel createMLModel pMLModelId_ pMLModelType_ pTrainingDataSourceId_ = CreateMLModel' - { _cmlmRecipe = Nothing - , _cmlmRecipeURI = Nothing - , _cmlmMLModelName = Nothing - , _cmlmParameters = Nothing - , _cmlmMLModelId = pMLModelId_ - , _cmlmMLModelType = pMLModelType_ - , _cmlmTrainingDataSourceId = pTrainingDataSourceId_ - } + { _cmlmRecipe = Nothing + , _cmlmRecipeURI = Nothing + , _cmlmMLModelName = Nothing + , _cmlmParameters = Nothing + , _cmlmMLModelId = pMLModelId_ + , _cmlmMLModelType = pMLModelType_ + , _cmlmTrainingDataSourceId = pTrainingDataSourceId_ + } -- | The data recipe for creating the @MLModel@ . You must specify either the recipe or its URI. If you don't specify a recipe or its URI, Amazon ML creates a default. cmlmRecipe :: Lens' CreateMLModel (Maybe Text) -cmlmRecipe = lens _cmlmRecipe (\ s a -> s{_cmlmRecipe = a}); +cmlmRecipe = lens _cmlmRecipe (\ s a -> s{_cmlmRecipe = a}) -- | The Amazon Simple Storage Service (Amazon S3) location and file name that contains the @MLModel@ recipe. You must specify either the recipe or its URI. If you don't specify a recipe or its URI, Amazon ML creates a default. cmlmRecipeURI :: Lens' CreateMLModel (Maybe Text) -cmlmRecipeURI = lens _cmlmRecipeURI (\ s a -> s{_cmlmRecipeURI = a}); +cmlmRecipeURI = lens _cmlmRecipeURI (\ s a -> s{_cmlmRecipeURI = a}) -- | A user-supplied name or description of the @MLModel@ . cmlmMLModelName :: Lens' CreateMLModel (Maybe Text) -cmlmMLModelName = lens _cmlmMLModelName (\ s a -> s{_cmlmMLModelName = a}); +cmlmMLModelName = lens _cmlmMLModelName (\ s a -> s{_cmlmMLModelName = a}) -- | A list of the training parameters in the @MLModel@ . The list is implemented as a map of key-value pairs. The following is the current set of training parameters: * @sgd.maxMLModelSizeInBytes@ - The maximum allowed size of the model. Depending on the input data, the size of the model might affect its performance. The value is an integer that ranges from @100000@ to @2147483648@ . The default value is @33554432@ . * @sgd.maxPasses@ - The number of times that the training process traverses the observations to build the @MLModel@ . The value is an integer that ranges from @1@ to @10000@ . The default value is @10@ . * @sgd.shuffleType@ - Whether Amazon ML shuffles the training data. Shuffling the data improves a model's ability to find the optimal solution for a variety of data types. The valid values are @auto@ and @none@ . The default value is @none@ . We strongly recommend that you shuffle your data. * @sgd.l1RegularizationAmount@ - The coefficient regularization L1 norm. It controls overfitting the data by penalizing large coefficients. This tends to drive coefficients to zero, resulting in a sparse feature set. If you use this parameter, start by specifying a small value, such as @1.0E-08@ . The value is a double that ranges from @0@ to @MAX_DOUBLE@ . The default is to not use L1 normalization. This parameter can't be used when @L2@ is specified. Use this parameter sparingly. * @sgd.l2RegularizationAmount@ - The coefficient regularization L2 norm. It controls overfitting the data by penalizing large coefficients. This tends to drive coefficients to small, nonzero values. If you use this parameter, start by specifying a small value, such as @1.0E-08@ . The value is a double that ranges from @0@ to @MAX_DOUBLE@ . The default is to not use L2 normalization. This parameter can't be used when @L1@ is specified. Use this parameter sparingly. cmlmParameters :: Lens' CreateMLModel (HashMap Text Text) -cmlmParameters = lens _cmlmParameters (\ s a -> s{_cmlmParameters = a}) . _Default . _Map; +cmlmParameters = lens _cmlmParameters (\ s a -> s{_cmlmParameters = a}) . _Default . _Map -- | A user-supplied ID that uniquely identifies the @MLModel@ . cmlmMLModelId :: Lens' CreateMLModel Text -cmlmMLModelId = lens _cmlmMLModelId (\ s a -> s{_cmlmMLModelId = a}); +cmlmMLModelId = lens _cmlmMLModelId (\ s a -> s{_cmlmMLModelId = a}) -- | The category of supervised learning that this @MLModel@ will address. Choose from the following types: * Choose @REGRESSION@ if the @MLModel@ will be used to predict a numeric value. * Choose @BINARY@ if the @MLModel@ result has two possible values. * Choose @MULTICLASS@ if the @MLModel@ result has a limited number of values. For more information, see the . cmlmMLModelType :: Lens' CreateMLModel MLModelType -cmlmMLModelType = lens _cmlmMLModelType (\ s a -> s{_cmlmMLModelType = a}); +cmlmMLModelType = lens _cmlmMLModelType (\ s a -> s{_cmlmMLModelType = a}) -- | The @DataSource@ that points to the training data. cmlmTrainingDataSourceId :: Lens' CreateMLModel Text -cmlmTrainingDataSourceId = lens _cmlmTrainingDataSourceId (\ s a -> s{_cmlmTrainingDataSourceId = a}); +cmlmTrainingDataSourceId = lens _cmlmTrainingDataSourceId (\ s a -> s{_cmlmTrainingDataSourceId = a}) instance AWSRequest CreateMLModel where type Rs CreateMLModel = CreateMLModelResponse @@ -199,15 +199,15 @@ -> CreateMLModelResponse createMLModelResponse pResponseStatus_ = CreateMLModelResponse' - {_cmlmrsMLModelId = Nothing, _cmlmrsResponseStatus = pResponseStatus_} + {_cmlmrsMLModelId = Nothing, _cmlmrsResponseStatus = pResponseStatus_} -- | A user-supplied ID that uniquely identifies the @MLModel@ . This value should be identical to the value of the @MLModelId@ in the request. cmlmrsMLModelId :: Lens' CreateMLModelResponse (Maybe Text) -cmlmrsMLModelId = lens _cmlmrsMLModelId (\ s a -> s{_cmlmrsMLModelId = a}); +cmlmrsMLModelId = lens _cmlmrsMLModelId (\ s a -> s{_cmlmrsMLModelId = a}) -- | -- | The response status code. cmlmrsResponseStatus :: Lens' CreateMLModelResponse Int -cmlmrsResponseStatus = lens _cmlmrsResponseStatus (\ s a -> s{_cmlmrsResponseStatus = a}); +cmlmrsResponseStatus = lens _cmlmrsResponseStatus (\ s a -> s{_cmlmrsResponseStatus = a}) instance NFData CreateMLModelResponse where diff --git a/gen/Network/AWS/MachineLearning/CreateRealtimeEndpoint.hs b/gen/Network/AWS/MachineLearning/CreateRealtimeEndpoint.hs --- a/gen/Network/AWS/MachineLearning/CreateRealtimeEndpoint.hs +++ b/gen/Network/AWS/MachineLearning/CreateRealtimeEndpoint.hs @@ -12,7 +12,7 @@ -- | -- Module : Network.AWS.MachineLearning.CreateRealtimeEndpoint --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -65,7 +65,7 @@ -- | The ID assigned to the @MLModel@ during creation. creMLModelId :: Lens' CreateRealtimeEndpoint Text -creMLModelId = lens _creMLModelId (\ s a -> s{_creMLModelId = a}); +creMLModelId = lens _creMLModelId (\ s a -> s{_creMLModelId = a}) instance AWSRequest CreateRealtimeEndpoint where type Rs CreateRealtimeEndpoint = @@ -132,22 +132,22 @@ -> CreateRealtimeEndpointResponse createRealtimeEndpointResponse pResponseStatus_ = CreateRealtimeEndpointResponse' - { _crersRealtimeEndpointInfo = Nothing - , _crersMLModelId = Nothing - , _crersResponseStatus = pResponseStatus_ - } + { _crersRealtimeEndpointInfo = Nothing + , _crersMLModelId = Nothing + , _crersResponseStatus = pResponseStatus_ + } -- | The endpoint information of the @MLModel@ crersRealtimeEndpointInfo :: Lens' CreateRealtimeEndpointResponse (Maybe RealtimeEndpointInfo) -crersRealtimeEndpointInfo = lens _crersRealtimeEndpointInfo (\ s a -> s{_crersRealtimeEndpointInfo = a}); +crersRealtimeEndpointInfo = lens _crersRealtimeEndpointInfo (\ s a -> s{_crersRealtimeEndpointInfo = a}) -- | A user-supplied ID that uniquely identifies the @MLModel@ . This value should be identical to the value of the @MLModelId@ in the request. crersMLModelId :: Lens' CreateRealtimeEndpointResponse (Maybe Text) -crersMLModelId = lens _crersMLModelId (\ s a -> s{_crersMLModelId = a}); +crersMLModelId = lens _crersMLModelId (\ s a -> s{_crersMLModelId = a}) -- | -- | The response status code. crersResponseStatus :: Lens' CreateRealtimeEndpointResponse Int -crersResponseStatus = lens _crersResponseStatus (\ s a -> s{_crersResponseStatus = a}); +crersResponseStatus = lens _crersResponseStatus (\ s a -> s{_crersResponseStatus = a}) instance NFData CreateRealtimeEndpointResponse where diff --git a/gen/Network/AWS/MachineLearning/DeleteBatchPrediction.hs b/gen/Network/AWS/MachineLearning/DeleteBatchPrediction.hs --- a/gen/Network/AWS/MachineLearning/DeleteBatchPrediction.hs +++ b/gen/Network/AWS/MachineLearning/DeleteBatchPrediction.hs @@ -12,7 +12,7 @@ -- | -- Module : Network.AWS.MachineLearning.DeleteBatchPrediction --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -68,7 +68,7 @@ -- | A user-supplied ID that uniquely identifies the @BatchPrediction@ . dbpBatchPredictionId :: Lens' DeleteBatchPrediction Text -dbpBatchPredictionId = lens _dbpBatchPredictionId (\ s a -> s{_dbpBatchPredictionId = a}); +dbpBatchPredictionId = lens _dbpBatchPredictionId (\ s a -> s{_dbpBatchPredictionId = a}) instance AWSRequest DeleteBatchPrediction where type Rs DeleteBatchPrediction = @@ -132,15 +132,15 @@ -> DeleteBatchPredictionResponse deleteBatchPredictionResponse pResponseStatus_ = DeleteBatchPredictionResponse' - {_dbprsBatchPredictionId = Nothing, _dbprsResponseStatus = pResponseStatus_} + {_dbprsBatchPredictionId = Nothing, _dbprsResponseStatus = pResponseStatus_} -- | A user-supplied ID that uniquely identifies the @BatchPrediction@ . This value should be identical to the value of the @BatchPredictionID@ in the request. dbprsBatchPredictionId :: Lens' DeleteBatchPredictionResponse (Maybe Text) -dbprsBatchPredictionId = lens _dbprsBatchPredictionId (\ s a -> s{_dbprsBatchPredictionId = a}); +dbprsBatchPredictionId = lens _dbprsBatchPredictionId (\ s a -> s{_dbprsBatchPredictionId = a}) -- | -- | The response status code. dbprsResponseStatus :: Lens' DeleteBatchPredictionResponse Int -dbprsResponseStatus = lens _dbprsResponseStatus (\ s a -> s{_dbprsResponseStatus = a}); +dbprsResponseStatus = lens _dbprsResponseStatus (\ s a -> s{_dbprsResponseStatus = a}) instance NFData DeleteBatchPredictionResponse where diff --git a/gen/Network/AWS/MachineLearning/DeleteDataSource.hs b/gen/Network/AWS/MachineLearning/DeleteDataSource.hs --- a/gen/Network/AWS/MachineLearning/DeleteDataSource.hs +++ b/gen/Network/AWS/MachineLearning/DeleteDataSource.hs @@ -12,7 +12,7 @@ -- | -- Module : Network.AWS.MachineLearning.DeleteDataSource --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -68,7 +68,7 @@ -- | A user-supplied ID that uniquely identifies the @DataSource@ . ddsDataSourceId :: Lens' DeleteDataSource Text -ddsDataSourceId = lens _ddsDataSourceId (\ s a -> s{_ddsDataSourceId = a}); +ddsDataSourceId = lens _ddsDataSourceId (\ s a -> s{_ddsDataSourceId = a}) instance AWSRequest DeleteDataSource where type Rs DeleteDataSource = DeleteDataSourceResponse @@ -127,15 +127,15 @@ -> DeleteDataSourceResponse deleteDataSourceResponse pResponseStatus_ = DeleteDataSourceResponse' - {_ddsrsDataSourceId = Nothing, _ddsrsResponseStatus = pResponseStatus_} + {_ddsrsDataSourceId = Nothing, _ddsrsResponseStatus = pResponseStatus_} -- | A user-supplied ID that uniquely identifies the @DataSource@ . This value should be identical to the value of the @DataSourceID@ in the request. ddsrsDataSourceId :: Lens' DeleteDataSourceResponse (Maybe Text) -ddsrsDataSourceId = lens _ddsrsDataSourceId (\ s a -> s{_ddsrsDataSourceId = a}); +ddsrsDataSourceId = lens _ddsrsDataSourceId (\ s a -> s{_ddsrsDataSourceId = a}) -- | -- | The response status code. ddsrsResponseStatus :: Lens' DeleteDataSourceResponse Int -ddsrsResponseStatus = lens _ddsrsResponseStatus (\ s a -> s{_ddsrsResponseStatus = a}); +ddsrsResponseStatus = lens _ddsrsResponseStatus (\ s a -> s{_ddsrsResponseStatus = a}) instance NFData DeleteDataSourceResponse where diff --git a/gen/Network/AWS/MachineLearning/DeleteEvaluation.hs b/gen/Network/AWS/MachineLearning/DeleteEvaluation.hs --- a/gen/Network/AWS/MachineLearning/DeleteEvaluation.hs +++ b/gen/Network/AWS/MachineLearning/DeleteEvaluation.hs @@ -12,7 +12,7 @@ -- | -- Module : Network.AWS.MachineLearning.DeleteEvaluation --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -70,7 +70,7 @@ -- | A user-supplied ID that uniquely identifies the @Evaluation@ to delete. deEvaluationId :: Lens' DeleteEvaluation Text -deEvaluationId = lens _deEvaluationId (\ s a -> s{_deEvaluationId = a}); +deEvaluationId = lens _deEvaluationId (\ s a -> s{_deEvaluationId = a}) instance AWSRequest DeleteEvaluation where type Rs DeleteEvaluation = DeleteEvaluationResponse @@ -131,15 +131,15 @@ -> DeleteEvaluationResponse deleteEvaluationResponse pResponseStatus_ = DeleteEvaluationResponse' - {_dersEvaluationId = Nothing, _dersResponseStatus = pResponseStatus_} + {_dersEvaluationId = Nothing, _dersResponseStatus = pResponseStatus_} -- | A user-supplied ID that uniquely identifies the @Evaluation@ . This value should be identical to the value of the @EvaluationId@ in the request. dersEvaluationId :: Lens' DeleteEvaluationResponse (Maybe Text) -dersEvaluationId = lens _dersEvaluationId (\ s a -> s{_dersEvaluationId = a}); +dersEvaluationId = lens _dersEvaluationId (\ s a -> s{_dersEvaluationId = a}) -- | -- | The response status code. dersResponseStatus :: Lens' DeleteEvaluationResponse Int -dersResponseStatus = lens _dersResponseStatus (\ s a -> s{_dersResponseStatus = a}); +dersResponseStatus = lens _dersResponseStatus (\ s a -> s{_dersResponseStatus = a}) instance NFData DeleteEvaluationResponse where diff --git a/gen/Network/AWS/MachineLearning/DeleteMLModel.hs b/gen/Network/AWS/MachineLearning/DeleteMLModel.hs --- a/gen/Network/AWS/MachineLearning/DeleteMLModel.hs +++ b/gen/Network/AWS/MachineLearning/DeleteMLModel.hs @@ -12,7 +12,7 @@ -- | -- Module : Network.AWS.MachineLearning.DeleteMLModel --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -67,7 +67,7 @@ -- | A user-supplied ID that uniquely identifies the @MLModel@ . dmlmMLModelId :: Lens' DeleteMLModel Text -dmlmMLModelId = lens _dmlmMLModelId (\ s a -> s{_dmlmMLModelId = a}); +dmlmMLModelId = lens _dmlmMLModelId (\ s a -> s{_dmlmMLModelId = a}) instance AWSRequest DeleteMLModel where type Rs DeleteMLModel = DeleteMLModelResponse @@ -127,15 +127,15 @@ -> DeleteMLModelResponse deleteMLModelResponse pResponseStatus_ = DeleteMLModelResponse' - {_dmlmrsMLModelId = Nothing, _dmlmrsResponseStatus = pResponseStatus_} + {_dmlmrsMLModelId = Nothing, _dmlmrsResponseStatus = pResponseStatus_} -- | A user-supplied ID that uniquely identifies the @MLModel@ . This value should be identical to the value of the @MLModelID@ in the request. dmlmrsMLModelId :: Lens' DeleteMLModelResponse (Maybe Text) -dmlmrsMLModelId = lens _dmlmrsMLModelId (\ s a -> s{_dmlmrsMLModelId = a}); +dmlmrsMLModelId = lens _dmlmrsMLModelId (\ s a -> s{_dmlmrsMLModelId = a}) -- | -- | The response status code. dmlmrsResponseStatus :: Lens' DeleteMLModelResponse Int -dmlmrsResponseStatus = lens _dmlmrsResponseStatus (\ s a -> s{_dmlmrsResponseStatus = a}); +dmlmrsResponseStatus = lens _dmlmrsResponseStatus (\ s a -> s{_dmlmrsResponseStatus = a}) instance NFData DeleteMLModelResponse where diff --git a/gen/Network/AWS/MachineLearning/DeleteRealtimeEndpoint.hs b/gen/Network/AWS/MachineLearning/DeleteRealtimeEndpoint.hs --- a/gen/Network/AWS/MachineLearning/DeleteRealtimeEndpoint.hs +++ b/gen/Network/AWS/MachineLearning/DeleteRealtimeEndpoint.hs @@ -12,7 +12,7 @@ -- | -- Module : Network.AWS.MachineLearning.DeleteRealtimeEndpoint --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -65,7 +65,7 @@ -- | The ID assigned to the @MLModel@ during creation. dreMLModelId :: Lens' DeleteRealtimeEndpoint Text -dreMLModelId = lens _dreMLModelId (\ s a -> s{_dreMLModelId = a}); +dreMLModelId = lens _dreMLModelId (\ s a -> s{_dreMLModelId = a}) instance AWSRequest DeleteRealtimeEndpoint where type Rs DeleteRealtimeEndpoint = @@ -132,22 +132,22 @@ -> DeleteRealtimeEndpointResponse deleteRealtimeEndpointResponse pResponseStatus_ = DeleteRealtimeEndpointResponse' - { _drersRealtimeEndpointInfo = Nothing - , _drersMLModelId = Nothing - , _drersResponseStatus = pResponseStatus_ - } + { _drersRealtimeEndpointInfo = Nothing + , _drersMLModelId = Nothing + , _drersResponseStatus = pResponseStatus_ + } -- | The endpoint information of the @MLModel@ drersRealtimeEndpointInfo :: Lens' DeleteRealtimeEndpointResponse (Maybe RealtimeEndpointInfo) -drersRealtimeEndpointInfo = lens _drersRealtimeEndpointInfo (\ s a -> s{_drersRealtimeEndpointInfo = a}); +drersRealtimeEndpointInfo = lens _drersRealtimeEndpointInfo (\ s a -> s{_drersRealtimeEndpointInfo = a}) -- | A user-supplied ID that uniquely identifies the @MLModel@ . This value should be identical to the value of the @MLModelId@ in the request. drersMLModelId :: Lens' DeleteRealtimeEndpointResponse (Maybe Text) -drersMLModelId = lens _drersMLModelId (\ s a -> s{_drersMLModelId = a}); +drersMLModelId = lens _drersMLModelId (\ s a -> s{_drersMLModelId = a}) -- | -- | The response status code. drersResponseStatus :: Lens' DeleteRealtimeEndpointResponse Int -drersResponseStatus = lens _drersResponseStatus (\ s a -> s{_drersResponseStatus = a}); +drersResponseStatus = lens _drersResponseStatus (\ s a -> s{_drersResponseStatus = a}) instance NFData DeleteRealtimeEndpointResponse where diff --git a/gen/Network/AWS/MachineLearning/DeleteTags.hs b/gen/Network/AWS/MachineLearning/DeleteTags.hs --- a/gen/Network/AWS/MachineLearning/DeleteTags.hs +++ b/gen/Network/AWS/MachineLearning/DeleteTags.hs @@ -12,7 +12,7 @@ -- | -- Module : Network.AWS.MachineLearning.DeleteTags --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -72,23 +72,23 @@ -> DeleteTags deleteTags pResourceId_ pResourceType_ = DeleteTags' - { _dTagKeys = mempty - , _dResourceId = pResourceId_ - , _dResourceType = pResourceType_ - } + { _dTagKeys = mempty + , _dResourceId = pResourceId_ + , _dResourceType = pResourceType_ + } -- | One or more tags to delete. dTagKeys :: Lens' DeleteTags [Text] -dTagKeys = lens _dTagKeys (\ s a -> s{_dTagKeys = a}) . _Coerce; +dTagKeys = lens _dTagKeys (\ s a -> s{_dTagKeys = a}) . _Coerce -- | The ID of the tagged ML object. For example, @exampleModelId@ . dResourceId :: Lens' DeleteTags Text -dResourceId = lens _dResourceId (\ s a -> s{_dResourceId = a}); +dResourceId = lens _dResourceId (\ s a -> s{_dResourceId = a}) -- | The type of the tagged ML object. dResourceType :: Lens' DeleteTags TaggableResourceType -dResourceType = lens _dResourceType (\ s a -> s{_dResourceType = a}); +dResourceType = lens _dResourceType (\ s a -> s{_dResourceType = a}) instance AWSRequest DeleteTags where type Rs DeleteTags = DeleteTagsResponse @@ -153,22 +153,22 @@ -> DeleteTagsResponse deleteTagsResponse pResponseStatus_ = DeleteTagsResponse' - { _drsResourceId = Nothing - , _drsResourceType = Nothing - , _drsResponseStatus = pResponseStatus_ - } + { _drsResourceId = Nothing + , _drsResourceType = Nothing + , _drsResponseStatus = pResponseStatus_ + } -- | The ID of the ML object from which tags were deleted. drsResourceId :: Lens' DeleteTagsResponse (Maybe Text) -drsResourceId = lens _drsResourceId (\ s a -> s{_drsResourceId = a}); +drsResourceId = lens _drsResourceId (\ s a -> s{_drsResourceId = a}) -- | The type of the ML object from which tags were deleted. drsResourceType :: Lens' DeleteTagsResponse (Maybe TaggableResourceType) -drsResourceType = lens _drsResourceType (\ s a -> s{_drsResourceType = a}); +drsResourceType = lens _drsResourceType (\ s a -> s{_drsResourceType = a}) -- | -- | The response status code. drsResponseStatus :: Lens' DeleteTagsResponse Int -drsResponseStatus = lens _drsResponseStatus (\ s a -> s{_drsResponseStatus = a}); +drsResponseStatus = lens _drsResponseStatus (\ s a -> s{_drsResponseStatus = a}) instance NFData DeleteTagsResponse where diff --git a/gen/Network/AWS/MachineLearning/DescribeBatchPredictions.hs b/gen/Network/AWS/MachineLearning/DescribeBatchPredictions.hs --- a/gen/Network/AWS/MachineLearning/DescribeBatchPredictions.hs +++ b/gen/Network/AWS/MachineLearning/DescribeBatchPredictions.hs @@ -12,7 +12,7 @@ -- | -- Module : Network.AWS.MachineLearning.DescribeBatchPredictions --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -103,63 +103,63 @@ :: DescribeBatchPredictions describeBatchPredictions = DescribeBatchPredictions' - { _dbpEQ = Nothing - , _dbpGE = Nothing - , _dbpPrefix = Nothing - , _dbpGT = Nothing - , _dbpNE = Nothing - , _dbpNextToken = Nothing - , _dbpSortOrder = Nothing - , _dbpLimit = Nothing - , _dbpLT = Nothing - , _dbpFilterVariable = Nothing - , _dbpLE = Nothing - } + { _dbpEQ = Nothing + , _dbpGE = Nothing + , _dbpPrefix = Nothing + , _dbpGT = Nothing + , _dbpNE = Nothing + , _dbpNextToken = Nothing + , _dbpSortOrder = Nothing + , _dbpLimit = Nothing + , _dbpLT = Nothing + , _dbpFilterVariable = Nothing + , _dbpLE = Nothing + } -- | The equal to operator. The @BatchPrediction@ results will have @FilterVariable@ values that exactly match the value specified with @EQ@ . dbpEQ :: Lens' DescribeBatchPredictions (Maybe Text) -dbpEQ = lens _dbpEQ (\ s a -> s{_dbpEQ = a}); +dbpEQ = lens _dbpEQ (\ s a -> s{_dbpEQ = a}) -- | The greater than or equal to operator. The @BatchPrediction@ results will have @FilterVariable@ values that are greater than or equal to the value specified with @GE@ . dbpGE :: Lens' DescribeBatchPredictions (Maybe Text) -dbpGE = lens _dbpGE (\ s a -> s{_dbpGE = a}); +dbpGE = lens _dbpGE (\ s a -> s{_dbpGE = a}) -- | A string that is found at the beginning of a variable, such as @Name@ or @Id@ . For example, a @Batch Prediction@ operation could have the @Name@ @2014-09-09-HolidayGiftMailer@ . To search for this @BatchPrediction@ , select @Name@ for the @FilterVariable@ and any of the following strings for the @Prefix@ : * 2014-09 * 2014-09-09 * 2014-09-09-Holiday dbpPrefix :: Lens' DescribeBatchPredictions (Maybe Text) -dbpPrefix = lens _dbpPrefix (\ s a -> s{_dbpPrefix = a}); +dbpPrefix = lens _dbpPrefix (\ s a -> s{_dbpPrefix = a}) -- | The greater than operator. The @BatchPrediction@ results will have @FilterVariable@ values that are greater than the value specified with @GT@ . dbpGT :: Lens' DescribeBatchPredictions (Maybe Text) -dbpGT = lens _dbpGT (\ s a -> s{_dbpGT = a}); +dbpGT = lens _dbpGT (\ s a -> s{_dbpGT = a}) -- | The not equal to operator. The @BatchPrediction@ results will have @FilterVariable@ values not equal to the value specified with @NE@ . dbpNE :: Lens' DescribeBatchPredictions (Maybe Text) -dbpNE = lens _dbpNE (\ s a -> s{_dbpNE = a}); +dbpNE = lens _dbpNE (\ s a -> s{_dbpNE = a}) -- | An ID of the page in the paginated results. dbpNextToken :: Lens' DescribeBatchPredictions (Maybe Text) -dbpNextToken = lens _dbpNextToken (\ s a -> s{_dbpNextToken = a}); +dbpNextToken = lens _dbpNextToken (\ s a -> s{_dbpNextToken = a}) -- | A two-value parameter that determines the sequence of the resulting list of @MLModel@ s. * @asc@ - Arranges the list in ascending order (A-Z, 0-9). * @dsc@ - Arranges the list in descending order (Z-A, 9-0). Results are sorted by @FilterVariable@ . dbpSortOrder :: Lens' DescribeBatchPredictions (Maybe SortOrder) -dbpSortOrder = lens _dbpSortOrder (\ s a -> s{_dbpSortOrder = a}); +dbpSortOrder = lens _dbpSortOrder (\ s a -> s{_dbpSortOrder = a}) -- | The number of pages of information to include in the result. The range of acceptable values is @1@ through @100@ . The default value is @100@ . dbpLimit :: Lens' DescribeBatchPredictions (Maybe Natural) -dbpLimit = lens _dbpLimit (\ s a -> s{_dbpLimit = a}) . mapping _Nat; +dbpLimit = lens _dbpLimit (\ s a -> s{_dbpLimit = a}) . mapping _Nat -- | The less than operator. The @BatchPrediction@ results will have @FilterVariable@ values that are less than the value specified with @LT@ . dbpLT :: Lens' DescribeBatchPredictions (Maybe Text) -dbpLT = lens _dbpLT (\ s a -> s{_dbpLT = a}); +dbpLT = lens _dbpLT (\ s a -> s{_dbpLT = a}) -- | Use one of the following variables to filter a list of @BatchPrediction@ : * @CreatedAt@ - Sets the search criteria to the @BatchPrediction@ creation date. * @Status@ - Sets the search criteria to the @BatchPrediction@ status. * @Name@ - Sets the search criteria to the contents of the @BatchPrediction@ ____ @Name@ . * @IAMUser@ - Sets the search criteria to the user account that invoked the @BatchPrediction@ creation. * @MLModelId@ - Sets the search criteria to the @MLModel@ used in the @BatchPrediction@ . * @DataSourceId@ - Sets the search criteria to the @DataSource@ used in the @BatchPrediction@ . * @DataURI@ - Sets the search criteria to the data file(s) used in the @BatchPrediction@ . The URL can identify either a file or an Amazon Simple Storage Solution (Amazon S3) bucket or directory. dbpFilterVariable :: Lens' DescribeBatchPredictions (Maybe BatchPredictionFilterVariable) -dbpFilterVariable = lens _dbpFilterVariable (\ s a -> s{_dbpFilterVariable = a}); +dbpFilterVariable = lens _dbpFilterVariable (\ s a -> s{_dbpFilterVariable = a}) -- | The less than or equal to operator. The @BatchPrediction@ results will have @FilterVariable@ values that are less than or equal to the value specified with @LE@ . dbpLE :: Lens' DescribeBatchPredictions (Maybe Text) -dbpLE = lens _dbpLE (\ s a -> s{_dbpLE = a}); +dbpLE = lens _dbpLE (\ s a -> s{_dbpLE = a}) instance AWSPager DescribeBatchPredictions where page rq rs @@ -238,23 +238,23 @@ -> DescribeBatchPredictionsResponse describeBatchPredictionsResponse pResponseStatus_ = DescribeBatchPredictionsResponse' - { _dbpsrsResults = Nothing - , _dbpsrsNextToken = Nothing - , _dbpsrsResponseStatus = pResponseStatus_ - } + { _dbpsrsResults = Nothing + , _dbpsrsNextToken = Nothing + , _dbpsrsResponseStatus = pResponseStatus_ + } -- | A list of @BatchPrediction@ objects that meet the search criteria. dbpsrsResults :: Lens' DescribeBatchPredictionsResponse [BatchPrediction] -dbpsrsResults = lens _dbpsrsResults (\ s a -> s{_dbpsrsResults = a}) . _Default . _Coerce; +dbpsrsResults = lens _dbpsrsResults (\ s a -> s{_dbpsrsResults = a}) . _Default . _Coerce -- | The ID of the next page in the paginated results that indicates at least one more page follows. dbpsrsNextToken :: Lens' DescribeBatchPredictionsResponse (Maybe Text) -dbpsrsNextToken = lens _dbpsrsNextToken (\ s a -> s{_dbpsrsNextToken = a}); +dbpsrsNextToken = lens _dbpsrsNextToken (\ s a -> s{_dbpsrsNextToken = a}) -- | -- | The response status code. dbpsrsResponseStatus :: Lens' DescribeBatchPredictionsResponse Int -dbpsrsResponseStatus = lens _dbpsrsResponseStatus (\ s a -> s{_dbpsrsResponseStatus = a}); +dbpsrsResponseStatus = lens _dbpsrsResponseStatus (\ s a -> s{_dbpsrsResponseStatus = a}) instance NFData DescribeBatchPredictionsResponse where diff --git a/gen/Network/AWS/MachineLearning/DescribeDataSources.hs b/gen/Network/AWS/MachineLearning/DescribeDataSources.hs --- a/gen/Network/AWS/MachineLearning/DescribeDataSources.hs +++ b/gen/Network/AWS/MachineLearning/DescribeDataSources.hs @@ -12,7 +12,7 @@ -- | -- Module : Network.AWS.MachineLearning.DescribeDataSources --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -103,63 +103,63 @@ :: DescribeDataSources describeDataSources = DescribeDataSources' - { _ddsEQ = Nothing - , _ddsGE = Nothing - , _ddsPrefix = Nothing - , _ddsGT = Nothing - , _ddsNE = Nothing - , _ddsNextToken = Nothing - , _ddsSortOrder = Nothing - , _ddsLimit = Nothing - , _ddsLT = Nothing - , _ddsFilterVariable = Nothing - , _ddsLE = Nothing - } + { _ddsEQ = Nothing + , _ddsGE = Nothing + , _ddsPrefix = Nothing + , _ddsGT = Nothing + , _ddsNE = Nothing + , _ddsNextToken = Nothing + , _ddsSortOrder = Nothing + , _ddsLimit = Nothing + , _ddsLT = Nothing + , _ddsFilterVariable = Nothing + , _ddsLE = Nothing + } -- | The equal to operator. The @DataSource@ results will have @FilterVariable@ values that exactly match the value specified with @EQ@ . ddsEQ :: Lens' DescribeDataSources (Maybe Text) -ddsEQ = lens _ddsEQ (\ s a -> s{_ddsEQ = a}); +ddsEQ = lens _ddsEQ (\ s a -> s{_ddsEQ = a}) -- | The greater than or equal to operator. The @DataSource@ results will have @FilterVariable@ values that are greater than or equal to the value specified with @GE@ . ddsGE :: Lens' DescribeDataSources (Maybe Text) -ddsGE = lens _ddsGE (\ s a -> s{_ddsGE = a}); +ddsGE = lens _ddsGE (\ s a -> s{_ddsGE = a}) -- | A string that is found at the beginning of a variable, such as @Name@ or @Id@ . For example, a @DataSource@ could have the @Name@ @2014-09-09-HolidayGiftMailer@ . To search for this @DataSource@ , select @Name@ for the @FilterVariable@ and any of the following strings for the @Prefix@ : * 2014-09 * 2014-09-09 * 2014-09-09-Holiday ddsPrefix :: Lens' DescribeDataSources (Maybe Text) -ddsPrefix = lens _ddsPrefix (\ s a -> s{_ddsPrefix = a}); +ddsPrefix = lens _ddsPrefix (\ s a -> s{_ddsPrefix = a}) -- | The greater than operator. The @DataSource@ results will have @FilterVariable@ values that are greater than the value specified with @GT@ . ddsGT :: Lens' DescribeDataSources (Maybe Text) -ddsGT = lens _ddsGT (\ s a -> s{_ddsGT = a}); +ddsGT = lens _ddsGT (\ s a -> s{_ddsGT = a}) -- | The not equal to operator. The @DataSource@ results will have @FilterVariable@ values not equal to the value specified with @NE@ . ddsNE :: Lens' DescribeDataSources (Maybe Text) -ddsNE = lens _ddsNE (\ s a -> s{_ddsNE = a}); +ddsNE = lens _ddsNE (\ s a -> s{_ddsNE = a}) -- | The ID of the page in the paginated results. ddsNextToken :: Lens' DescribeDataSources (Maybe Text) -ddsNextToken = lens _ddsNextToken (\ s a -> s{_ddsNextToken = a}); +ddsNextToken = lens _ddsNextToken (\ s a -> s{_ddsNextToken = a}) -- | A two-value parameter that determines the sequence of the resulting list of @DataSource@ . * @asc@ - Arranges the list in ascending order (A-Z, 0-9). * @dsc@ - Arranges the list in descending order (Z-A, 9-0). Results are sorted by @FilterVariable@ . ddsSortOrder :: Lens' DescribeDataSources (Maybe SortOrder) -ddsSortOrder = lens _ddsSortOrder (\ s a -> s{_ddsSortOrder = a}); +ddsSortOrder = lens _ddsSortOrder (\ s a -> s{_ddsSortOrder = a}) -- | The maximum number of @DataSource@ to include in the result. ddsLimit :: Lens' DescribeDataSources (Maybe Natural) -ddsLimit = lens _ddsLimit (\ s a -> s{_ddsLimit = a}) . mapping _Nat; +ddsLimit = lens _ddsLimit (\ s a -> s{_ddsLimit = a}) . mapping _Nat -- | The less than operator. The @DataSource@ results will have @FilterVariable@ values that are less than the value specified with @LT@ . ddsLT :: Lens' DescribeDataSources (Maybe Text) -ddsLT = lens _ddsLT (\ s a -> s{_ddsLT = a}); +ddsLT = lens _ddsLT (\ s a -> s{_ddsLT = a}) -- | Use one of the following variables to filter a list of @DataSource@ : * @CreatedAt@ - Sets the search criteria to @DataSource@ creation dates. * @Status@ - Sets the search criteria to @DataSource@ statuses. * @Name@ - Sets the search criteria to the contents of @DataSource@ ____ @Name@ . * @DataUri@ - Sets the search criteria to the URI of data files used to create the @DataSource@ . The URI can identify either a file or an Amazon Simple Storage Service (Amazon S3) bucket or directory. * @IAMUser@ - Sets the search criteria to the user account that invoked the @DataSource@ creation. ddsFilterVariable :: Lens' DescribeDataSources (Maybe DataSourceFilterVariable) -ddsFilterVariable = lens _ddsFilterVariable (\ s a -> s{_ddsFilterVariable = a}); +ddsFilterVariable = lens _ddsFilterVariable (\ s a -> s{_ddsFilterVariable = a}) -- | The less than or equal to operator. The @DataSource@ results will have @FilterVariable@ values that are less than or equal to the value specified with @LE@ . ddsLE :: Lens' DescribeDataSources (Maybe Text) -ddsLE = lens _ddsLE (\ s a -> s{_ddsLE = a}); +ddsLE = lens _ddsLE (\ s a -> s{_ddsLE = a}) instance AWSPager DescribeDataSources where page rq rs @@ -238,22 +238,22 @@ -> DescribeDataSourcesResponse describeDataSourcesResponse pResponseStatus_ = DescribeDataSourcesResponse' - { _ddssrsResults = Nothing - , _ddssrsNextToken = Nothing - , _ddssrsResponseStatus = pResponseStatus_ - } + { _ddssrsResults = Nothing + , _ddssrsNextToken = Nothing + , _ddssrsResponseStatus = pResponseStatus_ + } -- | A list of @DataSource@ that meet the search criteria. ddssrsResults :: Lens' DescribeDataSourcesResponse [DataSource] -ddssrsResults = lens _ddssrsResults (\ s a -> s{_ddssrsResults = a}) . _Default . _Coerce; +ddssrsResults = lens _ddssrsResults (\ s a -> s{_ddssrsResults = a}) . _Default . _Coerce -- | An ID of the next page in the paginated results that indicates at least one more page follows. ddssrsNextToken :: Lens' DescribeDataSourcesResponse (Maybe Text) -ddssrsNextToken = lens _ddssrsNextToken (\ s a -> s{_ddssrsNextToken = a}); +ddssrsNextToken = lens _ddssrsNextToken (\ s a -> s{_ddssrsNextToken = a}) -- | -- | The response status code. ddssrsResponseStatus :: Lens' DescribeDataSourcesResponse Int -ddssrsResponseStatus = lens _ddssrsResponseStatus (\ s a -> s{_ddssrsResponseStatus = a}); +ddssrsResponseStatus = lens _ddssrsResponseStatus (\ s a -> s{_ddssrsResponseStatus = a}) instance NFData DescribeDataSourcesResponse where diff --git a/gen/Network/AWS/MachineLearning/DescribeEvaluations.hs b/gen/Network/AWS/MachineLearning/DescribeEvaluations.hs --- a/gen/Network/AWS/MachineLearning/DescribeEvaluations.hs +++ b/gen/Network/AWS/MachineLearning/DescribeEvaluations.hs @@ -12,7 +12,7 @@ -- | -- Module : Network.AWS.MachineLearning.DescribeEvaluations --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -103,63 +103,63 @@ :: DescribeEvaluations describeEvaluations = DescribeEvaluations' - { _deEQ = Nothing - , _deGE = Nothing - , _dePrefix = Nothing - , _deGT = Nothing - , _deNE = Nothing - , _deNextToken = Nothing - , _deSortOrder = Nothing - , _deLimit = Nothing - , _deLT = Nothing - , _deFilterVariable = Nothing - , _deLE = Nothing - } + { _deEQ = Nothing + , _deGE = Nothing + , _dePrefix = Nothing + , _deGT = Nothing + , _deNE = Nothing + , _deNextToken = Nothing + , _deSortOrder = Nothing + , _deLimit = Nothing + , _deLT = Nothing + , _deFilterVariable = Nothing + , _deLE = Nothing + } -- | The equal to operator. The @Evaluation@ results will have @FilterVariable@ values that exactly match the value specified with @EQ@ . deEQ :: Lens' DescribeEvaluations (Maybe Text) -deEQ = lens _deEQ (\ s a -> s{_deEQ = a}); +deEQ = lens _deEQ (\ s a -> s{_deEQ = a}) -- | The greater than or equal to operator. The @Evaluation@ results will have @FilterVariable@ values that are greater than or equal to the value specified with @GE@ . deGE :: Lens' DescribeEvaluations (Maybe Text) -deGE = lens _deGE (\ s a -> s{_deGE = a}); +deGE = lens _deGE (\ s a -> s{_deGE = a}) -- | A string that is found at the beginning of a variable, such as @Name@ or @Id@ . For example, an @Evaluation@ could have the @Name@ @2014-09-09-HolidayGiftMailer@ . To search for this @Evaluation@ , select @Name@ for the @FilterVariable@ and any of the following strings for the @Prefix@ : * 2014-09 * 2014-09-09 * 2014-09-09-Holiday dePrefix :: Lens' DescribeEvaluations (Maybe Text) -dePrefix = lens _dePrefix (\ s a -> s{_dePrefix = a}); +dePrefix = lens _dePrefix (\ s a -> s{_dePrefix = a}) -- | The greater than operator. The @Evaluation@ results will have @FilterVariable@ values that are greater than the value specified with @GT@ . deGT :: Lens' DescribeEvaluations (Maybe Text) -deGT = lens _deGT (\ s a -> s{_deGT = a}); +deGT = lens _deGT (\ s a -> s{_deGT = a}) -- | The not equal to operator. The @Evaluation@ results will have @FilterVariable@ values not equal to the value specified with @NE@ . deNE :: Lens' DescribeEvaluations (Maybe Text) -deNE = lens _deNE (\ s a -> s{_deNE = a}); +deNE = lens _deNE (\ s a -> s{_deNE = a}) -- | The ID of the page in the paginated results. deNextToken :: Lens' DescribeEvaluations (Maybe Text) -deNextToken = lens _deNextToken (\ s a -> s{_deNextToken = a}); +deNextToken = lens _deNextToken (\ s a -> s{_deNextToken = a}) -- | A two-value parameter that determines the sequence of the resulting list of @Evaluation@ . * @asc@ - Arranges the list in ascending order (A-Z, 0-9). * @dsc@ - Arranges the list in descending order (Z-A, 9-0). Results are sorted by @FilterVariable@ . deSortOrder :: Lens' DescribeEvaluations (Maybe SortOrder) -deSortOrder = lens _deSortOrder (\ s a -> s{_deSortOrder = a}); +deSortOrder = lens _deSortOrder (\ s a -> s{_deSortOrder = a}) -- | The maximum number of @Evaluation@ to include in the result. deLimit :: Lens' DescribeEvaluations (Maybe Natural) -deLimit = lens _deLimit (\ s a -> s{_deLimit = a}) . mapping _Nat; +deLimit = lens _deLimit (\ s a -> s{_deLimit = a}) . mapping _Nat -- | The less than operator. The @Evaluation@ results will have @FilterVariable@ values that are less than the value specified with @LT@ . deLT :: Lens' DescribeEvaluations (Maybe Text) -deLT = lens _deLT (\ s a -> s{_deLT = a}); +deLT = lens _deLT (\ s a -> s{_deLT = a}) -- | Use one of the following variable to filter a list of @Evaluation@ objects: * @CreatedAt@ - Sets the search criteria to the @Evaluation@ creation date. * @Status@ - Sets the search criteria to the @Evaluation@ status. * @Name@ - Sets the search criteria to the contents of @Evaluation@ ____ @Name@ . * @IAMUser@ - Sets the search criteria to the user account that invoked an @Evaluation@ . * @MLModelId@ - Sets the search criteria to the @MLModel@ that was evaluated. * @DataSourceId@ - Sets the search criteria to the @DataSource@ used in @Evaluation@ . * @DataUri@ - Sets the search criteria to the data file(s) used in @Evaluation@ . The URL can identify either a file or an Amazon Simple Storage Solution (Amazon S3) bucket or directory. deFilterVariable :: Lens' DescribeEvaluations (Maybe EvaluationFilterVariable) -deFilterVariable = lens _deFilterVariable (\ s a -> s{_deFilterVariable = a}); +deFilterVariable = lens _deFilterVariable (\ s a -> s{_deFilterVariable = a}) -- | The less than or equal to operator. The @Evaluation@ results will have @FilterVariable@ values that are less than or equal to the value specified with @LE@ . deLE :: Lens' DescribeEvaluations (Maybe Text) -deLE = lens _deLE (\ s a -> s{_deLE = a}); +deLE = lens _deLE (\ s a -> s{_deLE = a}) instance AWSPager DescribeEvaluations where page rq rs @@ -238,22 +238,22 @@ -> DescribeEvaluationsResponse describeEvaluationsResponse pResponseStatus_ = DescribeEvaluationsResponse' - { _desrsResults = Nothing - , _desrsNextToken = Nothing - , _desrsResponseStatus = pResponseStatus_ - } + { _desrsResults = Nothing + , _desrsNextToken = Nothing + , _desrsResponseStatus = pResponseStatus_ + } -- | A list of @Evaluation@ that meet the search criteria. desrsResults :: Lens' DescribeEvaluationsResponse [Evaluation] -desrsResults = lens _desrsResults (\ s a -> s{_desrsResults = a}) . _Default . _Coerce; +desrsResults = lens _desrsResults (\ s a -> s{_desrsResults = a}) . _Default . _Coerce -- | The ID of the next page in the paginated results that indicates at least one more page follows. desrsNextToken :: Lens' DescribeEvaluationsResponse (Maybe Text) -desrsNextToken = lens _desrsNextToken (\ s a -> s{_desrsNextToken = a}); +desrsNextToken = lens _desrsNextToken (\ s a -> s{_desrsNextToken = a}) -- | -- | The response status code. desrsResponseStatus :: Lens' DescribeEvaluationsResponse Int -desrsResponseStatus = lens _desrsResponseStatus (\ s a -> s{_desrsResponseStatus = a}); +desrsResponseStatus = lens _desrsResponseStatus (\ s a -> s{_desrsResponseStatus = a}) instance NFData DescribeEvaluationsResponse where diff --git a/gen/Network/AWS/MachineLearning/DescribeMLModels.hs b/gen/Network/AWS/MachineLearning/DescribeMLModels.hs --- a/gen/Network/AWS/MachineLearning/DescribeMLModels.hs +++ b/gen/Network/AWS/MachineLearning/DescribeMLModels.hs @@ -12,7 +12,7 @@ -- | -- Module : Network.AWS.MachineLearning.DescribeMLModels --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -103,63 +103,63 @@ :: DescribeMLModels describeMLModels = DescribeMLModels' - { _dmlmEQ = Nothing - , _dmlmGE = Nothing - , _dmlmPrefix = Nothing - , _dmlmGT = Nothing - , _dmlmNE = Nothing - , _dmlmNextToken = Nothing - , _dmlmSortOrder = Nothing - , _dmlmLimit = Nothing - , _dmlmLT = Nothing - , _dmlmFilterVariable = Nothing - , _dmlmLE = Nothing - } + { _dmlmEQ = Nothing + , _dmlmGE = Nothing + , _dmlmPrefix = Nothing + , _dmlmGT = Nothing + , _dmlmNE = Nothing + , _dmlmNextToken = Nothing + , _dmlmSortOrder = Nothing + , _dmlmLimit = Nothing + , _dmlmLT = Nothing + , _dmlmFilterVariable = Nothing + , _dmlmLE = Nothing + } -- | The equal to operator. The @MLModel@ results will have @FilterVariable@ values that exactly match the value specified with @EQ@ . dmlmEQ :: Lens' DescribeMLModels (Maybe Text) -dmlmEQ = lens _dmlmEQ (\ s a -> s{_dmlmEQ = a}); +dmlmEQ = lens _dmlmEQ (\ s a -> s{_dmlmEQ = a}) -- | The greater than or equal to operator. The @MLModel@ results will have @FilterVariable@ values that are greater than or equal to the value specified with @GE@ . dmlmGE :: Lens' DescribeMLModels (Maybe Text) -dmlmGE = lens _dmlmGE (\ s a -> s{_dmlmGE = a}); +dmlmGE = lens _dmlmGE (\ s a -> s{_dmlmGE = a}) -- | A string that is found at the beginning of a variable, such as @Name@ or @Id@ . For example, an @MLModel@ could have the @Name@ @2014-09-09-HolidayGiftMailer@ . To search for this @MLModel@ , select @Name@ for the @FilterVariable@ and any of the following strings for the @Prefix@ : * 2014-09 * 2014-09-09 * 2014-09-09-Holiday dmlmPrefix :: Lens' DescribeMLModels (Maybe Text) -dmlmPrefix = lens _dmlmPrefix (\ s a -> s{_dmlmPrefix = a}); +dmlmPrefix = lens _dmlmPrefix (\ s a -> s{_dmlmPrefix = a}) -- | The greater than operator. The @MLModel@ results will have @FilterVariable@ values that are greater than the value specified with @GT@ . dmlmGT :: Lens' DescribeMLModels (Maybe Text) -dmlmGT = lens _dmlmGT (\ s a -> s{_dmlmGT = a}); +dmlmGT = lens _dmlmGT (\ s a -> s{_dmlmGT = a}) -- | The not equal to operator. The @MLModel@ results will have @FilterVariable@ values not equal to the value specified with @NE@ . dmlmNE :: Lens' DescribeMLModels (Maybe Text) -dmlmNE = lens _dmlmNE (\ s a -> s{_dmlmNE = a}); +dmlmNE = lens _dmlmNE (\ s a -> s{_dmlmNE = a}) -- | The ID of the page in the paginated results. dmlmNextToken :: Lens' DescribeMLModels (Maybe Text) -dmlmNextToken = lens _dmlmNextToken (\ s a -> s{_dmlmNextToken = a}); +dmlmNextToken = lens _dmlmNextToken (\ s a -> s{_dmlmNextToken = a}) -- | A two-value parameter that determines the sequence of the resulting list of @MLModel@ . * @asc@ - Arranges the list in ascending order (A-Z, 0-9). * @dsc@ - Arranges the list in descending order (Z-A, 9-0). Results are sorted by @FilterVariable@ . dmlmSortOrder :: Lens' DescribeMLModels (Maybe SortOrder) -dmlmSortOrder = lens _dmlmSortOrder (\ s a -> s{_dmlmSortOrder = a}); +dmlmSortOrder = lens _dmlmSortOrder (\ s a -> s{_dmlmSortOrder = a}) -- | The number of pages of information to include in the result. The range of acceptable values is @1@ through @100@ . The default value is @100@ . dmlmLimit :: Lens' DescribeMLModels (Maybe Natural) -dmlmLimit = lens _dmlmLimit (\ s a -> s{_dmlmLimit = a}) . mapping _Nat; +dmlmLimit = lens _dmlmLimit (\ s a -> s{_dmlmLimit = a}) . mapping _Nat -- | The less than operator. The @MLModel@ results will have @FilterVariable@ values that are less than the value specified with @LT@ . dmlmLT :: Lens' DescribeMLModels (Maybe Text) -dmlmLT = lens _dmlmLT (\ s a -> s{_dmlmLT = a}); +dmlmLT = lens _dmlmLT (\ s a -> s{_dmlmLT = a}) -- | Use one of the following variables to filter a list of @MLModel@ : * @CreatedAt@ - Sets the search criteria to @MLModel@ creation date. * @Status@ - Sets the search criteria to @MLModel@ status. * @Name@ - Sets the search criteria to the contents of @MLModel@ ____ @Name@ . * @IAMUser@ - Sets the search criteria to the user account that invoked the @MLModel@ creation. * @TrainingDataSourceId@ - Sets the search criteria to the @DataSource@ used to train one or more @MLModel@ . * @RealtimeEndpointStatus@ - Sets the search criteria to the @MLModel@ real-time endpoint status. * @MLModelType@ - Sets the search criteria to @MLModel@ type: binary, regression, or multi-class. * @Algorithm@ - Sets the search criteria to the algorithm that the @MLModel@ uses. * @TrainingDataURI@ - Sets the search criteria to the data file(s) used in training a @MLModel@ . The URL can identify either a file or an Amazon Simple Storage Service (Amazon S3) bucket or directory. dmlmFilterVariable :: Lens' DescribeMLModels (Maybe MLModelFilterVariable) -dmlmFilterVariable = lens _dmlmFilterVariable (\ s a -> s{_dmlmFilterVariable = a}); +dmlmFilterVariable = lens _dmlmFilterVariable (\ s a -> s{_dmlmFilterVariable = a}) -- | The less than or equal to operator. The @MLModel@ results will have @FilterVariable@ values that are less than or equal to the value specified with @LE@ . dmlmLE :: Lens' DescribeMLModels (Maybe Text) -dmlmLE = lens _dmlmLE (\ s a -> s{_dmlmLE = a}); +dmlmLE = lens _dmlmLE (\ s a -> s{_dmlmLE = a}) instance AWSPager DescribeMLModels where page rq rs @@ -236,22 +236,22 @@ -> DescribeMLModelsResponse describeMLModelsResponse pResponseStatus_ = DescribeMLModelsResponse' - { _dmlmsrsResults = Nothing - , _dmlmsrsNextToken = Nothing - , _dmlmsrsResponseStatus = pResponseStatus_ - } + { _dmlmsrsResults = Nothing + , _dmlmsrsNextToken = Nothing + , _dmlmsrsResponseStatus = pResponseStatus_ + } -- | A list of @MLModel@ that meet the search criteria. dmlmsrsResults :: Lens' DescribeMLModelsResponse [MLModel] -dmlmsrsResults = lens _dmlmsrsResults (\ s a -> s{_dmlmsrsResults = a}) . _Default . _Coerce; +dmlmsrsResults = lens _dmlmsrsResults (\ s a -> s{_dmlmsrsResults = a}) . _Default . _Coerce -- | The ID of the next page in the paginated results that indicates at least one more page follows. dmlmsrsNextToken :: Lens' DescribeMLModelsResponse (Maybe Text) -dmlmsrsNextToken = lens _dmlmsrsNextToken (\ s a -> s{_dmlmsrsNextToken = a}); +dmlmsrsNextToken = lens _dmlmsrsNextToken (\ s a -> s{_dmlmsrsNextToken = a}) -- | -- | The response status code. dmlmsrsResponseStatus :: Lens' DescribeMLModelsResponse Int -dmlmsrsResponseStatus = lens _dmlmsrsResponseStatus (\ s a -> s{_dmlmsrsResponseStatus = a}); +dmlmsrsResponseStatus = lens _dmlmsrsResponseStatus (\ s a -> s{_dmlmsrsResponseStatus = a}) instance NFData DescribeMLModelsResponse where diff --git a/gen/Network/AWS/MachineLearning/DescribeTags.hs b/gen/Network/AWS/MachineLearning/DescribeTags.hs --- a/gen/Network/AWS/MachineLearning/DescribeTags.hs +++ b/gen/Network/AWS/MachineLearning/DescribeTags.hs @@ -12,7 +12,7 @@ -- | -- Module : Network.AWS.MachineLearning.DescribeTags --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -71,11 +71,11 @@ -- | The ID of the ML object. For example, @exampleModelId@ . dtResourceId :: Lens' DescribeTags Text -dtResourceId = lens _dtResourceId (\ s a -> s{_dtResourceId = a}); +dtResourceId = lens _dtResourceId (\ s a -> s{_dtResourceId = a}) -- | The type of the ML object. dtResourceType :: Lens' DescribeTags TaggableResourceType -dtResourceType = lens _dtResourceType (\ s a -> s{_dtResourceType = a}); +dtResourceType = lens _dtResourceType (\ s a -> s{_dtResourceType = a}) instance AWSRequest DescribeTags where type Rs DescribeTags = DescribeTagsResponse @@ -143,27 +143,27 @@ -> DescribeTagsResponse describeTagsResponse pResponseStatus_ = DescribeTagsResponse' - { _dtrsResourceId = Nothing - , _dtrsResourceType = Nothing - , _dtrsTags = Nothing - , _dtrsResponseStatus = pResponseStatus_ - } + { _dtrsResourceId = Nothing + , _dtrsResourceType = Nothing + , _dtrsTags = Nothing + , _dtrsResponseStatus = pResponseStatus_ + } -- | The ID of the tagged ML object. dtrsResourceId :: Lens' DescribeTagsResponse (Maybe Text) -dtrsResourceId = lens _dtrsResourceId (\ s a -> s{_dtrsResourceId = a}); +dtrsResourceId = lens _dtrsResourceId (\ s a -> s{_dtrsResourceId = a}) -- | The type of the tagged ML object. dtrsResourceType :: Lens' DescribeTagsResponse (Maybe TaggableResourceType) -dtrsResourceType = lens _dtrsResourceType (\ s a -> s{_dtrsResourceType = a}); +dtrsResourceType = lens _dtrsResourceType (\ s a -> s{_dtrsResourceType = a}) -- | A list of tags associated with the ML object. dtrsTags :: Lens' DescribeTagsResponse [Tag] -dtrsTags = lens _dtrsTags (\ s a -> s{_dtrsTags = a}) . _Default . _Coerce; +dtrsTags = lens _dtrsTags (\ s a -> s{_dtrsTags = a}) . _Default . _Coerce -- | -- | The response status code. dtrsResponseStatus :: Lens' DescribeTagsResponse Int -dtrsResponseStatus = lens _dtrsResponseStatus (\ s a -> s{_dtrsResponseStatus = a}); +dtrsResponseStatus = lens _dtrsResponseStatus (\ s a -> s{_dtrsResponseStatus = a}) instance NFData DescribeTagsResponse where diff --git a/gen/Network/AWS/MachineLearning/GetBatchPrediction.hs b/gen/Network/AWS/MachineLearning/GetBatchPrediction.hs --- a/gen/Network/AWS/MachineLearning/GetBatchPrediction.hs +++ b/gen/Network/AWS/MachineLearning/GetBatchPrediction.hs @@ -12,7 +12,7 @@ -- | -- Module : Network.AWS.MachineLearning.GetBatchPrediction --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -80,7 +80,7 @@ -- | An ID assigned to the @BatchPrediction@ at creation. gbpBatchPredictionId :: Lens' GetBatchPrediction Text -gbpBatchPredictionId = lens _gbpBatchPredictionId (\ s a -> s{_gbpBatchPredictionId = a}); +gbpBatchPredictionId = lens _gbpBatchPredictionId (\ s a -> s{_gbpBatchPredictionId = a}) instance AWSRequest GetBatchPrediction where type Rs GetBatchPrediction = @@ -206,97 +206,97 @@ -> GetBatchPredictionResponse getBatchPredictionResponse pResponseStatus_ = GetBatchPredictionResponse' - { _gbprsStatus = Nothing - , _gbprsLastUpdatedAt = Nothing - , _gbprsCreatedAt = Nothing - , _gbprsComputeTime = Nothing - , _gbprsInputDataLocationS3 = Nothing - , _gbprsMLModelId = Nothing - , _gbprsBatchPredictionDataSourceId = Nothing - , _gbprsTotalRecordCount = Nothing - , _gbprsStartedAt = Nothing - , _gbprsBatchPredictionId = Nothing - , _gbprsFinishedAt = Nothing - , _gbprsInvalidRecordCount = Nothing - , _gbprsCreatedByIAMUser = Nothing - , _gbprsName = Nothing - , _gbprsLogURI = Nothing - , _gbprsMessage = Nothing - , _gbprsOutputURI = Nothing - , _gbprsResponseStatus = pResponseStatus_ - } + { _gbprsStatus = Nothing + , _gbprsLastUpdatedAt = Nothing + , _gbprsCreatedAt = Nothing + , _gbprsComputeTime = Nothing + , _gbprsInputDataLocationS3 = Nothing + , _gbprsMLModelId = Nothing + , _gbprsBatchPredictionDataSourceId = Nothing + , _gbprsTotalRecordCount = Nothing + , _gbprsStartedAt = Nothing + , _gbprsBatchPredictionId = Nothing + , _gbprsFinishedAt = Nothing + , _gbprsInvalidRecordCount = Nothing + , _gbprsCreatedByIAMUser = Nothing + , _gbprsName = Nothing + , _gbprsLogURI = Nothing + , _gbprsMessage = Nothing + , _gbprsOutputURI = Nothing + , _gbprsResponseStatus = pResponseStatus_ + } -- | The status of the @BatchPrediction@ , which can be one of the following values: * @PENDING@ - Amazon Machine Learning (Amazon ML) submitted a request to generate batch predictions. * @INPROGRESS@ - The batch predictions are in progress. * @FAILED@ - The request to perform a batch prediction did not run to completion. It is not usable. * @COMPLETED@ - The batch prediction process completed successfully. * @DELETED@ - The @BatchPrediction@ is marked as deleted. It is not usable. gbprsStatus :: Lens' GetBatchPredictionResponse (Maybe EntityStatus) -gbprsStatus = lens _gbprsStatus (\ s a -> s{_gbprsStatus = a}); +gbprsStatus = lens _gbprsStatus (\ s a -> s{_gbprsStatus = a}) -- | The time of the most recent edit to @BatchPrediction@ . The time is expressed in epoch time. gbprsLastUpdatedAt :: Lens' GetBatchPredictionResponse (Maybe UTCTime) -gbprsLastUpdatedAt = lens _gbprsLastUpdatedAt (\ s a -> s{_gbprsLastUpdatedAt = a}) . mapping _Time; +gbprsLastUpdatedAt = lens _gbprsLastUpdatedAt (\ s a -> s{_gbprsLastUpdatedAt = a}) . mapping _Time -- | The time when the @BatchPrediction@ was created. The time is expressed in epoch time. gbprsCreatedAt :: Lens' GetBatchPredictionResponse (Maybe UTCTime) -gbprsCreatedAt = lens _gbprsCreatedAt (\ s a -> s{_gbprsCreatedAt = a}) . mapping _Time; +gbprsCreatedAt = lens _gbprsCreatedAt (\ s a -> s{_gbprsCreatedAt = a}) . mapping _Time -- | The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the @BatchPrediction@ , normalized and scaled on computation resources. @ComputeTime@ is only available if the @BatchPrediction@ is in the @COMPLETED@ state. gbprsComputeTime :: Lens' GetBatchPredictionResponse (Maybe Integer) -gbprsComputeTime = lens _gbprsComputeTime (\ s a -> s{_gbprsComputeTime = a}); +gbprsComputeTime = lens _gbprsComputeTime (\ s a -> s{_gbprsComputeTime = a}) -- | The location of the data file or directory in Amazon Simple Storage Service (Amazon S3). gbprsInputDataLocationS3 :: Lens' GetBatchPredictionResponse (Maybe Text) -gbprsInputDataLocationS3 = lens _gbprsInputDataLocationS3 (\ s a -> s{_gbprsInputDataLocationS3 = a}); +gbprsInputDataLocationS3 = lens _gbprsInputDataLocationS3 (\ s a -> s{_gbprsInputDataLocationS3 = a}) -- | The ID of the @MLModel@ that generated predictions for the @BatchPrediction@ request. gbprsMLModelId :: Lens' GetBatchPredictionResponse (Maybe Text) -gbprsMLModelId = lens _gbprsMLModelId (\ s a -> s{_gbprsMLModelId = a}); +gbprsMLModelId = lens _gbprsMLModelId (\ s a -> s{_gbprsMLModelId = a}) -- | The ID of the @DataSource@ that was used to create the @BatchPrediction@ . gbprsBatchPredictionDataSourceId :: Lens' GetBatchPredictionResponse (Maybe Text) -gbprsBatchPredictionDataSourceId = lens _gbprsBatchPredictionDataSourceId (\ s a -> s{_gbprsBatchPredictionDataSourceId = a}); +gbprsBatchPredictionDataSourceId = lens _gbprsBatchPredictionDataSourceId (\ s a -> s{_gbprsBatchPredictionDataSourceId = a}) -- | The number of total records that Amazon Machine Learning saw while processing the @BatchPrediction@ . gbprsTotalRecordCount :: Lens' GetBatchPredictionResponse (Maybe Integer) -gbprsTotalRecordCount = lens _gbprsTotalRecordCount (\ s a -> s{_gbprsTotalRecordCount = a}); +gbprsTotalRecordCount = lens _gbprsTotalRecordCount (\ s a -> s{_gbprsTotalRecordCount = a}) -- | The epoch time when Amazon Machine Learning marked the @BatchPrediction@ as @INPROGRESS@ . @StartedAt@ isn't available if the @BatchPrediction@ is in the @PENDING@ state. gbprsStartedAt :: Lens' GetBatchPredictionResponse (Maybe UTCTime) -gbprsStartedAt = lens _gbprsStartedAt (\ s a -> s{_gbprsStartedAt = a}) . mapping _Time; +gbprsStartedAt = lens _gbprsStartedAt (\ s a -> s{_gbprsStartedAt = a}) . mapping _Time -- | An ID assigned to the @BatchPrediction@ at creation. This value should be identical to the value of the @BatchPredictionID@ in the request. gbprsBatchPredictionId :: Lens' GetBatchPredictionResponse (Maybe Text) -gbprsBatchPredictionId = lens _gbprsBatchPredictionId (\ s a -> s{_gbprsBatchPredictionId = a}); +gbprsBatchPredictionId = lens _gbprsBatchPredictionId (\ s a -> s{_gbprsBatchPredictionId = a}) -- | The epoch time when Amazon Machine Learning marked the @BatchPrediction@ as @COMPLETED@ or @FAILED@ . @FinishedAt@ is only available when the @BatchPrediction@ is in the @COMPLETED@ or @FAILED@ state. gbprsFinishedAt :: Lens' GetBatchPredictionResponse (Maybe UTCTime) -gbprsFinishedAt = lens _gbprsFinishedAt (\ s a -> s{_gbprsFinishedAt = a}) . mapping _Time; +gbprsFinishedAt = lens _gbprsFinishedAt (\ s a -> s{_gbprsFinishedAt = a}) . mapping _Time -- | The number of invalid records that Amazon Machine Learning saw while processing the @BatchPrediction@ . gbprsInvalidRecordCount :: Lens' GetBatchPredictionResponse (Maybe Integer) -gbprsInvalidRecordCount = lens _gbprsInvalidRecordCount (\ s a -> s{_gbprsInvalidRecordCount = a}); +gbprsInvalidRecordCount = lens _gbprsInvalidRecordCount (\ s a -> s{_gbprsInvalidRecordCount = a}) -- | The AWS user account that invoked the @BatchPrediction@ . The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account. gbprsCreatedByIAMUser :: Lens' GetBatchPredictionResponse (Maybe Text) -gbprsCreatedByIAMUser = lens _gbprsCreatedByIAMUser (\ s a -> s{_gbprsCreatedByIAMUser = a}); +gbprsCreatedByIAMUser = lens _gbprsCreatedByIAMUser (\ s a -> s{_gbprsCreatedByIAMUser = a}) -- | A user-supplied name or description of the @BatchPrediction@ . gbprsName :: Lens' GetBatchPredictionResponse (Maybe Text) -gbprsName = lens _gbprsName (\ s a -> s{_gbprsName = a}); +gbprsName = lens _gbprsName (\ s a -> s{_gbprsName = a}) -- | A link to the file that contains logs of the @CreateBatchPrediction@ operation. gbprsLogURI :: Lens' GetBatchPredictionResponse (Maybe Text) -gbprsLogURI = lens _gbprsLogURI (\ s a -> s{_gbprsLogURI = a}); +gbprsLogURI = lens _gbprsLogURI (\ s a -> s{_gbprsLogURI = a}) -- | A description of the most recent details about processing the batch prediction request. gbprsMessage :: Lens' GetBatchPredictionResponse (Maybe Text) -gbprsMessage = lens _gbprsMessage (\ s a -> s{_gbprsMessage = a}); +gbprsMessage = lens _gbprsMessage (\ s a -> s{_gbprsMessage = a}) -- | The location of an Amazon S3 bucket or directory to receive the operation results. gbprsOutputURI :: Lens' GetBatchPredictionResponse (Maybe Text) -gbprsOutputURI = lens _gbprsOutputURI (\ s a -> s{_gbprsOutputURI = a}); +gbprsOutputURI = lens _gbprsOutputURI (\ s a -> s{_gbprsOutputURI = a}) -- | -- | The response status code. gbprsResponseStatus :: Lens' GetBatchPredictionResponse Int -gbprsResponseStatus = lens _gbprsResponseStatus (\ s a -> s{_gbprsResponseStatus = a}); +gbprsResponseStatus = lens _gbprsResponseStatus (\ s a -> s{_gbprsResponseStatus = a}) instance NFData GetBatchPredictionResponse where diff --git a/gen/Network/AWS/MachineLearning/GetDataSource.hs b/gen/Network/AWS/MachineLearning/GetDataSource.hs --- a/gen/Network/AWS/MachineLearning/GetDataSource.hs +++ b/gen/Network/AWS/MachineLearning/GetDataSource.hs @@ -12,7 +12,7 @@ -- | -- Module : Network.AWS.MachineLearning.GetDataSource --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -89,11 +89,11 @@ -- | Specifies whether the @GetDataSource@ operation should return @DataSourceSchema@ . If true, @DataSourceSchema@ is returned. If false, @DataSourceSchema@ is not returned. gdsVerbose :: Lens' GetDataSource (Maybe Bool) -gdsVerbose = lens _gdsVerbose (\ s a -> s{_gdsVerbose = a}); +gdsVerbose = lens _gdsVerbose (\ s a -> s{_gdsVerbose = a}) -- | The ID assigned to the @DataSource@ at creation. gdsDataSourceId :: Lens' GetDataSource Text -gdsDataSourceId = lens _gdsDataSourceId (\ s a -> s{_gdsDataSourceId = a}); +gdsDataSourceId = lens _gdsDataSourceId (\ s a -> s{_gdsDataSourceId = a}) instance AWSRequest GetDataSource where type Rs GetDataSource = GetDataSourceResponse @@ -229,112 +229,112 @@ -> GetDataSourceResponse getDataSourceResponse pResponseStatus_ = GetDataSourceResponse' - { _gdsrsStatus = Nothing - , _gdsrsNumberOfFiles = Nothing - , _gdsrsLastUpdatedAt = Nothing - , _gdsrsCreatedAt = Nothing - , _gdsrsComputeTime = Nothing - , _gdsrsDataSourceId = Nothing - , _gdsrsRDSMetadata = Nothing - , _gdsrsDataSizeInBytes = Nothing - , _gdsrsDataSourceSchema = Nothing - , _gdsrsStartedAt = Nothing - , _gdsrsFinishedAt = Nothing - , _gdsrsCreatedByIAMUser = Nothing - , _gdsrsName = Nothing - , _gdsrsLogURI = Nothing - , _gdsrsDataLocationS3 = Nothing - , _gdsrsComputeStatistics = Nothing - , _gdsrsMessage = Nothing - , _gdsrsRedshiftMetadata = Nothing - , _gdsrsDataRearrangement = Nothing - , _gdsrsRoleARN = Nothing - , _gdsrsResponseStatus = pResponseStatus_ - } + { _gdsrsStatus = Nothing + , _gdsrsNumberOfFiles = Nothing + , _gdsrsLastUpdatedAt = Nothing + , _gdsrsCreatedAt = Nothing + , _gdsrsComputeTime = Nothing + , _gdsrsDataSourceId = Nothing + , _gdsrsRDSMetadata = Nothing + , _gdsrsDataSizeInBytes = Nothing + , _gdsrsDataSourceSchema = Nothing + , _gdsrsStartedAt = Nothing + , _gdsrsFinishedAt = Nothing + , _gdsrsCreatedByIAMUser = Nothing + , _gdsrsName = Nothing + , _gdsrsLogURI = Nothing + , _gdsrsDataLocationS3 = Nothing + , _gdsrsComputeStatistics = Nothing + , _gdsrsMessage = Nothing + , _gdsrsRedshiftMetadata = Nothing + , _gdsrsDataRearrangement = Nothing + , _gdsrsRoleARN = Nothing + , _gdsrsResponseStatus = pResponseStatus_ + } -- | The current status of the @DataSource@ . This element can have one of the following values: * @PENDING@ - Amazon ML submitted a request to create a @DataSource@ . * @INPROGRESS@ - The creation process is underway. * @FAILED@ - The request to create a @DataSource@ did not run to completion. It is not usable. * @COMPLETED@ - The creation process completed successfully. * @DELETED@ - The @DataSource@ is marked as deleted. It is not usable. gdsrsStatus :: Lens' GetDataSourceResponse (Maybe EntityStatus) -gdsrsStatus = lens _gdsrsStatus (\ s a -> s{_gdsrsStatus = a}); +gdsrsStatus = lens _gdsrsStatus (\ s a -> s{_gdsrsStatus = a}) -- | The number of data files referenced by the @DataSource@ . gdsrsNumberOfFiles :: Lens' GetDataSourceResponse (Maybe Integer) -gdsrsNumberOfFiles = lens _gdsrsNumberOfFiles (\ s a -> s{_gdsrsNumberOfFiles = a}); +gdsrsNumberOfFiles = lens _gdsrsNumberOfFiles (\ s a -> s{_gdsrsNumberOfFiles = a}) -- | The time of the most recent edit to the @DataSource@ . The time is expressed in epoch time. gdsrsLastUpdatedAt :: Lens' GetDataSourceResponse (Maybe UTCTime) -gdsrsLastUpdatedAt = lens _gdsrsLastUpdatedAt (\ s a -> s{_gdsrsLastUpdatedAt = a}) . mapping _Time; +gdsrsLastUpdatedAt = lens _gdsrsLastUpdatedAt (\ s a -> s{_gdsrsLastUpdatedAt = a}) . mapping _Time -- | The time that the @DataSource@ was created. The time is expressed in epoch time. gdsrsCreatedAt :: Lens' GetDataSourceResponse (Maybe UTCTime) -gdsrsCreatedAt = lens _gdsrsCreatedAt (\ s a -> s{_gdsrsCreatedAt = a}) . mapping _Time; +gdsrsCreatedAt = lens _gdsrsCreatedAt (\ s a -> s{_gdsrsCreatedAt = a}) . mapping _Time -- | The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the @DataSource@ , normalized and scaled on computation resources. @ComputeTime@ is only available if the @DataSource@ is in the @COMPLETED@ state and the @ComputeStatistics@ is set to true. gdsrsComputeTime :: Lens' GetDataSourceResponse (Maybe Integer) -gdsrsComputeTime = lens _gdsrsComputeTime (\ s a -> s{_gdsrsComputeTime = a}); +gdsrsComputeTime = lens _gdsrsComputeTime (\ s a -> s{_gdsrsComputeTime = a}) -- | The ID assigned to the @DataSource@ at creation. This value should be identical to the value of the @DataSourceId@ in the request. gdsrsDataSourceId :: Lens' GetDataSourceResponse (Maybe Text) -gdsrsDataSourceId = lens _gdsrsDataSourceId (\ s a -> s{_gdsrsDataSourceId = a}); +gdsrsDataSourceId = lens _gdsrsDataSourceId (\ s a -> s{_gdsrsDataSourceId = a}) -- | Undocumented member. gdsrsRDSMetadata :: Lens' GetDataSourceResponse (Maybe RDSMetadata) -gdsrsRDSMetadata = lens _gdsrsRDSMetadata (\ s a -> s{_gdsrsRDSMetadata = a}); +gdsrsRDSMetadata = lens _gdsrsRDSMetadata (\ s a -> s{_gdsrsRDSMetadata = a}) -- | The total size of observations in the data files. gdsrsDataSizeInBytes :: Lens' GetDataSourceResponse (Maybe Integer) -gdsrsDataSizeInBytes = lens _gdsrsDataSizeInBytes (\ s a -> s{_gdsrsDataSizeInBytes = a}); +gdsrsDataSizeInBytes = lens _gdsrsDataSizeInBytes (\ s a -> s{_gdsrsDataSizeInBytes = a}) -- | The schema used by all of the data files of this @DataSource@ . gdsrsDataSourceSchema :: Lens' GetDataSourceResponse (Maybe Text) -gdsrsDataSourceSchema = lens _gdsrsDataSourceSchema (\ s a -> s{_gdsrsDataSourceSchema = a}); +gdsrsDataSourceSchema = lens _gdsrsDataSourceSchema (\ s a -> s{_gdsrsDataSourceSchema = a}) -- | The epoch time when Amazon Machine Learning marked the @DataSource@ as @INPROGRESS@ . @StartedAt@ isn't available if the @DataSource@ is in the @PENDING@ state. gdsrsStartedAt :: Lens' GetDataSourceResponse (Maybe UTCTime) -gdsrsStartedAt = lens _gdsrsStartedAt (\ s a -> s{_gdsrsStartedAt = a}) . mapping _Time; +gdsrsStartedAt = lens _gdsrsStartedAt (\ s a -> s{_gdsrsStartedAt = a}) . mapping _Time -- | The epoch time when Amazon Machine Learning marked the @DataSource@ as @COMPLETED@ or @FAILED@ . @FinishedAt@ is only available when the @DataSource@ is in the @COMPLETED@ or @FAILED@ state. gdsrsFinishedAt :: Lens' GetDataSourceResponse (Maybe UTCTime) -gdsrsFinishedAt = lens _gdsrsFinishedAt (\ s a -> s{_gdsrsFinishedAt = a}) . mapping _Time; +gdsrsFinishedAt = lens _gdsrsFinishedAt (\ s a -> s{_gdsrsFinishedAt = a}) . mapping _Time -- | The AWS user account from which the @DataSource@ was created. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account. gdsrsCreatedByIAMUser :: Lens' GetDataSourceResponse (Maybe Text) -gdsrsCreatedByIAMUser = lens _gdsrsCreatedByIAMUser (\ s a -> s{_gdsrsCreatedByIAMUser = a}); +gdsrsCreatedByIAMUser = lens _gdsrsCreatedByIAMUser (\ s a -> s{_gdsrsCreatedByIAMUser = a}) -- | A user-supplied name or description of the @DataSource@ . gdsrsName :: Lens' GetDataSourceResponse (Maybe Text) -gdsrsName = lens _gdsrsName (\ s a -> s{_gdsrsName = a}); +gdsrsName = lens _gdsrsName (\ s a -> s{_gdsrsName = a}) -- | A link to the file containing logs of @CreateDataSourceFrom*@ operations. gdsrsLogURI :: Lens' GetDataSourceResponse (Maybe Text) -gdsrsLogURI = lens _gdsrsLogURI (\ s a -> s{_gdsrsLogURI = a}); +gdsrsLogURI = lens _gdsrsLogURI (\ s a -> s{_gdsrsLogURI = a}) -- | The location of the data file or directory in Amazon Simple Storage Service (Amazon S3). gdsrsDataLocationS3 :: Lens' GetDataSourceResponse (Maybe Text) -gdsrsDataLocationS3 = lens _gdsrsDataLocationS3 (\ s a -> s{_gdsrsDataLocationS3 = a}); +gdsrsDataLocationS3 = lens _gdsrsDataLocationS3 (\ s a -> s{_gdsrsDataLocationS3 = a}) -- | The parameter is @true@ if statistics need to be generated from the observation data. gdsrsComputeStatistics :: Lens' GetDataSourceResponse (Maybe Bool) -gdsrsComputeStatistics = lens _gdsrsComputeStatistics (\ s a -> s{_gdsrsComputeStatistics = a}); +gdsrsComputeStatistics = lens _gdsrsComputeStatistics (\ s a -> s{_gdsrsComputeStatistics = a}) -- | The user-supplied description of the most recent details about creating the @DataSource@ . gdsrsMessage :: Lens' GetDataSourceResponse (Maybe Text) -gdsrsMessage = lens _gdsrsMessage (\ s a -> s{_gdsrsMessage = a}); +gdsrsMessage = lens _gdsrsMessage (\ s a -> s{_gdsrsMessage = a}) -- | Undocumented member. gdsrsRedshiftMetadata :: Lens' GetDataSourceResponse (Maybe RedshiftMetadata) -gdsrsRedshiftMetadata = lens _gdsrsRedshiftMetadata (\ s a -> s{_gdsrsRedshiftMetadata = a}); +gdsrsRedshiftMetadata = lens _gdsrsRedshiftMetadata (\ s a -> s{_gdsrsRedshiftMetadata = a}) -- | A JSON string that represents the splitting and rearrangement requirement used when this @DataSource@ was created. gdsrsDataRearrangement :: Lens' GetDataSourceResponse (Maybe Text) -gdsrsDataRearrangement = lens _gdsrsDataRearrangement (\ s a -> s{_gdsrsDataRearrangement = a}); +gdsrsDataRearrangement = lens _gdsrsDataRearrangement (\ s a -> s{_gdsrsDataRearrangement = a}) -- | Undocumented member. gdsrsRoleARN :: Lens' GetDataSourceResponse (Maybe Text) -gdsrsRoleARN = lens _gdsrsRoleARN (\ s a -> s{_gdsrsRoleARN = a}); +gdsrsRoleARN = lens _gdsrsRoleARN (\ s a -> s{_gdsrsRoleARN = a}) -- | -- | The response status code. gdsrsResponseStatus :: Lens' GetDataSourceResponse Int -gdsrsResponseStatus = lens _gdsrsResponseStatus (\ s a -> s{_gdsrsResponseStatus = a}); +gdsrsResponseStatus = lens _gdsrsResponseStatus (\ s a -> s{_gdsrsResponseStatus = a}) instance NFData GetDataSourceResponse where diff --git a/gen/Network/AWS/MachineLearning/GetEvaluation.hs b/gen/Network/AWS/MachineLearning/GetEvaluation.hs --- a/gen/Network/AWS/MachineLearning/GetEvaluation.hs +++ b/gen/Network/AWS/MachineLearning/GetEvaluation.hs @@ -12,7 +12,7 @@ -- | -- Module : Network.AWS.MachineLearning.GetEvaluation --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -77,7 +77,7 @@ -- | The ID of the @Evaluation@ to retrieve. The evaluation of each @MLModel@ is recorded and cataloged. The ID provides the means to access the information. geEvaluationId :: Lens' GetEvaluation Text -geEvaluationId = lens _geEvaluationId (\ s a -> s{_geEvaluationId = a}); +geEvaluationId = lens _geEvaluationId (\ s a -> s{_geEvaluationId = a}) instance AWSRequest GetEvaluation where type Rs GetEvaluation = GetEvaluationResponse @@ -192,87 +192,87 @@ -> GetEvaluationResponse getEvaluationResponse pResponseStatus_ = GetEvaluationResponse' - { _gersStatus = Nothing - , _gersPerformanceMetrics = Nothing - , _gersLastUpdatedAt = Nothing - , _gersCreatedAt = Nothing - , _gersComputeTime = Nothing - , _gersInputDataLocationS3 = Nothing - , _gersMLModelId = Nothing - , _gersStartedAt = Nothing - , _gersFinishedAt = Nothing - , _gersCreatedByIAMUser = Nothing - , _gersName = Nothing - , _gersLogURI = Nothing - , _gersEvaluationId = Nothing - , _gersMessage = Nothing - , _gersEvaluationDataSourceId = Nothing - , _gersResponseStatus = pResponseStatus_ - } + { _gersStatus = Nothing + , _gersPerformanceMetrics = Nothing + , _gersLastUpdatedAt = Nothing + , _gersCreatedAt = Nothing + , _gersComputeTime = Nothing + , _gersInputDataLocationS3 = Nothing + , _gersMLModelId = Nothing + , _gersStartedAt = Nothing + , _gersFinishedAt = Nothing + , _gersCreatedByIAMUser = Nothing + , _gersName = Nothing + , _gersLogURI = Nothing + , _gersEvaluationId = Nothing + , _gersMessage = Nothing + , _gersEvaluationDataSourceId = Nothing + , _gersResponseStatus = pResponseStatus_ + } -- | The status of the evaluation. This element can have one of the following values: * @PENDING@ - Amazon Machine Language (Amazon ML) submitted a request to evaluate an @MLModel@ . * @INPROGRESS@ - The evaluation is underway. * @FAILED@ - The request to evaluate an @MLModel@ did not run to completion. It is not usable. * @COMPLETED@ - The evaluation process completed successfully. * @DELETED@ - The @Evaluation@ is marked as deleted. It is not usable. gersStatus :: Lens' GetEvaluationResponse (Maybe EntityStatus) -gersStatus = lens _gersStatus (\ s a -> s{_gersStatus = a}); +gersStatus = lens _gersStatus (\ s a -> s{_gersStatus = a}) -- | Measurements of how well the @MLModel@ performed using observations referenced by the @DataSource@ . One of the following metric is returned based on the type of the @MLModel@ : * BinaryAUC: A binary @MLModel@ uses the Area Under the Curve (AUC) technique to measure performance. * RegressionRMSE: A regression @MLModel@ uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable. * MulticlassAvgFScore: A multiclass @MLModel@ uses the F1 score technique to measure performance. For more information about performance metrics, please see the . gersPerformanceMetrics :: Lens' GetEvaluationResponse (Maybe PerformanceMetrics) -gersPerformanceMetrics = lens _gersPerformanceMetrics (\ s a -> s{_gersPerformanceMetrics = a}); +gersPerformanceMetrics = lens _gersPerformanceMetrics (\ s a -> s{_gersPerformanceMetrics = a}) -- | The time of the most recent edit to the @Evaluation@ . The time is expressed in epoch time. gersLastUpdatedAt :: Lens' GetEvaluationResponse (Maybe UTCTime) -gersLastUpdatedAt = lens _gersLastUpdatedAt (\ s a -> s{_gersLastUpdatedAt = a}) . mapping _Time; +gersLastUpdatedAt = lens _gersLastUpdatedAt (\ s a -> s{_gersLastUpdatedAt = a}) . mapping _Time -- | The time that the @Evaluation@ was created. The time is expressed in epoch time. gersCreatedAt :: Lens' GetEvaluationResponse (Maybe UTCTime) -gersCreatedAt = lens _gersCreatedAt (\ s a -> s{_gersCreatedAt = a}) . mapping _Time; +gersCreatedAt = lens _gersCreatedAt (\ s a -> s{_gersCreatedAt = a}) . mapping _Time -- | The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the @Evaluation@ , normalized and scaled on computation resources. @ComputeTime@ is only available if the @Evaluation@ is in the @COMPLETED@ state. gersComputeTime :: Lens' GetEvaluationResponse (Maybe Integer) -gersComputeTime = lens _gersComputeTime (\ s a -> s{_gersComputeTime = a}); +gersComputeTime = lens _gersComputeTime (\ s a -> s{_gersComputeTime = a}) -- | The location of the data file or directory in Amazon Simple Storage Service (Amazon S3). gersInputDataLocationS3 :: Lens' GetEvaluationResponse (Maybe Text) -gersInputDataLocationS3 = lens _gersInputDataLocationS3 (\ s a -> s{_gersInputDataLocationS3 = a}); +gersInputDataLocationS3 = lens _gersInputDataLocationS3 (\ s a -> s{_gersInputDataLocationS3 = a}) -- | The ID of the @MLModel@ that was the focus of the evaluation. gersMLModelId :: Lens' GetEvaluationResponse (Maybe Text) -gersMLModelId = lens _gersMLModelId (\ s a -> s{_gersMLModelId = a}); +gersMLModelId = lens _gersMLModelId (\ s a -> s{_gersMLModelId = a}) -- | The epoch time when Amazon Machine Learning marked the @Evaluation@ as @INPROGRESS@ . @StartedAt@ isn't available if the @Evaluation@ is in the @PENDING@ state. gersStartedAt :: Lens' GetEvaluationResponse (Maybe UTCTime) -gersStartedAt = lens _gersStartedAt (\ s a -> s{_gersStartedAt = a}) . mapping _Time; +gersStartedAt = lens _gersStartedAt (\ s a -> s{_gersStartedAt = a}) . mapping _Time -- | The epoch time when Amazon Machine Learning marked the @Evaluation@ as @COMPLETED@ or @FAILED@ . @FinishedAt@ is only available when the @Evaluation@ is in the @COMPLETED@ or @FAILED@ state. gersFinishedAt :: Lens' GetEvaluationResponse (Maybe UTCTime) -gersFinishedAt = lens _gersFinishedAt (\ s a -> s{_gersFinishedAt = a}) . mapping _Time; +gersFinishedAt = lens _gersFinishedAt (\ s a -> s{_gersFinishedAt = a}) . mapping _Time -- | The AWS user account that invoked the evaluation. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account. gersCreatedByIAMUser :: Lens' GetEvaluationResponse (Maybe Text) -gersCreatedByIAMUser = lens _gersCreatedByIAMUser (\ s a -> s{_gersCreatedByIAMUser = a}); +gersCreatedByIAMUser = lens _gersCreatedByIAMUser (\ s a -> s{_gersCreatedByIAMUser = a}) -- | A user-supplied name or description of the @Evaluation@ . gersName :: Lens' GetEvaluationResponse (Maybe Text) -gersName = lens _gersName (\ s a -> s{_gersName = a}); +gersName = lens _gersName (\ s a -> s{_gersName = a}) -- | A link to the file that contains logs of the @CreateEvaluation@ operation. gersLogURI :: Lens' GetEvaluationResponse (Maybe Text) -gersLogURI = lens _gersLogURI (\ s a -> s{_gersLogURI = a}); +gersLogURI = lens _gersLogURI (\ s a -> s{_gersLogURI = a}) -- | The evaluation ID which is same as the @EvaluationId@ in the request. gersEvaluationId :: Lens' GetEvaluationResponse (Maybe Text) -gersEvaluationId = lens _gersEvaluationId (\ s a -> s{_gersEvaluationId = a}); +gersEvaluationId = lens _gersEvaluationId (\ s a -> s{_gersEvaluationId = a}) -- | A description of the most recent details about evaluating the @MLModel@ . gersMessage :: Lens' GetEvaluationResponse (Maybe Text) -gersMessage = lens _gersMessage (\ s a -> s{_gersMessage = a}); +gersMessage = lens _gersMessage (\ s a -> s{_gersMessage = a}) -- | The @DataSource@ used for this evaluation. gersEvaluationDataSourceId :: Lens' GetEvaluationResponse (Maybe Text) -gersEvaluationDataSourceId = lens _gersEvaluationDataSourceId (\ s a -> s{_gersEvaluationDataSourceId = a}); +gersEvaluationDataSourceId = lens _gersEvaluationDataSourceId (\ s a -> s{_gersEvaluationDataSourceId = a}) -- | -- | The response status code. gersResponseStatus :: Lens' GetEvaluationResponse Int -gersResponseStatus = lens _gersResponseStatus (\ s a -> s{_gersResponseStatus = a}); +gersResponseStatus = lens _gersResponseStatus (\ s a -> s{_gersResponseStatus = a}) instance NFData GetEvaluationResponse where diff --git a/gen/Network/AWS/MachineLearning/GetMLModel.hs b/gen/Network/AWS/MachineLearning/GetMLModel.hs --- a/gen/Network/AWS/MachineLearning/GetMLModel.hs +++ b/gen/Network/AWS/MachineLearning/GetMLModel.hs @@ -12,7 +12,7 @@ -- | -- Module : Network.AWS.MachineLearning.GetMLModel --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -90,11 +90,11 @@ -- | Specifies whether the @GetMLModel@ operation should return @Recipe@ . If true, @Recipe@ is returned. If false, @Recipe@ is not returned. gmlmVerbose :: Lens' GetMLModel (Maybe Bool) -gmlmVerbose = lens _gmlmVerbose (\ s a -> s{_gmlmVerbose = a}); +gmlmVerbose = lens _gmlmVerbose (\ s a -> s{_gmlmVerbose = a}) -- | The ID assigned to the @MLModel@ at creation. gmlmMLModelId :: Lens' GetMLModel Text -gmlmMLModelId = lens _gmlmMLModelId (\ s a -> s{_gmlmMLModelId = a}); +gmlmMLModelId = lens _gmlmMLModelId (\ s a -> s{_gmlmMLModelId = a}) instance AWSRequest GetMLModel where type Rs GetMLModel = GetMLModelResponse @@ -234,117 +234,117 @@ -> GetMLModelResponse getMLModelResponse pResponseStatus_ = GetMLModelResponse' - { _gmlmrsStatus = Nothing - , _gmlmrsLastUpdatedAt = Nothing - , _gmlmrsTrainingParameters = Nothing - , _gmlmrsScoreThresholdLastUpdatedAt = Nothing - , _gmlmrsCreatedAt = Nothing - , _gmlmrsComputeTime = Nothing - , _gmlmrsRecipe = Nothing - , _gmlmrsInputDataLocationS3 = Nothing - , _gmlmrsMLModelId = Nothing - , _gmlmrsSizeInBytes = Nothing - , _gmlmrsSchema = Nothing - , _gmlmrsStartedAt = Nothing - , _gmlmrsScoreThreshold = Nothing - , _gmlmrsFinishedAt = Nothing - , _gmlmrsCreatedByIAMUser = Nothing - , _gmlmrsName = Nothing - , _gmlmrsLogURI = Nothing - , _gmlmrsEndpointInfo = Nothing - , _gmlmrsTrainingDataSourceId = Nothing - , _gmlmrsMessage = Nothing - , _gmlmrsMLModelType = Nothing - , _gmlmrsResponseStatus = pResponseStatus_ - } + { _gmlmrsStatus = Nothing + , _gmlmrsLastUpdatedAt = Nothing + , _gmlmrsTrainingParameters = Nothing + , _gmlmrsScoreThresholdLastUpdatedAt = Nothing + , _gmlmrsCreatedAt = Nothing + , _gmlmrsComputeTime = Nothing + , _gmlmrsRecipe = Nothing + , _gmlmrsInputDataLocationS3 = Nothing + , _gmlmrsMLModelId = Nothing + , _gmlmrsSizeInBytes = Nothing + , _gmlmrsSchema = Nothing + , _gmlmrsStartedAt = Nothing + , _gmlmrsScoreThreshold = Nothing + , _gmlmrsFinishedAt = Nothing + , _gmlmrsCreatedByIAMUser = Nothing + , _gmlmrsName = Nothing + , _gmlmrsLogURI = Nothing + , _gmlmrsEndpointInfo = Nothing + , _gmlmrsTrainingDataSourceId = Nothing + , _gmlmrsMessage = Nothing + , _gmlmrsMLModelType = Nothing + , _gmlmrsResponseStatus = pResponseStatus_ + } -- | The current status of the @MLModel@ . This element can have one of the following values: * @PENDING@ - Amazon Machine Learning (Amazon ML) submitted a request to describe a @MLModel@ . * @INPROGRESS@ - The request is processing. * @FAILED@ - The request did not run to completion. The ML model isn't usable. * @COMPLETED@ - The request completed successfully. * @DELETED@ - The @MLModel@ is marked as deleted. It isn't usable. gmlmrsStatus :: Lens' GetMLModelResponse (Maybe EntityStatus) -gmlmrsStatus = lens _gmlmrsStatus (\ s a -> s{_gmlmrsStatus = a}); +gmlmrsStatus = lens _gmlmrsStatus (\ s a -> s{_gmlmrsStatus = a}) -- | The time of the most recent edit to the @MLModel@ . The time is expressed in epoch time. gmlmrsLastUpdatedAt :: Lens' GetMLModelResponse (Maybe UTCTime) -gmlmrsLastUpdatedAt = lens _gmlmrsLastUpdatedAt (\ s a -> s{_gmlmrsLastUpdatedAt = a}) . mapping _Time; +gmlmrsLastUpdatedAt = lens _gmlmrsLastUpdatedAt (\ s a -> s{_gmlmrsLastUpdatedAt = a}) . mapping _Time -- | A list of the training parameters in the @MLModel@ . The list is implemented as a map of key-value pairs. The following is the current set of training parameters: * @sgd.maxMLModelSizeInBytes@ - The maximum allowed size of the model. Depending on the input data, the size of the model might affect its performance. The value is an integer that ranges from @100000@ to @2147483648@ . The default value is @33554432@ . * @sgd.maxPasses@ - The number of times that the training process traverses the observations to build the @MLModel@ . The value is an integer that ranges from @1@ to @10000@ . The default value is @10@ . * @sgd.shuffleType@ - Whether Amazon ML shuffles the training data. Shuffling data improves a model's ability to find the optimal solution for a variety of data types. The valid values are @auto@ and @none@ . The default value is @none@ . We strongly recommend that you shuffle your data. * @sgd.l1RegularizationAmount@ - The coefficient regularization L1 norm. It controls overfitting the data by penalizing large coefficients. This tends to drive coefficients to zero, resulting in a sparse feature set. If you use this parameter, start by specifying a small value, such as @1.0E-08@ . The value is a double that ranges from @0@ to @MAX_DOUBLE@ . The default is to not use L1 normalization. This parameter can't be used when @L2@ is specified. Use this parameter sparingly. * @sgd.l2RegularizationAmount@ - The coefficient regularization L2 norm. It controls overfitting the data by penalizing large coefficients. This tends to drive coefficients to small, nonzero values. If you use this parameter, start by specifying a small value, such as @1.0E-08@ . The value is a double that ranges from @0@ to @MAX_DOUBLE@ . The default is to not use L2 normalization. This parameter can't be used when @L1@ is specified. Use this parameter sparingly. gmlmrsTrainingParameters :: Lens' GetMLModelResponse (HashMap Text Text) -gmlmrsTrainingParameters = lens _gmlmrsTrainingParameters (\ s a -> s{_gmlmrsTrainingParameters = a}) . _Default . _Map; +gmlmrsTrainingParameters = lens _gmlmrsTrainingParameters (\ s a -> s{_gmlmrsTrainingParameters = a}) . _Default . _Map -- | The time of the most recent edit to the @ScoreThreshold@ . The time is expressed in epoch time. gmlmrsScoreThresholdLastUpdatedAt :: Lens' GetMLModelResponse (Maybe UTCTime) -gmlmrsScoreThresholdLastUpdatedAt = lens _gmlmrsScoreThresholdLastUpdatedAt (\ s a -> s{_gmlmrsScoreThresholdLastUpdatedAt = a}) . mapping _Time; +gmlmrsScoreThresholdLastUpdatedAt = lens _gmlmrsScoreThresholdLastUpdatedAt (\ s a -> s{_gmlmrsScoreThresholdLastUpdatedAt = a}) . mapping _Time -- | The time that the @MLModel@ was created. The time is expressed in epoch time. gmlmrsCreatedAt :: Lens' GetMLModelResponse (Maybe UTCTime) -gmlmrsCreatedAt = lens _gmlmrsCreatedAt (\ s a -> s{_gmlmrsCreatedAt = a}) . mapping _Time; +gmlmrsCreatedAt = lens _gmlmrsCreatedAt (\ s a -> s{_gmlmrsCreatedAt = a}) . mapping _Time -- | The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the @MLModel@ , normalized and scaled on computation resources. @ComputeTime@ is only available if the @MLModel@ is in the @COMPLETED@ state. gmlmrsComputeTime :: Lens' GetMLModelResponse (Maybe Integer) -gmlmrsComputeTime = lens _gmlmrsComputeTime (\ s a -> s{_gmlmrsComputeTime = a}); +gmlmrsComputeTime = lens _gmlmrsComputeTime (\ s a -> s{_gmlmrsComputeTime = a}) -- | The recipe to use when training the @MLModel@ . The @Recipe@ provides detailed information about the observation data to use during training, and manipulations to perform on the observation data during training. gmlmrsRecipe :: Lens' GetMLModelResponse (Maybe Text) -gmlmrsRecipe = lens _gmlmrsRecipe (\ s a -> s{_gmlmrsRecipe = a}); +gmlmrsRecipe = lens _gmlmrsRecipe (\ s a -> s{_gmlmrsRecipe = a}) -- | The location of the data file or directory in Amazon Simple Storage Service (Amazon S3). gmlmrsInputDataLocationS3 :: Lens' GetMLModelResponse (Maybe Text) -gmlmrsInputDataLocationS3 = lens _gmlmrsInputDataLocationS3 (\ s a -> s{_gmlmrsInputDataLocationS3 = a}); +gmlmrsInputDataLocationS3 = lens _gmlmrsInputDataLocationS3 (\ s a -> s{_gmlmrsInputDataLocationS3 = a}) -- | The MLModel ID, which is same as the @MLModelId@ in the request. gmlmrsMLModelId :: Lens' GetMLModelResponse (Maybe Text) -gmlmrsMLModelId = lens _gmlmrsMLModelId (\ s a -> s{_gmlmrsMLModelId = a}); +gmlmrsMLModelId = lens _gmlmrsMLModelId (\ s a -> s{_gmlmrsMLModelId = a}) -- | Undocumented member. gmlmrsSizeInBytes :: Lens' GetMLModelResponse (Maybe Integer) -gmlmrsSizeInBytes = lens _gmlmrsSizeInBytes (\ s a -> s{_gmlmrsSizeInBytes = a}); +gmlmrsSizeInBytes = lens _gmlmrsSizeInBytes (\ s a -> s{_gmlmrsSizeInBytes = a}) -- | The schema used by all of the data files referenced by the @DataSource@ . gmlmrsSchema :: Lens' GetMLModelResponse (Maybe Text) -gmlmrsSchema = lens _gmlmrsSchema (\ s a -> s{_gmlmrsSchema = a}); +gmlmrsSchema = lens _gmlmrsSchema (\ s a -> s{_gmlmrsSchema = a}) -- | The epoch time when Amazon Machine Learning marked the @MLModel@ as @INPROGRESS@ . @StartedAt@ isn't available if the @MLModel@ is in the @PENDING@ state. gmlmrsStartedAt :: Lens' GetMLModelResponse (Maybe UTCTime) -gmlmrsStartedAt = lens _gmlmrsStartedAt (\ s a -> s{_gmlmrsStartedAt = a}) . mapping _Time; +gmlmrsStartedAt = lens _gmlmrsStartedAt (\ s a -> s{_gmlmrsStartedAt = a}) . mapping _Time -- | The scoring threshold is used in binary classification @MLModel@ models. It marks the boundary between a positive prediction and a negative prediction. Output values greater than or equal to the threshold receive a positive result from the MLModel, such as @true@ . Output values less than the threshold receive a negative response from the MLModel, such as @false@ . gmlmrsScoreThreshold :: Lens' GetMLModelResponse (Maybe Double) -gmlmrsScoreThreshold = lens _gmlmrsScoreThreshold (\ s a -> s{_gmlmrsScoreThreshold = a}); +gmlmrsScoreThreshold = lens _gmlmrsScoreThreshold (\ s a -> s{_gmlmrsScoreThreshold = a}) -- | The epoch time when Amazon Machine Learning marked the @MLModel@ as @COMPLETED@ or @FAILED@ . @FinishedAt@ is only available when the @MLModel@ is in the @COMPLETED@ or @FAILED@ state. gmlmrsFinishedAt :: Lens' GetMLModelResponse (Maybe UTCTime) -gmlmrsFinishedAt = lens _gmlmrsFinishedAt (\ s a -> s{_gmlmrsFinishedAt = a}) . mapping _Time; +gmlmrsFinishedAt = lens _gmlmrsFinishedAt (\ s a -> s{_gmlmrsFinishedAt = a}) . mapping _Time -- | The AWS user account from which the @MLModel@ was created. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account. gmlmrsCreatedByIAMUser :: Lens' GetMLModelResponse (Maybe Text) -gmlmrsCreatedByIAMUser = lens _gmlmrsCreatedByIAMUser (\ s a -> s{_gmlmrsCreatedByIAMUser = a}); +gmlmrsCreatedByIAMUser = lens _gmlmrsCreatedByIAMUser (\ s a -> s{_gmlmrsCreatedByIAMUser = a}) -- | A user-supplied name or description of the @MLModel@ . gmlmrsName :: Lens' GetMLModelResponse (Maybe Text) -gmlmrsName = lens _gmlmrsName (\ s a -> s{_gmlmrsName = a}); +gmlmrsName = lens _gmlmrsName (\ s a -> s{_gmlmrsName = a}) -- | A link to the file that contains logs of the @CreateMLModel@ operation. gmlmrsLogURI :: Lens' GetMLModelResponse (Maybe Text) -gmlmrsLogURI = lens _gmlmrsLogURI (\ s a -> s{_gmlmrsLogURI = a}); +gmlmrsLogURI = lens _gmlmrsLogURI (\ s a -> s{_gmlmrsLogURI = a}) -- | The current endpoint of the @MLModel@ gmlmrsEndpointInfo :: Lens' GetMLModelResponse (Maybe RealtimeEndpointInfo) -gmlmrsEndpointInfo = lens _gmlmrsEndpointInfo (\ s a -> s{_gmlmrsEndpointInfo = a}); +gmlmrsEndpointInfo = lens _gmlmrsEndpointInfo (\ s a -> s{_gmlmrsEndpointInfo = a}) -- | The ID of the training @DataSource@ . gmlmrsTrainingDataSourceId :: Lens' GetMLModelResponse (Maybe Text) -gmlmrsTrainingDataSourceId = lens _gmlmrsTrainingDataSourceId (\ s a -> s{_gmlmrsTrainingDataSourceId = a}); +gmlmrsTrainingDataSourceId = lens _gmlmrsTrainingDataSourceId (\ s a -> s{_gmlmrsTrainingDataSourceId = a}) -- | A description of the most recent details about accessing the @MLModel@ . gmlmrsMessage :: Lens' GetMLModelResponse (Maybe Text) -gmlmrsMessage = lens _gmlmrsMessage (\ s a -> s{_gmlmrsMessage = a}); +gmlmrsMessage = lens _gmlmrsMessage (\ s a -> s{_gmlmrsMessage = a}) -- | Identifies the @MLModel@ category. The following are the available types: * REGRESSION -- Produces a numeric result. For example, "What price should a house be listed at?" * BINARY -- Produces one of two possible results. For example, "Is this an e-commerce website?" * MULTICLASS -- Produces one of several possible results. For example, "Is this a HIGH, LOW or MEDIUM risk trade?" gmlmrsMLModelType :: Lens' GetMLModelResponse (Maybe MLModelType) -gmlmrsMLModelType = lens _gmlmrsMLModelType (\ s a -> s{_gmlmrsMLModelType = a}); +gmlmrsMLModelType = lens _gmlmrsMLModelType (\ s a -> s{_gmlmrsMLModelType = a}) -- | -- | The response status code. gmlmrsResponseStatus :: Lens' GetMLModelResponse Int -gmlmrsResponseStatus = lens _gmlmrsResponseStatus (\ s a -> s{_gmlmrsResponseStatus = a}); +gmlmrsResponseStatus = lens _gmlmrsResponseStatus (\ s a -> s{_gmlmrsResponseStatus = a}) instance NFData GetMLModelResponse where diff --git a/gen/Network/AWS/MachineLearning/Predict.hs b/gen/Network/AWS/MachineLearning/Predict.hs --- a/gen/Network/AWS/MachineLearning/Predict.hs +++ b/gen/Network/AWS/MachineLearning/Predict.hs @@ -12,7 +12,7 @@ -- | -- Module : Network.AWS.MachineLearning.Predict --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -69,23 +69,23 @@ -> Predict predict pMLModelId_ pPredictEndpoint_ = Predict' - { _pMLModelId = pMLModelId_ - , _pRecord = mempty - , _pPredictEndpoint = pPredictEndpoint_ - } + { _pMLModelId = pMLModelId_ + , _pRecord = mempty + , _pPredictEndpoint = pPredictEndpoint_ + } -- | A unique identifier of the @MLModel@ . pMLModelId :: Lens' Predict Text -pMLModelId = lens _pMLModelId (\ s a -> s{_pMLModelId = a}); +pMLModelId = lens _pMLModelId (\ s a -> s{_pMLModelId = a}) -- | Undocumented member. pRecord :: Lens' Predict (HashMap Text Text) -pRecord = lens _pRecord (\ s a -> s{_pRecord = a}) . _Map; +pRecord = lens _pRecord (\ s a -> s{_pRecord = a}) . _Map -- | Undocumented member. pPredictEndpoint :: Lens' Predict Text -pPredictEndpoint = lens _pPredictEndpoint (\ s a -> s{_pPredictEndpoint = a}); +pPredictEndpoint = lens _pPredictEndpoint (\ s a -> s{_pPredictEndpoint = a}) instance AWSRequest Predict where type Rs Predict = PredictResponse @@ -142,15 +142,15 @@ -> PredictResponse predictResponse pResponseStatus_ = PredictResponse' - {_prsPrediction = Nothing, _prsResponseStatus = pResponseStatus_} + {_prsPrediction = Nothing, _prsResponseStatus = pResponseStatus_} -- | Undocumented member. prsPrediction :: Lens' PredictResponse (Maybe Prediction) -prsPrediction = lens _prsPrediction (\ s a -> s{_prsPrediction = a}); +prsPrediction = lens _prsPrediction (\ s a -> s{_prsPrediction = a}) -- | -- | The response status code. prsResponseStatus :: Lens' PredictResponse Int -prsResponseStatus = lens _prsResponseStatus (\ s a -> s{_prsResponseStatus = a}); +prsResponseStatus = lens _prsResponseStatus (\ s a -> s{_prsResponseStatus = a}) instance NFData PredictResponse where diff --git a/gen/Network/AWS/MachineLearning/Types.hs b/gen/Network/AWS/MachineLearning/Types.hs --- a/gen/Network/AWS/MachineLearning/Types.hs +++ b/gen/Network/AWS/MachineLearning/Types.hs @@ -4,7 +4,7 @@ -- | -- Module : Network.AWS.MachineLearning.Types --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -254,24 +254,24 @@ machineLearning :: Service machineLearning = Service - { _svcAbbrev = "MachineLearning" - , _svcSigner = v4 - , _svcPrefix = "machinelearning" - , _svcVersion = "2014-12-12" - , _svcEndpoint = defaultEndpoint machineLearning - , _svcTimeout = Just 70 - , _svcCheck = statusSuccess - , _svcError = parseJSONError "MachineLearning" - , _svcRetry = retry - } + { _svcAbbrev = "MachineLearning" + , _svcSigner = v4 + , _svcPrefix = "machinelearning" + , _svcVersion = "2014-12-12" + , _svcEndpoint = defaultEndpoint machineLearning + , _svcTimeout = Just 70 + , _svcCheck = statusSuccess + , _svcError = parseJSONError "MachineLearning" + , _svcRetry = retry + } where retry = Exponential - { _retryBase = 5.0e-2 - , _retryGrowth = 2 - , _retryAttempts = 5 - , _retryCheck = check - } + { _retryBase = 5.0e-2 + , _retryGrowth = 2 + , _retryAttempts = 5 + , _retryCheck = check + } check e | has (hasCode "ThrottledException" . hasStatus 400) e = Just "throttled_exception" @@ -280,6 +280,8 @@ Just "throttling_exception" | has (hasCode "Throttling" . hasStatus 400) e = Just "throttling" | has (hasStatus 504) e = Just "gateway_timeout" + | has (hasCode "RequestThrottledException" . hasStatus 400) e = + Just "request_throttled_exception" | has (hasStatus 502) e = Just "bad_gateway" | has (hasStatus 503) e = Just "service_unavailable" | has (hasStatus 500) e = Just "general_server_error" diff --git a/gen/Network/AWS/MachineLearning/Types/Product.hs b/gen/Network/AWS/MachineLearning/Types/Product.hs --- a/gen/Network/AWS/MachineLearning/Types/Product.hs +++ b/gen/Network/AWS/MachineLearning/Types/Product.hs @@ -9,7 +9,7 @@ -- | -- Module : Network.AWS.MachineLearning.Types.Product --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -87,88 +87,88 @@ :: BatchPrediction batchPrediction = BatchPrediction' - { _bpStatus = Nothing - , _bpLastUpdatedAt = Nothing - , _bpCreatedAt = Nothing - , _bpComputeTime = Nothing - , _bpInputDataLocationS3 = Nothing - , _bpMLModelId = Nothing - , _bpBatchPredictionDataSourceId = Nothing - , _bpTotalRecordCount = Nothing - , _bpStartedAt = Nothing - , _bpBatchPredictionId = Nothing - , _bpFinishedAt = Nothing - , _bpInvalidRecordCount = Nothing - , _bpCreatedByIAMUser = Nothing - , _bpName = Nothing - , _bpMessage = Nothing - , _bpOutputURI = Nothing - } + { _bpStatus = Nothing + , _bpLastUpdatedAt = Nothing + , _bpCreatedAt = Nothing + , _bpComputeTime = Nothing + , _bpInputDataLocationS3 = Nothing + , _bpMLModelId = Nothing + , _bpBatchPredictionDataSourceId = Nothing + , _bpTotalRecordCount = Nothing + , _bpStartedAt = Nothing + , _bpBatchPredictionId = Nothing + , _bpFinishedAt = Nothing + , _bpInvalidRecordCount = Nothing + , _bpCreatedByIAMUser = Nothing + , _bpName = Nothing + , _bpMessage = Nothing + , _bpOutputURI = Nothing + } -- | The status of the @BatchPrediction@ . This element can have one of the following values: * @PENDING@ - Amazon Machine Learning (Amazon ML) submitted a request to generate predictions for a batch of observations. * @INPROGRESS@ - The process is underway. * @FAILED@ - The request to perform a batch prediction did not run to completion. It is not usable. * @COMPLETED@ - The batch prediction process completed successfully. * @DELETED@ - The @BatchPrediction@ is marked as deleted. It is not usable. bpStatus :: Lens' BatchPrediction (Maybe EntityStatus) -bpStatus = lens _bpStatus (\ s a -> s{_bpStatus = a}); +bpStatus = lens _bpStatus (\ s a -> s{_bpStatus = a}) -- | The time of the most recent edit to the @BatchPrediction@ . The time is expressed in epoch time. bpLastUpdatedAt :: Lens' BatchPrediction (Maybe UTCTime) -bpLastUpdatedAt = lens _bpLastUpdatedAt (\ s a -> s{_bpLastUpdatedAt = a}) . mapping _Time; +bpLastUpdatedAt = lens _bpLastUpdatedAt (\ s a -> s{_bpLastUpdatedAt = a}) . mapping _Time -- | The time that the @BatchPrediction@ was created. The time is expressed in epoch time. bpCreatedAt :: Lens' BatchPrediction (Maybe UTCTime) -bpCreatedAt = lens _bpCreatedAt (\ s a -> s{_bpCreatedAt = a}) . mapping _Time; +bpCreatedAt = lens _bpCreatedAt (\ s a -> s{_bpCreatedAt = a}) . mapping _Time -- | Undocumented member. bpComputeTime :: Lens' BatchPrediction (Maybe Integer) -bpComputeTime = lens _bpComputeTime (\ s a -> s{_bpComputeTime = a}); +bpComputeTime = lens _bpComputeTime (\ s a -> s{_bpComputeTime = a}) -- | The location of the data file or directory in Amazon Simple Storage Service (Amazon S3). bpInputDataLocationS3 :: Lens' BatchPrediction (Maybe Text) -bpInputDataLocationS3 = lens _bpInputDataLocationS3 (\ s a -> s{_bpInputDataLocationS3 = a}); +bpInputDataLocationS3 = lens _bpInputDataLocationS3 (\ s a -> s{_bpInputDataLocationS3 = a}) -- | The ID of the @MLModel@ that generated predictions for the @BatchPrediction@ request. bpMLModelId :: Lens' BatchPrediction (Maybe Text) -bpMLModelId = lens _bpMLModelId (\ s a -> s{_bpMLModelId = a}); +bpMLModelId = lens _bpMLModelId (\ s a -> s{_bpMLModelId = a}) -- | The ID of the @DataSource@ that points to the group of observations to predict. bpBatchPredictionDataSourceId :: Lens' BatchPrediction (Maybe Text) -bpBatchPredictionDataSourceId = lens _bpBatchPredictionDataSourceId (\ s a -> s{_bpBatchPredictionDataSourceId = a}); +bpBatchPredictionDataSourceId = lens _bpBatchPredictionDataSourceId (\ s a -> s{_bpBatchPredictionDataSourceId = a}) -- | Undocumented member. bpTotalRecordCount :: Lens' BatchPrediction (Maybe Integer) -bpTotalRecordCount = lens _bpTotalRecordCount (\ s a -> s{_bpTotalRecordCount = a}); +bpTotalRecordCount = lens _bpTotalRecordCount (\ s a -> s{_bpTotalRecordCount = a}) -- | Undocumented member. bpStartedAt :: Lens' BatchPrediction (Maybe UTCTime) -bpStartedAt = lens _bpStartedAt (\ s a -> s{_bpStartedAt = a}) . mapping _Time; +bpStartedAt = lens _bpStartedAt (\ s a -> s{_bpStartedAt = a}) . mapping _Time -- | The ID assigned to the @BatchPrediction@ at creation. This value should be identical to the value of the @BatchPredictionID@ in the request. bpBatchPredictionId :: Lens' BatchPrediction (Maybe Text) -bpBatchPredictionId = lens _bpBatchPredictionId (\ s a -> s{_bpBatchPredictionId = a}); +bpBatchPredictionId = lens _bpBatchPredictionId (\ s a -> s{_bpBatchPredictionId = a}) -- | Undocumented member. bpFinishedAt :: Lens' BatchPrediction (Maybe UTCTime) -bpFinishedAt = lens _bpFinishedAt (\ s a -> s{_bpFinishedAt = a}) . mapping _Time; +bpFinishedAt = lens _bpFinishedAt (\ s a -> s{_bpFinishedAt = a}) . mapping _Time -- | Undocumented member. bpInvalidRecordCount :: Lens' BatchPrediction (Maybe Integer) -bpInvalidRecordCount = lens _bpInvalidRecordCount (\ s a -> s{_bpInvalidRecordCount = a}); +bpInvalidRecordCount = lens _bpInvalidRecordCount (\ s a -> s{_bpInvalidRecordCount = a}) -- | The AWS user account that invoked the @BatchPrediction@ . The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account. bpCreatedByIAMUser :: Lens' BatchPrediction (Maybe Text) -bpCreatedByIAMUser = lens _bpCreatedByIAMUser (\ s a -> s{_bpCreatedByIAMUser = a}); +bpCreatedByIAMUser = lens _bpCreatedByIAMUser (\ s a -> s{_bpCreatedByIAMUser = a}) -- | A user-supplied name or description of the @BatchPrediction@ . bpName :: Lens' BatchPrediction (Maybe Text) -bpName = lens _bpName (\ s a -> s{_bpName = a}); +bpName = lens _bpName (\ s a -> s{_bpName = a}) -- | A description of the most recent details about processing the batch prediction request. bpMessage :: Lens' BatchPrediction (Maybe Text) -bpMessage = lens _bpMessage (\ s a -> s{_bpMessage = a}); +bpMessage = lens _bpMessage (\ s a -> s{_bpMessage = a}) -- | The location of an Amazon S3 bucket or directory to receive the operation results. The following substrings are not allowed in the @s3 key@ portion of the @outputURI@ field: ':', '//', '/./', '/../'. bpOutputURI :: Lens' BatchPrediction (Maybe Text) -bpOutputURI = lens _bpOutputURI (\ s a -> s{_bpOutputURI = a}); +bpOutputURI = lens _bpOutputURI (\ s a -> s{_bpOutputURI = a}) instance FromJSON BatchPrediction where parseJSON @@ -267,98 +267,98 @@ :: DataSource dataSource = DataSource' - { _dsStatus = Nothing - , _dsNumberOfFiles = Nothing - , _dsLastUpdatedAt = Nothing - , _dsCreatedAt = Nothing - , _dsComputeTime = Nothing - , _dsDataSourceId = Nothing - , _dsRDSMetadata = Nothing - , _dsDataSizeInBytes = Nothing - , _dsStartedAt = Nothing - , _dsFinishedAt = Nothing - , _dsCreatedByIAMUser = Nothing - , _dsName = Nothing - , _dsDataLocationS3 = Nothing - , _dsComputeStatistics = Nothing - , _dsMessage = Nothing - , _dsRedshiftMetadata = Nothing - , _dsDataRearrangement = Nothing - , _dsRoleARN = Nothing - } + { _dsStatus = Nothing + , _dsNumberOfFiles = Nothing + , _dsLastUpdatedAt = Nothing + , _dsCreatedAt = Nothing + , _dsComputeTime = Nothing + , _dsDataSourceId = Nothing + , _dsRDSMetadata = Nothing + , _dsDataSizeInBytes = Nothing + , _dsStartedAt = Nothing + , _dsFinishedAt = Nothing + , _dsCreatedByIAMUser = Nothing + , _dsName = Nothing + , _dsDataLocationS3 = Nothing + , _dsComputeStatistics = Nothing + , _dsMessage = Nothing + , _dsRedshiftMetadata = Nothing + , _dsDataRearrangement = Nothing + , _dsRoleARN = Nothing + } -- | The current status of the @DataSource@ . This element can have one of the following values: * PENDING - Amazon Machine Learning (Amazon ML) submitted a request to create a @DataSource@ . * INPROGRESS - The creation process is underway. * FAILED - The request to create a @DataSource@ did not run to completion. It is not usable. * COMPLETED - The creation process completed successfully. * DELETED - The @DataSource@ is marked as deleted. It is not usable. dsStatus :: Lens' DataSource (Maybe EntityStatus) -dsStatus = lens _dsStatus (\ s a -> s{_dsStatus = a}); +dsStatus = lens _dsStatus (\ s a -> s{_dsStatus = a}) -- | The number of data files referenced by the @DataSource@ . dsNumberOfFiles :: Lens' DataSource (Maybe Integer) -dsNumberOfFiles = lens _dsNumberOfFiles (\ s a -> s{_dsNumberOfFiles = a}); +dsNumberOfFiles = lens _dsNumberOfFiles (\ s a -> s{_dsNumberOfFiles = a}) -- | The time of the most recent edit to the @BatchPrediction@ . The time is expressed in epoch time. dsLastUpdatedAt :: Lens' DataSource (Maybe UTCTime) -dsLastUpdatedAt = lens _dsLastUpdatedAt (\ s a -> s{_dsLastUpdatedAt = a}) . mapping _Time; +dsLastUpdatedAt = lens _dsLastUpdatedAt (\ s a -> s{_dsLastUpdatedAt = a}) . mapping _Time -- | The time that the @DataSource@ was created. The time is expressed in epoch time. dsCreatedAt :: Lens' DataSource (Maybe UTCTime) -dsCreatedAt = lens _dsCreatedAt (\ s a -> s{_dsCreatedAt = a}) . mapping _Time; +dsCreatedAt = lens _dsCreatedAt (\ s a -> s{_dsCreatedAt = a}) . mapping _Time -- | Undocumented member. dsComputeTime :: Lens' DataSource (Maybe Integer) -dsComputeTime = lens _dsComputeTime (\ s a -> s{_dsComputeTime = a}); +dsComputeTime = lens _dsComputeTime (\ s a -> s{_dsComputeTime = a}) -- | The ID that is assigned to the @DataSource@ during creation. dsDataSourceId :: Lens' DataSource (Maybe Text) -dsDataSourceId = lens _dsDataSourceId (\ s a -> s{_dsDataSourceId = a}); +dsDataSourceId = lens _dsDataSourceId (\ s a -> s{_dsDataSourceId = a}) -- | Undocumented member. dsRDSMetadata :: Lens' DataSource (Maybe RDSMetadata) -dsRDSMetadata = lens _dsRDSMetadata (\ s a -> s{_dsRDSMetadata = a}); +dsRDSMetadata = lens _dsRDSMetadata (\ s a -> s{_dsRDSMetadata = a}) -- | The total number of observations contained in the data files that the @DataSource@ references. dsDataSizeInBytes :: Lens' DataSource (Maybe Integer) -dsDataSizeInBytes = lens _dsDataSizeInBytes (\ s a -> s{_dsDataSizeInBytes = a}); +dsDataSizeInBytes = lens _dsDataSizeInBytes (\ s a -> s{_dsDataSizeInBytes = a}) -- | Undocumented member. dsStartedAt :: Lens' DataSource (Maybe UTCTime) -dsStartedAt = lens _dsStartedAt (\ s a -> s{_dsStartedAt = a}) . mapping _Time; +dsStartedAt = lens _dsStartedAt (\ s a -> s{_dsStartedAt = a}) . mapping _Time -- | Undocumented member. dsFinishedAt :: Lens' DataSource (Maybe UTCTime) -dsFinishedAt = lens _dsFinishedAt (\ s a -> s{_dsFinishedAt = a}) . mapping _Time; +dsFinishedAt = lens _dsFinishedAt (\ s a -> s{_dsFinishedAt = a}) . mapping _Time -- | The AWS user account from which the @DataSource@ was created. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account. dsCreatedByIAMUser :: Lens' DataSource (Maybe Text) -dsCreatedByIAMUser = lens _dsCreatedByIAMUser (\ s a -> s{_dsCreatedByIAMUser = a}); +dsCreatedByIAMUser = lens _dsCreatedByIAMUser (\ s a -> s{_dsCreatedByIAMUser = a}) -- | A user-supplied name or description of the @DataSource@ . dsName :: Lens' DataSource (Maybe Text) -dsName = lens _dsName (\ s a -> s{_dsName = a}); +dsName = lens _dsName (\ s a -> s{_dsName = a}) -- | The location and name of the data in Amazon Simple Storage Service (Amazon S3) that is used by a @DataSource@ . dsDataLocationS3 :: Lens' DataSource (Maybe Text) -dsDataLocationS3 = lens _dsDataLocationS3 (\ s a -> s{_dsDataLocationS3 = a}); +dsDataLocationS3 = lens _dsDataLocationS3 (\ s a -> s{_dsDataLocationS3 = a}) -- | The parameter is @true@ if statistics need to be generated from the observation data. dsComputeStatistics :: Lens' DataSource (Maybe Bool) -dsComputeStatistics = lens _dsComputeStatistics (\ s a -> s{_dsComputeStatistics = a}); +dsComputeStatistics = lens _dsComputeStatistics (\ s a -> s{_dsComputeStatistics = a}) -- | A description of the most recent details about creating the @DataSource@ . dsMessage :: Lens' DataSource (Maybe Text) -dsMessage = lens _dsMessage (\ s a -> s{_dsMessage = a}); +dsMessage = lens _dsMessage (\ s a -> s{_dsMessage = a}) -- | Undocumented member. dsRedshiftMetadata :: Lens' DataSource (Maybe RedshiftMetadata) -dsRedshiftMetadata = lens _dsRedshiftMetadata (\ s a -> s{_dsRedshiftMetadata = a}); +dsRedshiftMetadata = lens _dsRedshiftMetadata (\ s a -> s{_dsRedshiftMetadata = a}) -- | A JSON string that represents the splitting and rearrangement requirement used when this @DataSource@ was created. dsDataRearrangement :: Lens' DataSource (Maybe Text) -dsDataRearrangement = lens _dsDataRearrangement (\ s a -> s{_dsDataRearrangement = a}); +dsDataRearrangement = lens _dsDataRearrangement (\ s a -> s{_dsDataRearrangement = a}) -- | Undocumented member. dsRoleARN :: Lens' DataSource (Maybe Text) -dsRoleARN = lens _dsRoleARN (\ s a -> s{_dsRoleARN = a}); +dsRoleARN = lens _dsRoleARN (\ s a -> s{_dsRoleARN = a}) instance FromJSON DataSource where parseJSON @@ -447,78 +447,78 @@ :: Evaluation evaluation = Evaluation' - { _eStatus = Nothing - , _ePerformanceMetrics = Nothing - , _eLastUpdatedAt = Nothing - , _eCreatedAt = Nothing - , _eComputeTime = Nothing - , _eInputDataLocationS3 = Nothing - , _eMLModelId = Nothing - , _eStartedAt = Nothing - , _eFinishedAt = Nothing - , _eCreatedByIAMUser = Nothing - , _eName = Nothing - , _eEvaluationId = Nothing - , _eMessage = Nothing - , _eEvaluationDataSourceId = Nothing - } + { _eStatus = Nothing + , _ePerformanceMetrics = Nothing + , _eLastUpdatedAt = Nothing + , _eCreatedAt = Nothing + , _eComputeTime = Nothing + , _eInputDataLocationS3 = Nothing + , _eMLModelId = Nothing + , _eStartedAt = Nothing + , _eFinishedAt = Nothing + , _eCreatedByIAMUser = Nothing + , _eName = Nothing + , _eEvaluationId = Nothing + , _eMessage = Nothing + , _eEvaluationDataSourceId = Nothing + } -- | The status of the evaluation. This element can have one of the following values: * @PENDING@ - Amazon Machine Learning (Amazon ML) submitted a request to evaluate an @MLModel@ . * @INPROGRESS@ - The evaluation is underway. * @FAILED@ - The request to evaluate an @MLModel@ did not run to completion. It is not usable. * @COMPLETED@ - The evaluation process completed successfully. * @DELETED@ - The @Evaluation@ is marked as deleted. It is not usable. eStatus :: Lens' Evaluation (Maybe EntityStatus) -eStatus = lens _eStatus (\ s a -> s{_eStatus = a}); +eStatus = lens _eStatus (\ s a -> s{_eStatus = a}) -- | Measurements of how well the @MLModel@ performed, using observations referenced by the @DataSource@ . One of the following metrics is returned, based on the type of the @MLModel@ : * BinaryAUC: A binary @MLModel@ uses the Area Under the Curve (AUC) technique to measure performance. * RegressionRMSE: A regression @MLModel@ uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable. * MulticlassAvgFScore: A multiclass @MLModel@ uses the F1 score technique to measure performance. For more information about performance metrics, please see the . ePerformanceMetrics :: Lens' Evaluation (Maybe PerformanceMetrics) -ePerformanceMetrics = lens _ePerformanceMetrics (\ s a -> s{_ePerformanceMetrics = a}); +ePerformanceMetrics = lens _ePerformanceMetrics (\ s a -> s{_ePerformanceMetrics = a}) -- | The time of the most recent edit to the @Evaluation@ . The time is expressed in epoch time. eLastUpdatedAt :: Lens' Evaluation (Maybe UTCTime) -eLastUpdatedAt = lens _eLastUpdatedAt (\ s a -> s{_eLastUpdatedAt = a}) . mapping _Time; +eLastUpdatedAt = lens _eLastUpdatedAt (\ s a -> s{_eLastUpdatedAt = a}) . mapping _Time -- | The time that the @Evaluation@ was created. The time is expressed in epoch time. eCreatedAt :: Lens' Evaluation (Maybe UTCTime) -eCreatedAt = lens _eCreatedAt (\ s a -> s{_eCreatedAt = a}) . mapping _Time; +eCreatedAt = lens _eCreatedAt (\ s a -> s{_eCreatedAt = a}) . mapping _Time -- | Undocumented member. eComputeTime :: Lens' Evaluation (Maybe Integer) -eComputeTime = lens _eComputeTime (\ s a -> s{_eComputeTime = a}); +eComputeTime = lens _eComputeTime (\ s a -> s{_eComputeTime = a}) -- | The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation. eInputDataLocationS3 :: Lens' Evaluation (Maybe Text) -eInputDataLocationS3 = lens _eInputDataLocationS3 (\ s a -> s{_eInputDataLocationS3 = a}); +eInputDataLocationS3 = lens _eInputDataLocationS3 (\ s a -> s{_eInputDataLocationS3 = a}) -- | The ID of the @MLModel@ that is the focus of the evaluation. eMLModelId :: Lens' Evaluation (Maybe Text) -eMLModelId = lens _eMLModelId (\ s a -> s{_eMLModelId = a}); +eMLModelId = lens _eMLModelId (\ s a -> s{_eMLModelId = a}) -- | Undocumented member. eStartedAt :: Lens' Evaluation (Maybe UTCTime) -eStartedAt = lens _eStartedAt (\ s a -> s{_eStartedAt = a}) . mapping _Time; +eStartedAt = lens _eStartedAt (\ s a -> s{_eStartedAt = a}) . mapping _Time -- | Undocumented member. eFinishedAt :: Lens' Evaluation (Maybe UTCTime) -eFinishedAt = lens _eFinishedAt (\ s a -> s{_eFinishedAt = a}) . mapping _Time; +eFinishedAt = lens _eFinishedAt (\ s a -> s{_eFinishedAt = a}) . mapping _Time -- | The AWS user account that invoked the evaluation. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account. eCreatedByIAMUser :: Lens' Evaluation (Maybe Text) -eCreatedByIAMUser = lens _eCreatedByIAMUser (\ s a -> s{_eCreatedByIAMUser = a}); +eCreatedByIAMUser = lens _eCreatedByIAMUser (\ s a -> s{_eCreatedByIAMUser = a}) -- | A user-supplied name or description of the @Evaluation@ . eName :: Lens' Evaluation (Maybe Text) -eName = lens _eName (\ s a -> s{_eName = a}); +eName = lens _eName (\ s a -> s{_eName = a}) -- | The ID that is assigned to the @Evaluation@ at creation. eEvaluationId :: Lens' Evaluation (Maybe Text) -eEvaluationId = lens _eEvaluationId (\ s a -> s{_eEvaluationId = a}); +eEvaluationId = lens _eEvaluationId (\ s a -> s{_eEvaluationId = a}) -- | A description of the most recent details about evaluating the @MLModel@ . eMessage :: Lens' Evaluation (Maybe Text) -eMessage = lens _eMessage (\ s a -> s{_eMessage = a}); +eMessage = lens _eMessage (\ s a -> s{_eMessage = a}) -- | The ID of the @DataSource@ that is used to evaluate the @MLModel@ . eEvaluationDataSourceId :: Lens' Evaluation (Maybe Text) -eEvaluationDataSourceId = lens _eEvaluationDataSourceId (\ s a -> s{_eEvaluationDataSourceId = a}); +eEvaluationDataSourceId = lens _eEvaluationDataSourceId (\ s a -> s{_eEvaluationDataSourceId = a}) instance FromJSON Evaluation where parseJSON @@ -618,103 +618,103 @@ :: MLModel mLModel = MLModel' - { _mlmStatus = Nothing - , _mlmLastUpdatedAt = Nothing - , _mlmTrainingParameters = Nothing - , _mlmScoreThresholdLastUpdatedAt = Nothing - , _mlmCreatedAt = Nothing - , _mlmComputeTime = Nothing - , _mlmInputDataLocationS3 = Nothing - , _mlmMLModelId = Nothing - , _mlmSizeInBytes = Nothing - , _mlmStartedAt = Nothing - , _mlmScoreThreshold = Nothing - , _mlmFinishedAt = Nothing - , _mlmAlgorithm = Nothing - , _mlmCreatedByIAMUser = Nothing - , _mlmName = Nothing - , _mlmEndpointInfo = Nothing - , _mlmTrainingDataSourceId = Nothing - , _mlmMessage = Nothing - , _mlmMLModelType = Nothing - } + { _mlmStatus = Nothing + , _mlmLastUpdatedAt = Nothing + , _mlmTrainingParameters = Nothing + , _mlmScoreThresholdLastUpdatedAt = Nothing + , _mlmCreatedAt = Nothing + , _mlmComputeTime = Nothing + , _mlmInputDataLocationS3 = Nothing + , _mlmMLModelId = Nothing + , _mlmSizeInBytes = Nothing + , _mlmStartedAt = Nothing + , _mlmScoreThreshold = Nothing + , _mlmFinishedAt = Nothing + , _mlmAlgorithm = Nothing + , _mlmCreatedByIAMUser = Nothing + , _mlmName = Nothing + , _mlmEndpointInfo = Nothing + , _mlmTrainingDataSourceId = Nothing + , _mlmMessage = Nothing + , _mlmMLModelType = Nothing + } -- | The current status of an @MLModel@ . This element can have one of the following values: * @PENDING@ - Amazon Machine Learning (Amazon ML) submitted a request to create an @MLModel@ . * @INPROGRESS@ - The creation process is underway. * @FAILED@ - The request to create an @MLModel@ didn't run to completion. The model isn't usable. * @COMPLETED@ - The creation process completed successfully. * @DELETED@ - The @MLModel@ is marked as deleted. It isn't usable. mlmStatus :: Lens' MLModel (Maybe EntityStatus) -mlmStatus = lens _mlmStatus (\ s a -> s{_mlmStatus = a}); +mlmStatus = lens _mlmStatus (\ s a -> s{_mlmStatus = a}) -- | The time of the most recent edit to the @MLModel@ . The time is expressed in epoch time. mlmLastUpdatedAt :: Lens' MLModel (Maybe UTCTime) -mlmLastUpdatedAt = lens _mlmLastUpdatedAt (\ s a -> s{_mlmLastUpdatedAt = a}) . mapping _Time; +mlmLastUpdatedAt = lens _mlmLastUpdatedAt (\ s a -> s{_mlmLastUpdatedAt = a}) . mapping _Time -- | A list of the training parameters in the @MLModel@ . The list is implemented as a map of key-value pairs. The following is the current set of training parameters: * @sgd.maxMLModelSizeInBytes@ - The maximum allowed size of the model. Depending on the input data, the size of the model might affect its performance. The value is an integer that ranges from @100000@ to @2147483648@ . The default value is @33554432@ . * @sgd.maxPasses@ - The number of times that the training process traverses the observations to build the @MLModel@ . The value is an integer that ranges from @1@ to @10000@ . The default value is @10@ . * @sgd.shuffleType@ - Whether Amazon ML shuffles the training data. Shuffling the data improves a model's ability to find the optimal solution for a variety of data types. The valid values are @auto@ and @none@ . The default value is @none@ . * @sgd.l1RegularizationAmount@ - The coefficient regularization L1 norm, which controls overfitting the data by penalizing large coefficients. This parameter tends to drive coefficients to zero, resulting in sparse feature set. If you use this parameter, start by specifying a small value, such as @1.0E-08@ . The value is a double that ranges from @0@ to @MAX_DOUBLE@ . The default is to not use L1 normalization. This parameter can't be used when @L2@ is specified. Use this parameter sparingly. * @sgd.l2RegularizationAmount@ - The coefficient regularization L2 norm, which controls overfitting the data by penalizing large coefficients. This tends to drive coefficients to small, nonzero values. If you use this parameter, start by specifying a small value, such as @1.0E-08@ . The value is a double that ranges from @0@ to @MAX_DOUBLE@ . The default is to not use L2 normalization. This parameter can't be used when @L1@ is specified. Use this parameter sparingly. mlmTrainingParameters :: Lens' MLModel (HashMap Text Text) -mlmTrainingParameters = lens _mlmTrainingParameters (\ s a -> s{_mlmTrainingParameters = a}) . _Default . _Map; +mlmTrainingParameters = lens _mlmTrainingParameters (\ s a -> s{_mlmTrainingParameters = a}) . _Default . _Map -- | The time of the most recent edit to the @ScoreThreshold@ . The time is expressed in epoch time. mlmScoreThresholdLastUpdatedAt :: Lens' MLModel (Maybe UTCTime) -mlmScoreThresholdLastUpdatedAt = lens _mlmScoreThresholdLastUpdatedAt (\ s a -> s{_mlmScoreThresholdLastUpdatedAt = a}) . mapping _Time; +mlmScoreThresholdLastUpdatedAt = lens _mlmScoreThresholdLastUpdatedAt (\ s a -> s{_mlmScoreThresholdLastUpdatedAt = a}) . mapping _Time -- | The time that the @MLModel@ was created. The time is expressed in epoch time. mlmCreatedAt :: Lens' MLModel (Maybe UTCTime) -mlmCreatedAt = lens _mlmCreatedAt (\ s a -> s{_mlmCreatedAt = a}) . mapping _Time; +mlmCreatedAt = lens _mlmCreatedAt (\ s a -> s{_mlmCreatedAt = a}) . mapping _Time -- | Undocumented member. mlmComputeTime :: Lens' MLModel (Maybe Integer) -mlmComputeTime = lens _mlmComputeTime (\ s a -> s{_mlmComputeTime = a}); +mlmComputeTime = lens _mlmComputeTime (\ s a -> s{_mlmComputeTime = a}) -- | The location of the data file or directory in Amazon Simple Storage Service (Amazon S3). mlmInputDataLocationS3 :: Lens' MLModel (Maybe Text) -mlmInputDataLocationS3 = lens _mlmInputDataLocationS3 (\ s a -> s{_mlmInputDataLocationS3 = a}); +mlmInputDataLocationS3 = lens _mlmInputDataLocationS3 (\ s a -> s{_mlmInputDataLocationS3 = a}) -- | The ID assigned to the @MLModel@ at creation. mlmMLModelId :: Lens' MLModel (Maybe Text) -mlmMLModelId = lens _mlmMLModelId (\ s a -> s{_mlmMLModelId = a}); +mlmMLModelId = lens _mlmMLModelId (\ s a -> s{_mlmMLModelId = a}) -- | Undocumented member. mlmSizeInBytes :: Lens' MLModel (Maybe Integer) -mlmSizeInBytes = lens _mlmSizeInBytes (\ s a -> s{_mlmSizeInBytes = a}); +mlmSizeInBytes = lens _mlmSizeInBytes (\ s a -> s{_mlmSizeInBytes = a}) -- | Undocumented member. mlmStartedAt :: Lens' MLModel (Maybe UTCTime) -mlmStartedAt = lens _mlmStartedAt (\ s a -> s{_mlmStartedAt = a}) . mapping _Time; +mlmStartedAt = lens _mlmStartedAt (\ s a -> s{_mlmStartedAt = a}) . mapping _Time -- | Undocumented member. mlmScoreThreshold :: Lens' MLModel (Maybe Double) -mlmScoreThreshold = lens _mlmScoreThreshold (\ s a -> s{_mlmScoreThreshold = a}); +mlmScoreThreshold = lens _mlmScoreThreshold (\ s a -> s{_mlmScoreThreshold = a}) -- | Undocumented member. mlmFinishedAt :: Lens' MLModel (Maybe UTCTime) -mlmFinishedAt = lens _mlmFinishedAt (\ s a -> s{_mlmFinishedAt = a}) . mapping _Time; +mlmFinishedAt = lens _mlmFinishedAt (\ s a -> s{_mlmFinishedAt = a}) . mapping _Time -- | The algorithm used to train the @MLModel@ . The following algorithm is supported: * @SGD@ -- Stochastic gradient descent. The goal of @SGD@ is to minimize the gradient of the loss function. mlmAlgorithm :: Lens' MLModel (Maybe Algorithm) -mlmAlgorithm = lens _mlmAlgorithm (\ s a -> s{_mlmAlgorithm = a}); +mlmAlgorithm = lens _mlmAlgorithm (\ s a -> s{_mlmAlgorithm = a}) -- | The AWS user account from which the @MLModel@ was created. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account. mlmCreatedByIAMUser :: Lens' MLModel (Maybe Text) -mlmCreatedByIAMUser = lens _mlmCreatedByIAMUser (\ s a -> s{_mlmCreatedByIAMUser = a}); +mlmCreatedByIAMUser = lens _mlmCreatedByIAMUser (\ s a -> s{_mlmCreatedByIAMUser = a}) -- | A user-supplied name or description of the @MLModel@ . mlmName :: Lens' MLModel (Maybe Text) -mlmName = lens _mlmName (\ s a -> s{_mlmName = a}); +mlmName = lens _mlmName (\ s a -> s{_mlmName = a}) -- | The current endpoint of the @MLModel@ . mlmEndpointInfo :: Lens' MLModel (Maybe RealtimeEndpointInfo) -mlmEndpointInfo = lens _mlmEndpointInfo (\ s a -> s{_mlmEndpointInfo = a}); +mlmEndpointInfo = lens _mlmEndpointInfo (\ s a -> s{_mlmEndpointInfo = a}) -- | The ID of the training @DataSource@ . The @CreateMLModel@ operation uses the @TrainingDataSourceId@ . mlmTrainingDataSourceId :: Lens' MLModel (Maybe Text) -mlmTrainingDataSourceId = lens _mlmTrainingDataSourceId (\ s a -> s{_mlmTrainingDataSourceId = a}); +mlmTrainingDataSourceId = lens _mlmTrainingDataSourceId (\ s a -> s{_mlmTrainingDataSourceId = a}) -- | A description of the most recent details about accessing the @MLModel@ . mlmMessage :: Lens' MLModel (Maybe Text) -mlmMessage = lens _mlmMessage (\ s a -> s{_mlmMessage = a}); +mlmMessage = lens _mlmMessage (\ s a -> s{_mlmMessage = a}) -- | Identifies the @MLModel@ category. The following are the available types: * @REGRESSION@ - Produces a numeric result. For example, "What price should a house be listed at?" * @BINARY@ - Produces one of two possible results. For example, "Is this a child-friendly web site?". * @MULTICLASS@ - Produces one of several possible results. For example, "Is this a HIGH-, LOW-, or MEDIUM-risk trade?". mlmMLModelType :: Lens' MLModel (Maybe MLModelType) -mlmMLModelType = lens _mlmMLModelType (\ s a -> s{_mlmMLModelType = a}); +mlmMLModelType = lens _mlmMLModelType (\ s a -> s{_mlmMLModelType = a}) instance FromJSON MLModel where parseJSON @@ -776,7 +776,7 @@ -- | Undocumented member. pmProperties :: Lens' PerformanceMetrics (HashMap Text Text) -pmProperties = lens _pmProperties (\ s a -> s{_pmProperties = a}) . _Default . _Map; +pmProperties = lens _pmProperties (\ s a -> s{_pmProperties = a}) . _Default . _Map instance FromJSON PerformanceMetrics where parseJSON @@ -827,28 +827,28 @@ :: Prediction prediction = Prediction' - { _pPredictedValue = Nothing - , _pPredictedLabel = Nothing - , _pPredictedScores = Nothing - , _pDetails = Nothing - } + { _pPredictedValue = Nothing + , _pPredictedLabel = Nothing + , _pPredictedScores = Nothing + , _pDetails = Nothing + } -- | The prediction value for @REGRESSION@ @MLModel@ . pPredictedValue :: Lens' Prediction (Maybe Double) -pPredictedValue = lens _pPredictedValue (\ s a -> s{_pPredictedValue = a}); +pPredictedValue = lens _pPredictedValue (\ s a -> s{_pPredictedValue = a}) -- | The prediction label for either a @BINARY@ or @MULTICLASS@ @MLModel@ . pPredictedLabel :: Lens' Prediction (Maybe Text) -pPredictedLabel = lens _pPredictedLabel (\ s a -> s{_pPredictedLabel = a}); +pPredictedLabel = lens _pPredictedLabel (\ s a -> s{_pPredictedLabel = a}) -- | Undocumented member. pPredictedScores :: Lens' Prediction (HashMap Text Double) -pPredictedScores = lens _pPredictedScores (\ s a -> s{_pPredictedScores = a}) . _Default . _Map; +pPredictedScores = lens _pPredictedScores (\ s a -> s{_pPredictedScores = a}) . _Default . _Map -- | Undocumented member. pDetails :: Lens' Prediction (HashMap DetailsAttributes Text) -pDetails = lens _pDetails (\ s a -> s{_pDetails = a}) . _Default . _Map; +pDetails = lens _pDetails (\ s a -> s{_pDetails = a}) . _Default . _Map instance FromJSON Prediction where parseJSON @@ -919,63 +919,63 @@ -> RDSDataSpec rdsDataSpec pDatabaseInformation_ pSelectSqlQuery_ pDatabaseCredentials_ pS3StagingLocation_ pResourceRole_ pServiceRole_ pSubnetId_ = RDSDataSpec' - { _rdsdsDataSchemaURI = Nothing - , _rdsdsDataSchema = Nothing - , _rdsdsDataRearrangement = Nothing - , _rdsdsDatabaseInformation = pDatabaseInformation_ - , _rdsdsSelectSqlQuery = pSelectSqlQuery_ - , _rdsdsDatabaseCredentials = pDatabaseCredentials_ - , _rdsdsS3StagingLocation = pS3StagingLocation_ - , _rdsdsResourceRole = pResourceRole_ - , _rdsdsServiceRole = pServiceRole_ - , _rdsdsSubnetId = pSubnetId_ - , _rdsdsSecurityGroupIds = mempty - } + { _rdsdsDataSchemaURI = Nothing + , _rdsdsDataSchema = Nothing + , _rdsdsDataRearrangement = Nothing + , _rdsdsDatabaseInformation = pDatabaseInformation_ + , _rdsdsSelectSqlQuery = pSelectSqlQuery_ + , _rdsdsDatabaseCredentials = pDatabaseCredentials_ + , _rdsdsS3StagingLocation = pS3StagingLocation_ + , _rdsdsResourceRole = pResourceRole_ + , _rdsdsServiceRole = pServiceRole_ + , _rdsdsSubnetId = pSubnetId_ + , _rdsdsSecurityGroupIds = mempty + } -- | The Amazon S3 location of the @DataSchema@ . rdsdsDataSchemaURI :: Lens' RDSDataSpec (Maybe Text) -rdsdsDataSchemaURI = lens _rdsdsDataSchemaURI (\ s a -> s{_rdsdsDataSchemaURI = a}); +rdsdsDataSchemaURI = lens _rdsdsDataSchemaURI (\ s a -> s{_rdsdsDataSchemaURI = a}) -- | A JSON string that represents the schema for an Amazon RDS @DataSource@ . The @DataSchema@ defines the structure of the observation data in the data file(s) referenced in the @DataSource@ . A @DataSchema@ is not required if you specify a @DataSchemaUri@ Define your @DataSchema@ as a series of key-value pairs. @attributes@ and @excludedVariableNames@ have an array of key-value pairs for their value. Use the following format to define your @DataSchema@ . { "version": "1.0", "recordAnnotationFieldName": "F1", "recordWeightFieldName": "F2", "targetFieldName": "F3", "dataFormat": "CSV", "dataFileContainsHeader": true, "attributes": [ { "fieldName": "F1", "fieldType": "TEXT" }, { "fieldName": "F2", "fieldType": "NUMERIC" }, { "fieldName": "F3", "fieldType": "CATEGORICAL" }, { "fieldName": "F4", "fieldType": "NUMERIC" }, { "fieldName": "F5", "fieldType": "CATEGORICAL" }, { "fieldName": "F6", "fieldType": "TEXT" }, { "fieldName": "F7", "fieldType": "WEIGHTED_INT_SEQUENCE" }, { "fieldName": "F8", "fieldType": "WEIGHTED_STRING_SEQUENCE" } ], "excludedVariableNames": [ "F6" ] } rdsdsDataSchema :: Lens' RDSDataSpec (Maybe Text) -rdsdsDataSchema = lens _rdsdsDataSchema (\ s a -> s{_rdsdsDataSchema = a}); +rdsdsDataSchema = lens _rdsdsDataSchema (\ s a -> s{_rdsdsDataSchema = a}) -- | A JSON string that represents the splitting and rearrangement processing to be applied to a @DataSource@ . If the @DataRearrangement@ parameter is not provided, all of the input data is used to create the @Datasource@ . There are multiple parameters that control what data is used to create a datasource: * __@percentBegin@ __ Use @percentBegin@ to indicate the beginning of the range of the data used to create the Datasource. If you do not include @percentBegin@ and @percentEnd@ , Amazon ML includes all of the data when creating the datasource. * __@percentEnd@ __ Use @percentEnd@ to indicate the end of the range of the data used to create the Datasource. If you do not include @percentBegin@ and @percentEnd@ , Amazon ML includes all of the data when creating the datasource. * __@complement@ __ The @complement@ parameter instructs Amazon ML to use the data that is not included in the range of @percentBegin@ to @percentEnd@ to create a datasource. The @complement@ parameter is useful if you need to create complementary datasources for training and evaluation. To create a complementary datasource, use the same values for @percentBegin@ and @percentEnd@ , along with the @complement@ parameter. For example, the following two datasources do not share any data, and can be used to train and evaluate a model. The first datasource has 25 percent of the data, and the second one has 75 percent of the data. Datasource for evaluation: @{"splitting":{"percentBegin":0, "percentEnd":25}}@ Datasource for training: @{"splitting":{"percentBegin":0, "percentEnd":25, "complement":"true"}}@ * __@strategy@ __ To change how Amazon ML splits the data for a datasource, use the @strategy@ parameter. The default value for the @strategy@ parameter is @sequential@ , meaning that Amazon ML takes all of the data records between the @percentBegin@ and @percentEnd@ parameters for the datasource, in the order that the records appear in the input data. The following two @DataRearrangement@ lines are examples of sequentially ordered training and evaluation datasources: Datasource for evaluation: @{"splitting":{"percentBegin":70, "percentEnd":100, "strategy":"sequential"}}@ Datasource for training: @{"splitting":{"percentBegin":70, "percentEnd":100, "strategy":"sequential", "complement":"true"}}@ To randomly split the input data into the proportions indicated by the percentBegin and percentEnd parameters, set the @strategy@ parameter to @random@ and provide a string that is used as the seed value for the random data splitting (for example, you can use the S3 path to your data as the random seed string). If you choose the random split strategy, Amazon ML assigns each row of data a pseudo-random number between 0 and 100, and then selects the rows that have an assigned number between @percentBegin@ and @percentEnd@ . Pseudo-random numbers are assigned using both the input seed string value and the byte offset as a seed, so changing the data results in a different split. Any existing ordering is preserved. The random splitting strategy ensures that variables in the training and evaluation data are distributed similarly. It is useful in the cases where the input data may have an implicit sort order, which would otherwise result in training and evaluation datasources containing non-similar data records. The following two @DataRearrangement@ lines are examples of non-sequentially ordered training and evaluation datasources: Datasource for evaluation: @{"splitting":{"percentBegin":70, "percentEnd":100, "strategy":"random", "randomSeed"="s3://my_s3_path/bucket/file.csv"}}@ Datasource for training: @{"splitting":{"percentBegin":70, "percentEnd":100, "strategy":"random", "randomSeed"="s3://my_s3_path/bucket/file.csv", "complement":"true"}}@ rdsdsDataRearrangement :: Lens' RDSDataSpec (Maybe Text) -rdsdsDataRearrangement = lens _rdsdsDataRearrangement (\ s a -> s{_rdsdsDataRearrangement = a}); +rdsdsDataRearrangement = lens _rdsdsDataRearrangement (\ s a -> s{_rdsdsDataRearrangement = a}) -- | Describes the @DatabaseName@ and @InstanceIdentifier@ of an Amazon RDS database. rdsdsDatabaseInformation :: Lens' RDSDataSpec RDSDatabase -rdsdsDatabaseInformation = lens _rdsdsDatabaseInformation (\ s a -> s{_rdsdsDatabaseInformation = a}); +rdsdsDatabaseInformation = lens _rdsdsDatabaseInformation (\ s a -> s{_rdsdsDatabaseInformation = a}) -- | The query that is used to retrieve the observation data for the @DataSource@ . rdsdsSelectSqlQuery :: Lens' RDSDataSpec Text -rdsdsSelectSqlQuery = lens _rdsdsSelectSqlQuery (\ s a -> s{_rdsdsSelectSqlQuery = a}); +rdsdsSelectSqlQuery = lens _rdsdsSelectSqlQuery (\ s a -> s{_rdsdsSelectSqlQuery = a}) -- | The AWS Identity and Access Management (IAM) credentials that are used connect to the Amazon RDS database. rdsdsDatabaseCredentials :: Lens' RDSDataSpec RDSDatabaseCredentials -rdsdsDatabaseCredentials = lens _rdsdsDatabaseCredentials (\ s a -> s{_rdsdsDatabaseCredentials = a}); +rdsdsDatabaseCredentials = lens _rdsdsDatabaseCredentials (\ s a -> s{_rdsdsDatabaseCredentials = a}) -- | The Amazon S3 location for staging Amazon RDS data. The data retrieved from Amazon RDS using @SelectSqlQuery@ is stored in this location. rdsdsS3StagingLocation :: Lens' RDSDataSpec Text -rdsdsS3StagingLocation = lens _rdsdsS3StagingLocation (\ s a -> s{_rdsdsS3StagingLocation = a}); +rdsdsS3StagingLocation = lens _rdsdsS3StagingLocation (\ s a -> s{_rdsdsS3StagingLocation = a}) -- | The role (DataPipelineDefaultResourceRole) assumed by an Amazon Elastic Compute Cloud (Amazon EC2) instance to carry out the copy operation from Amazon RDS to an Amazon S3 task. For more information, see for data pipelines. rdsdsResourceRole :: Lens' RDSDataSpec Text -rdsdsResourceRole = lens _rdsdsResourceRole (\ s a -> s{_rdsdsResourceRole = a}); +rdsdsResourceRole = lens _rdsdsResourceRole (\ s a -> s{_rdsdsResourceRole = a}) -- | The role (DataPipelineDefaultRole) assumed by AWS Data Pipeline service to monitor the progress of the copy task from Amazon RDS to Amazon S3. For more information, see for data pipelines. rdsdsServiceRole :: Lens' RDSDataSpec Text -rdsdsServiceRole = lens _rdsdsServiceRole (\ s a -> s{_rdsdsServiceRole = a}); +rdsdsServiceRole = lens _rdsdsServiceRole (\ s a -> s{_rdsdsServiceRole = a}) -- | The subnet ID to be used to access a VPC-based RDS DB instance. This attribute is used by Data Pipeline to carry out the copy task from Amazon RDS to Amazon S3. rdsdsSubnetId :: Lens' RDSDataSpec Text -rdsdsSubnetId = lens _rdsdsSubnetId (\ s a -> s{_rdsdsSubnetId = a}); +rdsdsSubnetId = lens _rdsdsSubnetId (\ s a -> s{_rdsdsSubnetId = a}) -- | The security group IDs to be used to access a VPC-based RDS DB instance. Ensure that there are appropriate ingress rules set up to allow access to the RDS DB instance. This attribute is used by Data Pipeline to carry out the copy operation from Amazon RDS to an Amazon S3 task. rdsdsSecurityGroupIds :: Lens' RDSDataSpec [Text] -rdsdsSecurityGroupIds = lens _rdsdsSecurityGroupIds (\ s a -> s{_rdsdsSecurityGroupIds = a}) . _Coerce; +rdsdsSecurityGroupIds = lens _rdsdsSecurityGroupIds (\ s a -> s{_rdsdsSecurityGroupIds = a}) . _Coerce instance Hashable RDSDataSpec where @@ -1024,18 +1024,18 @@ -> RDSDatabase rdsDatabase pInstanceIdentifier_ pDatabaseName_ = RDSDatabase' - { _rdsdInstanceIdentifier = pInstanceIdentifier_ - , _rdsdDatabaseName = pDatabaseName_ - } + { _rdsdInstanceIdentifier = pInstanceIdentifier_ + , _rdsdDatabaseName = pDatabaseName_ + } -- | The ID of an RDS DB instance. rdsdInstanceIdentifier :: Lens' RDSDatabase Text -rdsdInstanceIdentifier = lens _rdsdInstanceIdentifier (\ s a -> s{_rdsdInstanceIdentifier = a}); +rdsdInstanceIdentifier = lens _rdsdInstanceIdentifier (\ s a -> s{_rdsdInstanceIdentifier = a}) -- | Undocumented member. rdsdDatabaseName :: Lens' RDSDatabase Text -rdsdDatabaseName = lens _rdsdDatabaseName (\ s a -> s{_rdsdDatabaseName = a}); +rdsdDatabaseName = lens _rdsdDatabaseName (\ s a -> s{_rdsdDatabaseName = a}) instance FromJSON RDSDatabase where parseJSON @@ -1081,16 +1081,16 @@ -> RDSDatabaseCredentials rdsDatabaseCredentials pUsername_ pPassword_ = RDSDatabaseCredentials' - {_rdsdcUsername = pUsername_, _rdsdcPassword = pPassword_} + {_rdsdcUsername = pUsername_, _rdsdcPassword = pPassword_} -- | Undocumented member. rdsdcUsername :: Lens' RDSDatabaseCredentials Text -rdsdcUsername = lens _rdsdcUsername (\ s a -> s{_rdsdcUsername = a}); +rdsdcUsername = lens _rdsdcUsername (\ s a -> s{_rdsdcUsername = a}) -- | Undocumented member. rdsdcPassword :: Lens' RDSDatabaseCredentials Text -rdsdcPassword = lens _rdsdcPassword (\ s a -> s{_rdsdcPassword = a}); +rdsdcPassword = lens _rdsdcPassword (\ s a -> s{_rdsdcPassword = a}) instance Hashable RDSDatabaseCredentials where @@ -1137,38 +1137,38 @@ :: RDSMetadata rdsMetadata = RDSMetadata' - { _rmSelectSqlQuery = Nothing - , _rmDataPipelineId = Nothing - , _rmDatabase = Nothing - , _rmDatabaseUserName = Nothing - , _rmResourceRole = Nothing - , _rmServiceRole = Nothing - } + { _rmSelectSqlQuery = Nothing + , _rmDataPipelineId = Nothing + , _rmDatabase = Nothing + , _rmDatabaseUserName = Nothing + , _rmResourceRole = Nothing + , _rmServiceRole = Nothing + } -- | The SQL query that is supplied during 'CreateDataSourceFromRDS' . Returns only if @Verbose@ is true in @GetDataSourceInput@ . rmSelectSqlQuery :: Lens' RDSMetadata (Maybe Text) -rmSelectSqlQuery = lens _rmSelectSqlQuery (\ s a -> s{_rmSelectSqlQuery = a}); +rmSelectSqlQuery = lens _rmSelectSqlQuery (\ s a -> s{_rmSelectSqlQuery = a}) -- | The ID of the Data Pipeline instance that is used to carry to copy data from Amazon RDS to Amazon S3. You can use the ID to find details about the instance in the Data Pipeline console. rmDataPipelineId :: Lens' RDSMetadata (Maybe Text) -rmDataPipelineId = lens _rmDataPipelineId (\ s a -> s{_rmDataPipelineId = a}); +rmDataPipelineId = lens _rmDataPipelineId (\ s a -> s{_rmDataPipelineId = a}) -- | The database details required to connect to an Amazon RDS. rmDatabase :: Lens' RDSMetadata (Maybe RDSDatabase) -rmDatabase = lens _rmDatabase (\ s a -> s{_rmDatabase = a}); +rmDatabase = lens _rmDatabase (\ s a -> s{_rmDatabase = a}) -- | Undocumented member. rmDatabaseUserName :: Lens' RDSMetadata (Maybe Text) -rmDatabaseUserName = lens _rmDatabaseUserName (\ s a -> s{_rmDatabaseUserName = a}); +rmDatabaseUserName = lens _rmDatabaseUserName (\ s a -> s{_rmDatabaseUserName = a}) -- | The role (DataPipelineDefaultResourceRole) assumed by an Amazon EC2 instance to carry out the copy task from Amazon RDS to Amazon S3. For more information, see for data pipelines. rmResourceRole :: Lens' RDSMetadata (Maybe Text) -rmResourceRole = lens _rmResourceRole (\ s a -> s{_rmResourceRole = a}); +rmResourceRole = lens _rmResourceRole (\ s a -> s{_rmResourceRole = a}) -- | The role (DataPipelineDefaultRole) assumed by the Data Pipeline service to monitor the progress of the copy task from Amazon RDS to Amazon S3. For more information, see for data pipelines. rmServiceRole :: Lens' RDSMetadata (Maybe Text) -rmServiceRole = lens _rmServiceRole (\ s a -> s{_rmServiceRole = a}); +rmServiceRole = lens _rmServiceRole (\ s a -> s{_rmServiceRole = a}) instance FromJSON RDSMetadata where parseJSON @@ -1213,28 +1213,28 @@ :: RealtimeEndpointInfo realtimeEndpointInfo = RealtimeEndpointInfo' - { _reiCreatedAt = Nothing - , _reiEndpointURL = Nothing - , _reiEndpointStatus = Nothing - , _reiPeakRequestsPerSecond = Nothing - } + { _reiCreatedAt = Nothing + , _reiEndpointURL = Nothing + , _reiEndpointStatus = Nothing + , _reiPeakRequestsPerSecond = Nothing + } -- | The time that the request to create the real-time endpoint for the @MLModel@ was received. The time is expressed in epoch time. reiCreatedAt :: Lens' RealtimeEndpointInfo (Maybe UTCTime) -reiCreatedAt = lens _reiCreatedAt (\ s a -> s{_reiCreatedAt = a}) . mapping _Time; +reiCreatedAt = lens _reiCreatedAt (\ s a -> s{_reiCreatedAt = a}) . mapping _Time -- | The URI that specifies where to send real-time prediction requests for the @MLModel@ . reiEndpointURL :: Lens' RealtimeEndpointInfo (Maybe Text) -reiEndpointURL = lens _reiEndpointURL (\ s a -> s{_reiEndpointURL = a}); +reiEndpointURL = lens _reiEndpointURL (\ s a -> s{_reiEndpointURL = a}) -- | The current status of the real-time endpoint for the @MLModel@ . This element can have one of the following values: * @NONE@ - Endpoint does not exist or was previously deleted. * @READY@ - Endpoint is ready to be used for real-time predictions. * @UPDATING@ - Updating/creating the endpoint. reiEndpointStatus :: Lens' RealtimeEndpointInfo (Maybe RealtimeEndpointStatus) -reiEndpointStatus = lens _reiEndpointStatus (\ s a -> s{_reiEndpointStatus = a}); +reiEndpointStatus = lens _reiEndpointStatus (\ s a -> s{_reiEndpointStatus = a}) -- | The maximum processing rate for the real-time endpoint for @MLModel@ , measured in incoming requests per second. reiPeakRequestsPerSecond :: Lens' RealtimeEndpointInfo (Maybe Int) -reiPeakRequestsPerSecond = lens _reiPeakRequestsPerSecond (\ s a -> s{_reiPeakRequestsPerSecond = a}); +reiPeakRequestsPerSecond = lens _reiPeakRequestsPerSecond (\ s a -> s{_reiPeakRequestsPerSecond = a}) instance FromJSON RealtimeEndpointInfo where parseJSON @@ -1290,43 +1290,43 @@ -> RedshiftDataSpec redshiftDataSpec pDatabaseInformation_ pSelectSqlQuery_ pDatabaseCredentials_ pS3StagingLocation_ = RedshiftDataSpec' - { _rDataSchemaURI = Nothing - , _rDataSchema = Nothing - , _rDataRearrangement = Nothing - , _rDatabaseInformation = pDatabaseInformation_ - , _rSelectSqlQuery = pSelectSqlQuery_ - , _rDatabaseCredentials = pDatabaseCredentials_ - , _rS3StagingLocation = pS3StagingLocation_ - } + { _rDataSchemaURI = Nothing + , _rDataSchema = Nothing + , _rDataRearrangement = Nothing + , _rDatabaseInformation = pDatabaseInformation_ + , _rSelectSqlQuery = pSelectSqlQuery_ + , _rDatabaseCredentials = pDatabaseCredentials_ + , _rS3StagingLocation = pS3StagingLocation_ + } -- | Describes the schema location for an Amazon Redshift @DataSource@ . rDataSchemaURI :: Lens' RedshiftDataSpec (Maybe Text) -rDataSchemaURI = lens _rDataSchemaURI (\ s a -> s{_rDataSchemaURI = a}); +rDataSchemaURI = lens _rDataSchemaURI (\ s a -> s{_rDataSchemaURI = a}) -- | A JSON string that represents the schema for an Amazon Redshift @DataSource@ . The @DataSchema@ defines the structure of the observation data in the data file(s) referenced in the @DataSource@ . A @DataSchema@ is not required if you specify a @DataSchemaUri@ . Define your @DataSchema@ as a series of key-value pairs. @attributes@ and @excludedVariableNames@ have an array of key-value pairs for their value. Use the following format to define your @DataSchema@ . { "version": "1.0", "recordAnnotationFieldName": "F1", "recordWeightFieldName": "F2", "targetFieldName": "F3", "dataFormat": "CSV", "dataFileContainsHeader": true, "attributes": [ { "fieldName": "F1", "fieldType": "TEXT" }, { "fieldName": "F2", "fieldType": "NUMERIC" }, { "fieldName": "F3", "fieldType": "CATEGORICAL" }, { "fieldName": "F4", "fieldType": "NUMERIC" }, { "fieldName": "F5", "fieldType": "CATEGORICAL" }, { "fieldName": "F6", "fieldType": "TEXT" }, { "fieldName": "F7", "fieldType": "WEIGHTED_INT_SEQUENCE" }, { "fieldName": "F8", "fieldType": "WEIGHTED_STRING_SEQUENCE" } ], "excludedVariableNames": [ "F6" ] } rDataSchema :: Lens' RedshiftDataSpec (Maybe Text) -rDataSchema = lens _rDataSchema (\ s a -> s{_rDataSchema = a}); +rDataSchema = lens _rDataSchema (\ s a -> s{_rDataSchema = a}) -- | A JSON string that represents the splitting and rearrangement processing to be applied to a @DataSource@ . If the @DataRearrangement@ parameter is not provided, all of the input data is used to create the @Datasource@ . There are multiple parameters that control what data is used to create a datasource: * __@percentBegin@ __ Use @percentBegin@ to indicate the beginning of the range of the data used to create the Datasource. If you do not include @percentBegin@ and @percentEnd@ , Amazon ML includes all of the data when creating the datasource. * __@percentEnd@ __ Use @percentEnd@ to indicate the end of the range of the data used to create the Datasource. If you do not include @percentBegin@ and @percentEnd@ , Amazon ML includes all of the data when creating the datasource. * __@complement@ __ The @complement@ parameter instructs Amazon ML to use the data that is not included in the range of @percentBegin@ to @percentEnd@ to create a datasource. The @complement@ parameter is useful if you need to create complementary datasources for training and evaluation. To create a complementary datasource, use the same values for @percentBegin@ and @percentEnd@ , along with the @complement@ parameter. For example, the following two datasources do not share any data, and can be used to train and evaluate a model. The first datasource has 25 percent of the data, and the second one has 75 percent of the data. Datasource for evaluation: @{"splitting":{"percentBegin":0, "percentEnd":25}}@ Datasource for training: @{"splitting":{"percentBegin":0, "percentEnd":25, "complement":"true"}}@ * __@strategy@ __ To change how Amazon ML splits the data for a datasource, use the @strategy@ parameter. The default value for the @strategy@ parameter is @sequential@ , meaning that Amazon ML takes all of the data records between the @percentBegin@ and @percentEnd@ parameters for the datasource, in the order that the records appear in the input data. The following two @DataRearrangement@ lines are examples of sequentially ordered training and evaluation datasources: Datasource for evaluation: @{"splitting":{"percentBegin":70, "percentEnd":100, "strategy":"sequential"}}@ Datasource for training: @{"splitting":{"percentBegin":70, "percentEnd":100, "strategy":"sequential", "complement":"true"}}@ To randomly split the input data into the proportions indicated by the percentBegin and percentEnd parameters, set the @strategy@ parameter to @random@ and provide a string that is used as the seed value for the random data splitting (for example, you can use the S3 path to your data as the random seed string). If you choose the random split strategy, Amazon ML assigns each row of data a pseudo-random number between 0 and 100, and then selects the rows that have an assigned number between @percentBegin@ and @percentEnd@ . Pseudo-random numbers are assigned using both the input seed string value and the byte offset as a seed, so changing the data results in a different split. Any existing ordering is preserved. The random splitting strategy ensures that variables in the training and evaluation data are distributed similarly. It is useful in the cases where the input data may have an implicit sort order, which would otherwise result in training and evaluation datasources containing non-similar data records. The following two @DataRearrangement@ lines are examples of non-sequentially ordered training and evaluation datasources: Datasource for evaluation: @{"splitting":{"percentBegin":70, "percentEnd":100, "strategy":"random", "randomSeed"="s3://my_s3_path/bucket/file.csv"}}@ Datasource for training: @{"splitting":{"percentBegin":70, "percentEnd":100, "strategy":"random", "randomSeed"="s3://my_s3_path/bucket/file.csv", "complement":"true"}}@ rDataRearrangement :: Lens' RedshiftDataSpec (Maybe Text) -rDataRearrangement = lens _rDataRearrangement (\ s a -> s{_rDataRearrangement = a}); +rDataRearrangement = lens _rDataRearrangement (\ s a -> s{_rDataRearrangement = a}) -- | Describes the @DatabaseName@ and @ClusterIdentifier@ for an Amazon Redshift @DataSource@ . rDatabaseInformation :: Lens' RedshiftDataSpec RedshiftDatabase -rDatabaseInformation = lens _rDatabaseInformation (\ s a -> s{_rDatabaseInformation = a}); +rDatabaseInformation = lens _rDatabaseInformation (\ s a -> s{_rDatabaseInformation = a}) -- | Describes the SQL Query to execute on an Amazon Redshift database for an Amazon Redshift @DataSource@ . rSelectSqlQuery :: Lens' RedshiftDataSpec Text -rSelectSqlQuery = lens _rSelectSqlQuery (\ s a -> s{_rSelectSqlQuery = a}); +rSelectSqlQuery = lens _rSelectSqlQuery (\ s a -> s{_rSelectSqlQuery = a}) -- | Describes AWS Identity and Access Management (IAM) credentials that are used connect to the Amazon Redshift database. rDatabaseCredentials :: Lens' RedshiftDataSpec RedshiftDatabaseCredentials -rDatabaseCredentials = lens _rDatabaseCredentials (\ s a -> s{_rDatabaseCredentials = a}); +rDatabaseCredentials = lens _rDatabaseCredentials (\ s a -> s{_rDatabaseCredentials = a}) -- | Describes an Amazon S3 location to store the result set of the @SelectSqlQuery@ query. rS3StagingLocation :: Lens' RedshiftDataSpec Text -rS3StagingLocation = lens _rS3StagingLocation (\ s a -> s{_rS3StagingLocation = a}); +rS3StagingLocation = lens _rS3StagingLocation (\ s a -> s{_rS3StagingLocation = a}) instance Hashable RedshiftDataSpec where @@ -1370,16 +1370,18 @@ -> RedshiftDatabase redshiftDatabase pDatabaseName_ pClusterIdentifier_ = RedshiftDatabase' - {_rdDatabaseName = pDatabaseName_, _rdClusterIdentifier = pClusterIdentifier_} + { _rdDatabaseName = pDatabaseName_ + , _rdClusterIdentifier = pClusterIdentifier_ + } -- | Undocumented member. rdDatabaseName :: Lens' RedshiftDatabase Text -rdDatabaseName = lens _rdDatabaseName (\ s a -> s{_rdDatabaseName = a}); +rdDatabaseName = lens _rdDatabaseName (\ s a -> s{_rdDatabaseName = a}) -- | Undocumented member. rdClusterIdentifier :: Lens' RedshiftDatabase Text -rdClusterIdentifier = lens _rdClusterIdentifier (\ s a -> s{_rdClusterIdentifier = a}); +rdClusterIdentifier = lens _rdClusterIdentifier (\ s a -> s{_rdClusterIdentifier = a}) instance FromJSON RedshiftDatabase where parseJSON @@ -1423,16 +1425,16 @@ -> RedshiftDatabaseCredentials redshiftDatabaseCredentials pUsername_ pPassword_ = RedshiftDatabaseCredentials' - {_rdcUsername = pUsername_, _rdcPassword = pPassword_} + {_rdcUsername = pUsername_, _rdcPassword = pPassword_} -- | Undocumented member. rdcUsername :: Lens' RedshiftDatabaseCredentials Text -rdcUsername = lens _rdcUsername (\ s a -> s{_rdcUsername = a}); +rdcUsername = lens _rdcUsername (\ s a -> s{_rdcUsername = a}) -- | Undocumented member. rdcPassword :: Lens' RedshiftDatabaseCredentials Text -rdcPassword = lens _rdcPassword (\ s a -> s{_rdcPassword = a}); +rdcPassword = lens _rdcPassword (\ s a -> s{_rdcPassword = a}) instance Hashable RedshiftDatabaseCredentials where @@ -1470,23 +1472,23 @@ :: RedshiftMetadata redshiftMetadata = RedshiftMetadata' - { _redSelectSqlQuery = Nothing - , _redRedshiftDatabase = Nothing - , _redDatabaseUserName = Nothing - } + { _redSelectSqlQuery = Nothing + , _redRedshiftDatabase = Nothing + , _redDatabaseUserName = Nothing + } -- | The SQL query that is specified during 'CreateDataSourceFromRedshift' . Returns only if @Verbose@ is true in GetDataSourceInput. redSelectSqlQuery :: Lens' RedshiftMetadata (Maybe Text) -redSelectSqlQuery = lens _redSelectSqlQuery (\ s a -> s{_redSelectSqlQuery = a}); +redSelectSqlQuery = lens _redSelectSqlQuery (\ s a -> s{_redSelectSqlQuery = a}) -- | Undocumented member. redRedshiftDatabase :: Lens' RedshiftMetadata (Maybe RedshiftDatabase) -redRedshiftDatabase = lens _redRedshiftDatabase (\ s a -> s{_redRedshiftDatabase = a}); +redRedshiftDatabase = lens _redRedshiftDatabase (\ s a -> s{_redRedshiftDatabase = a}) -- | Undocumented member. redDatabaseUserName :: Lens' RedshiftMetadata (Maybe Text) -redDatabaseUserName = lens _redDatabaseUserName (\ s a -> s{_redDatabaseUserName = a}); +redDatabaseUserName = lens _redDatabaseUserName (\ s a -> s{_redDatabaseUserName = a}) instance FromJSON RedshiftMetadata where parseJSON @@ -1530,28 +1532,28 @@ -> S3DataSpec s3DataSpec pDataLocationS3_ = S3DataSpec' - { _sdsDataSchema = Nothing - , _sdsDataSchemaLocationS3 = Nothing - , _sdsDataRearrangement = Nothing - , _sdsDataLocationS3 = pDataLocationS3_ - } + { _sdsDataSchema = Nothing + , _sdsDataSchemaLocationS3 = Nothing + , _sdsDataRearrangement = Nothing + , _sdsDataLocationS3 = pDataLocationS3_ + } -- | A JSON string that represents the schema for an Amazon S3 @DataSource@ . The @DataSchema@ defines the structure of the observation data in the data file(s) referenced in the @DataSource@ . You must provide either the @DataSchema@ or the @DataSchemaLocationS3@ . Define your @DataSchema@ as a series of key-value pairs. @attributes@ and @excludedVariableNames@ have an array of key-value pairs for their value. Use the following format to define your @DataSchema@ . { "version": "1.0", "recordAnnotationFieldName": "F1", "recordWeightFieldName": "F2", "targetFieldName": "F3", "dataFormat": "CSV", "dataFileContainsHeader": true, "attributes": [ { "fieldName": "F1", "fieldType": "TEXT" }, { "fieldName": "F2", "fieldType": "NUMERIC" }, { "fieldName": "F3", "fieldType": "CATEGORICAL" }, { "fieldName": "F4", "fieldType": "NUMERIC" }, { "fieldName": "F5", "fieldType": "CATEGORICAL" }, { "fieldName": "F6", "fieldType": "TEXT" }, { "fieldName": "F7", "fieldType": "WEIGHTED_INT_SEQUENCE" }, { "fieldName": "F8", "fieldType": "WEIGHTED_STRING_SEQUENCE" } ], "excludedVariableNames": [ "F6" ] } sdsDataSchema :: Lens' S3DataSpec (Maybe Text) -sdsDataSchema = lens _sdsDataSchema (\ s a -> s{_sdsDataSchema = a}); +sdsDataSchema = lens _sdsDataSchema (\ s a -> s{_sdsDataSchema = a}) -- | Describes the schema location in Amazon S3. You must provide either the @DataSchema@ or the @DataSchemaLocationS3@ . sdsDataSchemaLocationS3 :: Lens' S3DataSpec (Maybe Text) -sdsDataSchemaLocationS3 = lens _sdsDataSchemaLocationS3 (\ s a -> s{_sdsDataSchemaLocationS3 = a}); +sdsDataSchemaLocationS3 = lens _sdsDataSchemaLocationS3 (\ s a -> s{_sdsDataSchemaLocationS3 = a}) -- | A JSON string that represents the splitting and rearrangement processing to be applied to a @DataSource@ . If the @DataRearrangement@ parameter is not provided, all of the input data is used to create the @Datasource@ . There are multiple parameters that control what data is used to create a datasource: * __@percentBegin@ __ Use @percentBegin@ to indicate the beginning of the range of the data used to create the Datasource. If you do not include @percentBegin@ and @percentEnd@ , Amazon ML includes all of the data when creating the datasource. * __@percentEnd@ __ Use @percentEnd@ to indicate the end of the range of the data used to create the Datasource. If you do not include @percentBegin@ and @percentEnd@ , Amazon ML includes all of the data when creating the datasource. * __@complement@ __ The @complement@ parameter instructs Amazon ML to use the data that is not included in the range of @percentBegin@ to @percentEnd@ to create a datasource. The @complement@ parameter is useful if you need to create complementary datasources for training and evaluation. To create a complementary datasource, use the same values for @percentBegin@ and @percentEnd@ , along with the @complement@ parameter. For example, the following two datasources do not share any data, and can be used to train and evaluate a model. The first datasource has 25 percent of the data, and the second one has 75 percent of the data. Datasource for evaluation: @{"splitting":{"percentBegin":0, "percentEnd":25}}@ Datasource for training: @{"splitting":{"percentBegin":0, "percentEnd":25, "complement":"true"}}@ * __@strategy@ __ To change how Amazon ML splits the data for a datasource, use the @strategy@ parameter. The default value for the @strategy@ parameter is @sequential@ , meaning that Amazon ML takes all of the data records between the @percentBegin@ and @percentEnd@ parameters for the datasource, in the order that the records appear in the input data. The following two @DataRearrangement@ lines are examples of sequentially ordered training and evaluation datasources: Datasource for evaluation: @{"splitting":{"percentBegin":70, "percentEnd":100, "strategy":"sequential"}}@ Datasource for training: @{"splitting":{"percentBegin":70, "percentEnd":100, "strategy":"sequential", "complement":"true"}}@ To randomly split the input data into the proportions indicated by the percentBegin and percentEnd parameters, set the @strategy@ parameter to @random@ and provide a string that is used as the seed value for the random data splitting (for example, you can use the S3 path to your data as the random seed string). If you choose the random split strategy, Amazon ML assigns each row of data a pseudo-random number between 0 and 100, and then selects the rows that have an assigned number between @percentBegin@ and @percentEnd@ . Pseudo-random numbers are assigned using both the input seed string value and the byte offset as a seed, so changing the data results in a different split. Any existing ordering is preserved. The random splitting strategy ensures that variables in the training and evaluation data are distributed similarly. It is useful in the cases where the input data may have an implicit sort order, which would otherwise result in training and evaluation datasources containing non-similar data records. The following two @DataRearrangement@ lines are examples of non-sequentially ordered training and evaluation datasources: Datasource for evaluation: @{"splitting":{"percentBegin":70, "percentEnd":100, "strategy":"random", "randomSeed"="s3://my_s3_path/bucket/file.csv"}}@ Datasource for training: @{"splitting":{"percentBegin":70, "percentEnd":100, "strategy":"random", "randomSeed"="s3://my_s3_path/bucket/file.csv", "complement":"true"}}@ sdsDataRearrangement :: Lens' S3DataSpec (Maybe Text) -sdsDataRearrangement = lens _sdsDataRearrangement (\ s a -> s{_sdsDataRearrangement = a}); +sdsDataRearrangement = lens _sdsDataRearrangement (\ s a -> s{_sdsDataRearrangement = a}) -- | The location of the data file(s) used by a @DataSource@ . The URI specifies a data file or an Amazon Simple Storage Service (Amazon S3) directory or bucket containing data files. sdsDataLocationS3 :: Lens' S3DataSpec Text -sdsDataLocationS3 = lens _sdsDataLocationS3 (\ s a -> s{_sdsDataLocationS3 = a}); +sdsDataLocationS3 = lens _sdsDataLocationS3 (\ s a -> s{_sdsDataLocationS3 = a}) instance Hashable S3DataSpec where @@ -1592,11 +1594,11 @@ -- | An optional string, typically used to describe or define the tag. Valid characters include Unicode letters, digits, white space, _, ., /, =, +, -, %, and @. tagValue :: Lens' Tag (Maybe Text) -tagValue = lens _tagValue (\ s a -> s{_tagValue = a}); +tagValue = lens _tagValue (\ s a -> s{_tagValue = a}) -- | A unique identifier for the tag. Valid characters include Unicode letters, digits, white space, _, ., /, =, +, -, %, and @. tagKey :: Lens' Tag (Maybe Text) -tagKey = lens _tagKey (\ s a -> s{_tagKey = a}); +tagKey = lens _tagKey (\ s a -> s{_tagKey = a}) instance FromJSON Tag where parseJSON diff --git a/gen/Network/AWS/MachineLearning/Types/Sum.hs b/gen/Network/AWS/MachineLearning/Types/Sum.hs --- a/gen/Network/AWS/MachineLearning/Types/Sum.hs +++ b/gen/Network/AWS/MachineLearning/Types/Sum.hs @@ -9,7 +9,7 @@ -- | -- Module : Network.AWS.MachineLearning.Types.Sum --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated diff --git a/gen/Network/AWS/MachineLearning/UpdateBatchPrediction.hs b/gen/Network/AWS/MachineLearning/UpdateBatchPrediction.hs --- a/gen/Network/AWS/MachineLearning/UpdateBatchPrediction.hs +++ b/gen/Network/AWS/MachineLearning/UpdateBatchPrediction.hs @@ -12,7 +12,7 @@ -- | -- Module : Network.AWS.MachineLearning.UpdateBatchPrediction --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -67,18 +67,18 @@ -> UpdateBatchPrediction updateBatchPrediction pBatchPredictionId_ pBatchPredictionName_ = UpdateBatchPrediction' - { _ubpBatchPredictionId = pBatchPredictionId_ - , _ubpBatchPredictionName = pBatchPredictionName_ - } + { _ubpBatchPredictionId = pBatchPredictionId_ + , _ubpBatchPredictionName = pBatchPredictionName_ + } -- | The ID assigned to the @BatchPrediction@ during creation. ubpBatchPredictionId :: Lens' UpdateBatchPrediction Text -ubpBatchPredictionId = lens _ubpBatchPredictionId (\ s a -> s{_ubpBatchPredictionId = a}); +ubpBatchPredictionId = lens _ubpBatchPredictionId (\ s a -> s{_ubpBatchPredictionId = a}) -- | A new user-supplied name or description of the @BatchPrediction@ . ubpBatchPredictionName :: Lens' UpdateBatchPrediction Text -ubpBatchPredictionName = lens _ubpBatchPredictionName (\ s a -> s{_ubpBatchPredictionName = a}); +ubpBatchPredictionName = lens _ubpBatchPredictionName (\ s a -> s{_ubpBatchPredictionName = a}) instance AWSRequest UpdateBatchPrediction where type Rs UpdateBatchPrediction = @@ -143,15 +143,15 @@ -> UpdateBatchPredictionResponse updateBatchPredictionResponse pResponseStatus_ = UpdateBatchPredictionResponse' - {_ubprsBatchPredictionId = Nothing, _ubprsResponseStatus = pResponseStatus_} + {_ubprsBatchPredictionId = Nothing, _ubprsResponseStatus = pResponseStatus_} -- | The ID assigned to the @BatchPrediction@ during creation. This value should be identical to the value of the @BatchPredictionId@ in the request. ubprsBatchPredictionId :: Lens' UpdateBatchPredictionResponse (Maybe Text) -ubprsBatchPredictionId = lens _ubprsBatchPredictionId (\ s a -> s{_ubprsBatchPredictionId = a}); +ubprsBatchPredictionId = lens _ubprsBatchPredictionId (\ s a -> s{_ubprsBatchPredictionId = a}) -- | -- | The response status code. ubprsResponseStatus :: Lens' UpdateBatchPredictionResponse Int -ubprsResponseStatus = lens _ubprsResponseStatus (\ s a -> s{_ubprsResponseStatus = a}); +ubprsResponseStatus = lens _ubprsResponseStatus (\ s a -> s{_ubprsResponseStatus = a}) instance NFData UpdateBatchPredictionResponse where diff --git a/gen/Network/AWS/MachineLearning/UpdateDataSource.hs b/gen/Network/AWS/MachineLearning/UpdateDataSource.hs --- a/gen/Network/AWS/MachineLearning/UpdateDataSource.hs +++ b/gen/Network/AWS/MachineLearning/UpdateDataSource.hs @@ -12,7 +12,7 @@ -- | -- Module : Network.AWS.MachineLearning.UpdateDataSource --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -67,16 +67,16 @@ -> UpdateDataSource updateDataSource pDataSourceId_ pDataSourceName_ = UpdateDataSource' - {_udsDataSourceId = pDataSourceId_, _udsDataSourceName = pDataSourceName_} + {_udsDataSourceId = pDataSourceId_, _udsDataSourceName = pDataSourceName_} -- | The ID assigned to the @DataSource@ during creation. udsDataSourceId :: Lens' UpdateDataSource Text -udsDataSourceId = lens _udsDataSourceId (\ s a -> s{_udsDataSourceId = a}); +udsDataSourceId = lens _udsDataSourceId (\ s a -> s{_udsDataSourceId = a}) -- | A new user-supplied name or description of the @DataSource@ that will replace the current description. udsDataSourceName :: Lens' UpdateDataSource Text -udsDataSourceName = lens _udsDataSourceName (\ s a -> s{_udsDataSourceName = a}); +udsDataSourceName = lens _udsDataSourceName (\ s a -> s{_udsDataSourceName = a}) instance AWSRequest UpdateDataSource where type Rs UpdateDataSource = UpdateDataSourceResponse @@ -138,15 +138,15 @@ -> UpdateDataSourceResponse updateDataSourceResponse pResponseStatus_ = UpdateDataSourceResponse' - {_udsrsDataSourceId = Nothing, _udsrsResponseStatus = pResponseStatus_} + {_udsrsDataSourceId = Nothing, _udsrsResponseStatus = pResponseStatus_} -- | The ID assigned to the @DataSource@ during creation. This value should be identical to the value of the @DataSourceID@ in the request. udsrsDataSourceId :: Lens' UpdateDataSourceResponse (Maybe Text) -udsrsDataSourceId = lens _udsrsDataSourceId (\ s a -> s{_udsrsDataSourceId = a}); +udsrsDataSourceId = lens _udsrsDataSourceId (\ s a -> s{_udsrsDataSourceId = a}) -- | -- | The response status code. udsrsResponseStatus :: Lens' UpdateDataSourceResponse Int -udsrsResponseStatus = lens _udsrsResponseStatus (\ s a -> s{_udsrsResponseStatus = a}); +udsrsResponseStatus = lens _udsrsResponseStatus (\ s a -> s{_udsrsResponseStatus = a}) instance NFData UpdateDataSourceResponse where diff --git a/gen/Network/AWS/MachineLearning/UpdateEvaluation.hs b/gen/Network/AWS/MachineLearning/UpdateEvaluation.hs --- a/gen/Network/AWS/MachineLearning/UpdateEvaluation.hs +++ b/gen/Network/AWS/MachineLearning/UpdateEvaluation.hs @@ -12,7 +12,7 @@ -- | -- Module : Network.AWS.MachineLearning.UpdateEvaluation --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -67,16 +67,16 @@ -> UpdateEvaluation updateEvaluation pEvaluationId_ pEvaluationName_ = UpdateEvaluation' - {_ueEvaluationId = pEvaluationId_, _ueEvaluationName = pEvaluationName_} + {_ueEvaluationId = pEvaluationId_, _ueEvaluationName = pEvaluationName_} -- | The ID assigned to the @Evaluation@ during creation. ueEvaluationId :: Lens' UpdateEvaluation Text -ueEvaluationId = lens _ueEvaluationId (\ s a -> s{_ueEvaluationId = a}); +ueEvaluationId = lens _ueEvaluationId (\ s a -> s{_ueEvaluationId = a}) -- | A new user-supplied name or description of the @Evaluation@ that will replace the current content. ueEvaluationName :: Lens' UpdateEvaluation Text -ueEvaluationName = lens _ueEvaluationName (\ s a -> s{_ueEvaluationName = a}); +ueEvaluationName = lens _ueEvaluationName (\ s a -> s{_ueEvaluationName = a}) instance AWSRequest UpdateEvaluation where type Rs UpdateEvaluation = UpdateEvaluationResponse @@ -138,15 +138,15 @@ -> UpdateEvaluationResponse updateEvaluationResponse pResponseStatus_ = UpdateEvaluationResponse' - {_uersEvaluationId = Nothing, _uersResponseStatus = pResponseStatus_} + {_uersEvaluationId = Nothing, _uersResponseStatus = pResponseStatus_} -- | The ID assigned to the @Evaluation@ during creation. This value should be identical to the value of the @Evaluation@ in the request. uersEvaluationId :: Lens' UpdateEvaluationResponse (Maybe Text) -uersEvaluationId = lens _uersEvaluationId (\ s a -> s{_uersEvaluationId = a}); +uersEvaluationId = lens _uersEvaluationId (\ s a -> s{_uersEvaluationId = a}) -- | -- | The response status code. uersResponseStatus :: Lens' UpdateEvaluationResponse Int -uersResponseStatus = lens _uersResponseStatus (\ s a -> s{_uersResponseStatus = a}); +uersResponseStatus = lens _uersResponseStatus (\ s a -> s{_uersResponseStatus = a}) instance NFData UpdateEvaluationResponse where diff --git a/gen/Network/AWS/MachineLearning/UpdateMLModel.hs b/gen/Network/AWS/MachineLearning/UpdateMLModel.hs --- a/gen/Network/AWS/MachineLearning/UpdateMLModel.hs +++ b/gen/Network/AWS/MachineLearning/UpdateMLModel.hs @@ -12,7 +12,7 @@ -- | -- Module : Network.AWS.MachineLearning.UpdateMLModel --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -70,23 +70,23 @@ -> UpdateMLModel updateMLModel pMLModelId_ = UpdateMLModel' - { _umlmMLModelName = Nothing - , _umlmScoreThreshold = Nothing - , _umlmMLModelId = pMLModelId_ - } + { _umlmMLModelName = Nothing + , _umlmScoreThreshold = Nothing + , _umlmMLModelId = pMLModelId_ + } -- | A user-supplied name or description of the @MLModel@ . umlmMLModelName :: Lens' UpdateMLModel (Maybe Text) -umlmMLModelName = lens _umlmMLModelName (\ s a -> s{_umlmMLModelName = a}); +umlmMLModelName = lens _umlmMLModelName (\ s a -> s{_umlmMLModelName = a}) -- | The @ScoreThreshold@ used in binary classification @MLModel@ that marks the boundary between a positive prediction and a negative prediction. Output values greater than or equal to the @ScoreThreshold@ receive a positive result from the @MLModel@ , such as @true@ . Output values less than the @ScoreThreshold@ receive a negative response from the @MLModel@ , such as @false@ . umlmScoreThreshold :: Lens' UpdateMLModel (Maybe Double) -umlmScoreThreshold = lens _umlmScoreThreshold (\ s a -> s{_umlmScoreThreshold = a}); +umlmScoreThreshold = lens _umlmScoreThreshold (\ s a -> s{_umlmScoreThreshold = a}) -- | The ID assigned to the @MLModel@ during creation. umlmMLModelId :: Lens' UpdateMLModel Text -umlmMLModelId = lens _umlmMLModelId (\ s a -> s{_umlmMLModelId = a}); +umlmMLModelId = lens _umlmMLModelId (\ s a -> s{_umlmMLModelId = a}) instance AWSRequest UpdateMLModel where type Rs UpdateMLModel = UpdateMLModelResponse @@ -149,15 +149,15 @@ -> UpdateMLModelResponse updateMLModelResponse pResponseStatus_ = UpdateMLModelResponse' - {_umlmrsMLModelId = Nothing, _umlmrsResponseStatus = pResponseStatus_} + {_umlmrsMLModelId = Nothing, _umlmrsResponseStatus = pResponseStatus_} -- | The ID assigned to the @MLModel@ during creation. This value should be identical to the value of the @MLModelID@ in the request. umlmrsMLModelId :: Lens' UpdateMLModelResponse (Maybe Text) -umlmrsMLModelId = lens _umlmrsMLModelId (\ s a -> s{_umlmrsMLModelId = a}); +umlmrsMLModelId = lens _umlmrsMLModelId (\ s a -> s{_umlmrsMLModelId = a}) -- | -- | The response status code. umlmrsResponseStatus :: Lens' UpdateMLModelResponse Int -umlmrsResponseStatus = lens _umlmrsResponseStatus (\ s a -> s{_umlmrsResponseStatus = a}); +umlmrsResponseStatus = lens _umlmrsResponseStatus (\ s a -> s{_umlmrsResponseStatus = a}) instance NFData UpdateMLModelResponse where diff --git a/gen/Network/AWS/MachineLearning/Waiters.hs b/gen/Network/AWS/MachineLearning/Waiters.hs --- a/gen/Network/AWS/MachineLearning/Waiters.hs +++ b/gen/Network/AWS/MachineLearning/Waiters.hs @@ -7,7 +7,7 @@ -- | -- Module : Network.AWS.MachineLearning.Waiters --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated @@ -28,78 +28,78 @@ mLModelAvailable :: Wait DescribeMLModels mLModelAvailable = Wait - { _waitName = "MLModelAvailable" - , _waitAttempts = 60 - , _waitDelay = 30 - , _waitAcceptors = - [ matchAll - "COMPLETED" - AcceptSuccess - (folding (concatOf dmlmsrsResults) . mlmStatus . _Just . to toTextCI) - , matchAny - "FAILED" - AcceptFailure - (folding (concatOf dmlmsrsResults) . mlmStatus . _Just . to toTextCI) - ] - } + { _waitName = "MLModelAvailable" + , _waitAttempts = 60 + , _waitDelay = 30 + , _waitAcceptors = + [ matchAll + "COMPLETED" + AcceptSuccess + (folding (concatOf dmlmsrsResults) . mlmStatus . _Just . to toTextCI) + , matchAny + "FAILED" + AcceptFailure + (folding (concatOf dmlmsrsResults) . mlmStatus . _Just . to toTextCI) + ] + } -- | Polls 'Network.AWS.MachineLearning.DescribeBatchPredictions' every 30 seconds until a successful state is reached. An error is returned after 60 failed checks. batchPredictionAvailable :: Wait DescribeBatchPredictions batchPredictionAvailable = Wait - { _waitName = "BatchPredictionAvailable" - , _waitAttempts = 60 - , _waitDelay = 30 - , _waitAcceptors = - [ matchAll - "COMPLETED" - AcceptSuccess - (folding (concatOf dbpsrsResults) . bpStatus . _Just . to toTextCI) - , matchAny - "FAILED" - AcceptFailure - (folding (concatOf dbpsrsResults) . bpStatus . _Just . to toTextCI) - ] - } + { _waitName = "BatchPredictionAvailable" + , _waitAttempts = 60 + , _waitDelay = 30 + , _waitAcceptors = + [ matchAll + "COMPLETED" + AcceptSuccess + (folding (concatOf dbpsrsResults) . bpStatus . _Just . to toTextCI) + , matchAny + "FAILED" + AcceptFailure + (folding (concatOf dbpsrsResults) . bpStatus . _Just . to toTextCI) + ] + } -- | Polls 'Network.AWS.MachineLearning.DescribeDataSources' every 30 seconds until a successful state is reached. An error is returned after 60 failed checks. dataSourceAvailable :: Wait DescribeDataSources dataSourceAvailable = Wait - { _waitName = "DataSourceAvailable" - , _waitAttempts = 60 - , _waitDelay = 30 - , _waitAcceptors = - [ matchAll - "COMPLETED" - AcceptSuccess - (folding (concatOf ddssrsResults) . dsStatus . _Just . to toTextCI) - , matchAny - "FAILED" - AcceptFailure - (folding (concatOf ddssrsResults) . dsStatus . _Just . to toTextCI) - ] - } + { _waitName = "DataSourceAvailable" + , _waitAttempts = 60 + , _waitDelay = 30 + , _waitAcceptors = + [ matchAll + "COMPLETED" + AcceptSuccess + (folding (concatOf ddssrsResults) . dsStatus . _Just . to toTextCI) + , matchAny + "FAILED" + AcceptFailure + (folding (concatOf ddssrsResults) . dsStatus . _Just . to toTextCI) + ] + } -- | Polls 'Network.AWS.MachineLearning.DescribeEvaluations' every 30 seconds until a successful state is reached. An error is returned after 60 failed checks. evaluationAvailable :: Wait DescribeEvaluations evaluationAvailable = Wait - { _waitName = "EvaluationAvailable" - , _waitAttempts = 60 - , _waitDelay = 30 - , _waitAcceptors = - [ matchAll - "COMPLETED" - AcceptSuccess - (folding (concatOf desrsResults) . eStatus . _Just . to toTextCI) - , matchAny - "FAILED" - AcceptFailure - (folding (concatOf desrsResults) . eStatus . _Just . to toTextCI) - ] - } + { _waitName = "EvaluationAvailable" + , _waitAttempts = 60 + , _waitDelay = 30 + , _waitAcceptors = + [ matchAll + "COMPLETED" + AcceptSuccess + (folding (concatOf desrsResults) . eStatus . _Just . to toTextCI) + , matchAny + "FAILED" + AcceptFailure + (folding (concatOf desrsResults) . eStatus . _Just . to toTextCI) + ] + } diff --git a/test/Main.hs b/test/Main.hs --- a/test/Main.hs +++ b/test/Main.hs @@ -2,7 +2,7 @@ -- | -- Module : Main --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated diff --git a/test/Test/AWS/Gen/MachineLearning.hs b/test/Test/AWS/Gen/MachineLearning.hs --- a/test/Test/AWS/Gen/MachineLearning.hs +++ b/test/Test/AWS/Gen/MachineLearning.hs @@ -5,7 +5,7 @@ -- | -- Module : Test.AWS.Gen.MachineLearning --- Copyright : (c) 2013-2017 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : Mozilla Public License, v. 2.0. -- Maintainer : Brendan Hay -- Stability : auto-generated diff --git a/test/Test/AWS/MachineLearning.hs b/test/Test/AWS/MachineLearning.hs --- a/test/Test/AWS/MachineLearning.hs +++ b/test/Test/AWS/MachineLearning.hs @@ -1,7 +1,7 @@ {-# LANGUAGE OverloadedStrings #-} -- Module : Test.AWS.MachineLearning --- Copyright : (c) 2013-2016 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : This Source Code Form is subject to the terms of -- the Mozilla Public License, v. 2.0. -- A copy of the MPL can be found in the LICENSE file or diff --git a/test/Test/AWS/MachineLearning/Internal.hs b/test/Test/AWS/MachineLearning/Internal.hs --- a/test/Test/AWS/MachineLearning/Internal.hs +++ b/test/Test/AWS/MachineLearning/Internal.hs @@ -2,7 +2,7 @@ {-# OPTIONS_GHC -fno-warn-unused-imports #-} -- Module : Test.AWS.MachineLearning.Internal --- Copyright : (c) 2013-2016 Brendan Hay +-- Copyright : (c) 2013-2018 Brendan Hay -- License : This Source Code Form is subject to the terms of -- the Mozilla Public License, v. 2.0. -- A copy of the MPL can be found in the LICENSE file or