Get a model evaluation slice

  import 
  
 com.google.cloud.aiplatform.v1. ModelEvaluationSlice 
 
 ; 
 import 
  
 com.google.cloud.aiplatform.v1. ModelEvaluationSlice 
. Slice 
 
 ; 
 import 
  
 com.google.cloud.aiplatform.v1. ModelEvaluationSliceName 
 
 ; 
 import 
  
 com.google.cloud.aiplatform.v1. ModelServiceClient 
 
 ; 
 import 
  
 com.google.cloud.aiplatform.v1. ModelServiceSettings 
 
 ; 
 import 
  
 java.io.IOException 
 ; 
 public 
  
 class 
 GetModelEvaluationSliceSample 
  
 { 
  
 public 
  
 static 
  
 void 
  
 main 
 ( 
 String 
 [] 
  
 args 
 ) 
  
 throws 
  
 IOException 
  
 { 
  
 // TODO(developer): Replace these variables before running the sample. 
  
 // To obtain evaluationId run the code block below after setting modelServiceSettings. 
  
 // 
  
 // try (ModelServiceClient modelServiceClient = ModelServiceClient.create(modelServiceSettings)) 
  
 // { 
  
 //   String location = "us-central1"; 
  
 //   ModelName modelFullId = ModelName.of(project, location, modelId); 
  
 //   ListModelEvaluationsRequest modelEvaluationsrequest = 
  
 //   ListModelEvaluationsRequest.newBuilder().setParent(modelFullId.toString()).build(); 
  
 //   for (ModelEvaluation modelEvaluation : 
  
 //     modelServiceClient.listModelEvaluations(modelEvaluationsrequest).iterateAll()) { 
  
 //       System.out.format("Model Evaluation Name: %s%n", modelEvaluation.getName()); 
  
 //   } 
  
 // } 
  
 String 
  
 project 
  
 = 
  
 "YOUR_PROJECT_ID" 
 ; 
  
 String 
  
 modelId 
  
 = 
  
 "YOUR_MODEL_ID" 
 ; 
  
 String 
  
 evaluationId 
  
 = 
  
 "YOUR_EVALUATION_ID" 
 ; 
  
 String 
  
 sliceId 
  
 = 
  
 "YOUR_SLICE_ID" 
 ; 
  
 getModelEvaluationSliceSample 
 ( 
 project 
 , 
  
 modelId 
 , 
  
 evaluationId 
 , 
  
 sliceId 
 ); 
  
 } 
  
 static 
  
 void 
  
 getModelEvaluationSliceSample 
 ( 
  
 String 
  
 project 
 , 
  
 String 
  
 modelId 
 , 
  
 String 
  
 evaluationId 
 , 
  
 String 
  
 sliceId 
 ) 
  
 throws 
  
 IOException 
  
 { 
  
  ModelServiceSettings 
 
  
 modelServiceSettings 
  
 = 
  
  ModelServiceSettings 
 
 . 
 newBuilder 
 () 
  
 . 
 setEndpoint 
 ( 
 "us-central1-aiplatform.googleapis.com:443" 
 ) 
  
 . 
 build 
 (); 
  
 // Initialize client that will be used to send requests. This client only needs to be created 
  
 // once, and can be reused for multiple requests. After completing all of your requests, call 
  
 // the "close" method on the client to safely clean up any remaining background resources. 
  
 try 
  
 ( 
  ModelServiceClient 
 
  
 modelServiceClient 
  
 = 
  
  ModelServiceClient 
 
 . 
 create 
 ( 
 modelServiceSettings 
 )) 
  
 { 
  
 String 
  
 location 
  
 = 
  
 "us-central1" 
 ; 
  
  ModelEvaluationSliceName 
 
  
 modelEvaluationSliceName 
  
 = 
  
  ModelEvaluationSliceName 
 
 . 
 of 
 ( 
 project 
 , 
  
 location 
 , 
  
 modelId 
 , 
  
 evaluationId 
 , 
  
 sliceId 
 ); 
  
  ModelEvaluationSlice 
 
  
 modelEvaluationSlice 
  
 = 
  
 modelServiceClient 
 . 
 getModelEvaluationSlice 
 ( 
 modelEvaluationSliceName 
 ); 
  
 System 
 . 
 out 
 . 
 println 
 ( 
 "Get Model Evaluation Slice Response" 
 ); 
  
 System 
 . 
 out 
 . 
 format 
 ( 
 "Model Evaluation Slice Name: %s\n" 
 , 
  
 modelEvaluationSlice 
 . 
  getName 
 
 ()); 
  
 System 
 . 
 out 
 . 
 format 
 ( 
 "Metrics Schema Uri: %s\n" 
 , 
  
 modelEvaluationSlice 
 . 
  getMetricsSchemaUri 
 
 ()); 
  
 System 
 . 
 out 
 . 
 format 
 ( 
 "Metrics: %s\n" 
 , 
  
 modelEvaluationSlice 
 . 
  getMetrics 
 
 ()); 
  
 System 
 . 
 out 
 . 
 format 
 ( 
 "Create Time: %s\n" 
 , 
  
 modelEvaluationSlice 
 . 
  getCreateTime 
 
 ()); 
  
  Slice 
 
  
 slice 
  
 = 
  
 modelEvaluationSlice 
 . 
  getSlice 
 
 (); 
  
 System 
 . 
 out 
 . 
 format 
 ( 
 "Slice Dimensions: %s\n" 
 , 
  
 slice 
 . 
 getDimension 
 ()); 
  
 System 
 . 
 out 
 . 
 format 
 ( 
 "Slice Value: %s\n" 
 , 
  
 slice 
 . 
 getValue 
 ()); 
  
 } 
  
 } 
 } 
 

  /** 
 * TODO(developer): Uncomment these variables before running the sample 
 * (not necessary if passing values as arguments). To obtain evaluationId, 
 * instantiate the client and run the following the commands. 
 */ 
 // const parentName = `projects/${project}/locations/${location}/models/${modelId}`; 
 // const evalRequest = { 
 //   parent: parentName 
 // }; 
 // const [evalResponse] = await modelServiceClient.listModelEvaluations(evalRequest); 
 // console.log(evalResponse); 
 // const modelId = 'YOUR_MODEL_ID'; 
 // const evaluationId = 'YOUR_EVALUATION_ID'; 
 // const sliceId = 'YOUR_SLICE_ID'; 
 // const project = 'YOUR_PROJECT_ID'; 
 // const location = 'YOUR_PROJECT_LOCATION'; 
 // Imports the Google Cloud Model Service client library 
 const 
  
 { 
 ModelServiceClient 
 } 
  
 = 
  
 require 
 ( 
 ' @google-cloud/aiplatform 
' 
 ); 
 // Specifies the location of the api endpoint 
 const 
  
 clientOptions 
  
 = 
  
 { 
  
 apiEndpoint 
 : 
  
 'us-central1-aiplatform.googleapis.com' 
 , 
 }; 
 // Specifies the location of the api endpoint 
 const 
  
 modelServiceClient 
  
 = 
  
 new 
  
  ModelServiceClient 
 
 ( 
 clientOptions 
 ); 
 async 
  
 function 
  
 getModelEvaluationSlice 
 () 
  
 { 
  
 // Configure the parent resource 
  
 const 
  
 name 
  
 = 
  
 `projects/ 
 ${ 
 project 
 } 
 /locations/ 
 ${ 
 location 
 } 
 /models/ 
 ${ 
 modelId 
 } 
 /evaluations/ 
 ${ 
 evaluationId 
 } 
 /slices/ 
 ${ 
 sliceId 
 } 
 ` 
 ; 
  
 const 
  
 request 
  
 = 
  
 { 
  
 name 
 , 
  
 }; 
  
 // Get and print out a list of all the endpoints for this resource 
  
 const 
  
 [ 
 response 
 ] 
  
 = 
  
 await 
  
 modelServiceClient 
 . 
 getModelEvaluationSlice 
 ( 
 request 
 ); 
  
 console 
 . 
 log 
 ( 
 'Get model evaluation slice' 
 ); 
  
 console 
 . 
 log 
 ( 
 `\tName : 
 ${ 
 response 
 . 
 name 
 } 
 ` 
 ); 
  
 console 
 . 
 log 
 ( 
 `\tMetrics_Schema_Uri : 
 ${ 
 response 
 . 
 metricsSchemaUri 
 } 
 ` 
 ); 
  
 console 
 . 
 log 
 ( 
 `\tMetrics : 
 ${ 
 JSON 
 . 
 stringify 
 ( 
 response 
 . 
 metrics 
 ) 
 } 
 ` 
 ); 
  
 console 
 . 
 log 
 ( 
 `\tCreate time : 
 ${ 
 JSON 
 . 
 stringify 
 ( 
 response 
 . 
 createTime 
 ) 
 } 
 ` 
 ); 
  
 console 
 . 
 log 
 ( 
 'Slice' 
 ); 
  
 const 
  
 slice 
  
 = 
  
 response 
 . 
 slice 
 ; 
  
 console 
 . 
 log 
 ( 
 `\tDimension : 
 ${ 
 slice 
 . 
 dimension 
 } 
 ` 
 ); 
  
 console 
 . 
 log 
 ( 
 `\tValue : 
 ${ 
 slice 
 . 
 value 
 } 
 ` 
 ); 
 } 
 getModelEvaluationSlice 
 (); 
 

  from 
  
 google.cloud 
  
 import 
 aiplatform 
 def 
  
 get_model_evaluation_slice_sample 
 ( 
 project 
 : 
 str 
 , 
 model_id 
 : 
 str 
 , 
 evaluation_id 
 : 
 str 
 , 
 slice_id 
 : 
 str 
 , 
 location 
 : 
 str 
 = 
 "us-central1" 
 , 
 api_endpoint 
 : 
 str 
 = 
 "us-central1-aiplatform.googleapis.com" 
 , 
 ): 
  
 """ 
 To obtain evaluation_id run the following commands where LOCATION 
 is the region where the model is stored, PROJECT is the project ID, 
 and MODEL_ID is the ID of your model. 
 model_client = aiplatform.gapic.ModelServiceClient( 
 client_options={ 
 'api_endpoint':'LOCATION-aiplatform.googleapis.com' 
 } 
 ) 
 evaluations = model_client.list_model_evaluations(parent='projects/PROJECT/locations/LOCATION/models/MODEL_ID') 
 print("evaluations:", evaluations) 
 """ 
 # The AI Platform services require regional API endpoints. 
 client_options 
 = 
 { 
 "api_endpoint" 
 : 
 api_endpoint 
 } 
 # Initialize client that will be used to create and send requests. 
 # This client only needs to be created once, and can be reused for multiple requests. 
 client 
 = 
 aiplatform 
 . 
 gapic 
 . 
  ModelServiceClient 
 
 ( 
 client_options 
 = 
 client_options 
 ) 
 name 
 = 
 client 
 . 
  model_evaluation_slice_path 
 
 ( 
 project 
 = 
 project 
 , 
 location 
 = 
 location 
 , 
 model 
 = 
 model_id 
 , 
 evaluation 
 = 
 evaluation_id 
 , 
 slice 
 = 
 slice_id 
 , 
 ) 
 response 
 = 
 client 
 . 
  get_model_evaluation_slice 
 
 ( 
 name 
 = 
 name 
 ) 
 print 
 ( 
 "response:" 
 , 
 response 
 )