Import data for video classification

  import 
  
 com.google.api.gax.longrunning. OperationFuture 
 
 ; 
 import 
  
 com.google.cloud.aiplatform.v1. DatasetName 
 
 ; 
 import 
  
 com.google.cloud.aiplatform.v1. DatasetServiceClient 
 
 ; 
 import 
  
 com.google.cloud.aiplatform.v1. DatasetServiceSettings 
 
 ; 
 import 
  
 com.google.cloud.aiplatform.v1. GcsSource 
 
 ; 
 import 
  
 com.google.cloud.aiplatform.v1. ImportDataConfig 
 
 ; 
 import 
  
 com.google.cloud.aiplatform.v1. ImportDataOperationMetadata 
 
 ; 
 import 
  
 com.google.cloud.aiplatform.v1. ImportDataResponse 
 
 ; 
 import 
  
 java.io.IOException 
 ; 
 import 
  
 java.util.Collections 
 ; 
 import 
  
 java.util.List 
 ; 
 import 
  
 java.util.concurrent.ExecutionException 
 ; 
 import 
  
 java.util.concurrent.TimeUnit 
 ; 
 import 
  
 java.util.concurrent.TimeoutException 
 ; 
 public 
  
 class 
 ImportDataVideoClassificationSample 
  
 { 
  
 public 
  
 static 
  
 void 
  
 main 
 ( 
 String 
 [] 
  
 args 
 ) 
  
 throws 
  
 InterruptedException 
 , 
  
 ExecutionException 
 , 
  
 TimeoutException 
 , 
  
 IOException 
  
 { 
  
 // TODO(developer): Replace these variables before running the sample. 
  
 String 
  
 gcsSourceUri 
  
 = 
  
 "gs://YOUR_GCS_SOURCE_BUCKET/path_to_your_video_source/[file.csv/file.jsonl]" 
 ; 
  
 String 
  
 project 
  
 = 
  
 "YOUR_PROJECT_ID" 
 ; 
  
 String 
  
 datasetId 
  
 = 
  
 "YOUR_DATASET_ID" 
 ; 
  
 importDataVideoClassification 
 ( 
 gcsSourceUri 
 , 
  
 project 
 , 
  
 datasetId 
 ); 
  
 } 
  
 static 
  
 void 
  
 importDataVideoClassification 
 ( 
 String 
  
 gcsSourceUri 
 , 
  
 String 
  
 project 
 , 
  
 String 
  
 datasetId 
 ) 
  
 throws 
  
 IOException 
 , 
  
 ExecutionException 
 , 
  
 InterruptedException 
 , 
  
 TimeoutException 
  
 { 
  
  DatasetServiceSettings 
 
  
 datasetServiceSettings 
  
 = 
  
  DatasetServiceSettings 
 
 . 
 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 
  
 ( 
  DatasetServiceClient 
 
  
 datasetServiceClient 
  
 = 
  
  DatasetServiceClient 
 
 . 
 create 
 ( 
 datasetServiceSettings 
 )) 
  
 { 
  
 String 
  
 location 
  
 = 
  
 "us-central1" 
 ; 
  
 String 
  
 importSchemaUri 
  
 = 
  
 "gs://google-cloud-aiplatform/schema/dataset/ioformat/" 
  
 + 
  
 "video_classification_io_format_1.0.0.yaml" 
 ; 
  
  GcsSource 
 
 . 
 Builder 
  
 gcsSource 
  
 = 
  
  GcsSource 
 
 . 
 newBuilder 
 (); 
  
 gcsSource 
 . 
  addUris 
 
 ( 
 gcsSourceUri 
 ); 
  
  DatasetName 
 
  
 datasetName 
  
 = 
  
  DatasetName 
 
 . 
 of 
 ( 
 project 
 , 
  
 location 
 , 
  
 datasetId 
 ); 
  
 List<ImportDataConfig> 
  
 importDataConfigs 
  
 = 
  
 Collections 
 . 
 singletonList 
 ( 
  
  ImportDataConfig 
 
 . 
 newBuilder 
 () 
  
 . 
 setGcsSource 
 ( 
 gcsSource 
 ) 
  
 . 
  setImportSchemaUri 
 
 ( 
 importSchemaUri 
 ) 
  
 . 
 build 
 ()); 
  
 OperationFuture<ImportDataResponse 
 , 
  
 ImportDataOperationMetadata 
>  
 importDataResponseFuture 
  
 = 
  
 datasetServiceClient 
 . 
  importDataAsync 
 
 ( 
 datasetName 
 , 
  
 importDataConfigs 
 ); 
  
 System 
 . 
 out 
 . 
 format 
 ( 
  
 "Operation name: %s\n" 
 , 
  
 importDataResponseFuture 
 . 
 getInitialFuture 
 (). 
  get 
 
 (). 
 getName 
 ()); 
  
 System 
 . 
 out 
 . 
 println 
 ( 
 "Waiting for operation to finish..." 
 ); 
  
  ImportDataResponse 
 
  
 importDataResponse 
  
 = 
  
 importDataResponseFuture 
 . 
  get 
 
 ( 
 1800 
 , 
  
 TimeUnit 
 . 
 SECONDS 
 ); 
  
 System 
 . 
 out 
 . 
 format 
 ( 
  
 "Import Data Video Classification Response: %s\n" 
 , 
  
 importDataResponse 
 . 
 toString 
 ()); 
  
 } 
  
 } 
 } 
 

  /** 
 * TODO(developer): Uncomment these variables before running the sample.\ 
 * (Not necessary if passing values as arguments) 
 */ 
 // const datasetId = 'YOUR_DATASET_ID'; 
 // const gcsSourceUri = 'YOUR_GCS_SOURCE_URI'; 
 // eg. 'gs://<your-gcs-bucket>/<import_source_path>/[file.csv/file.jsonl]' 
 // const project = 'YOUR_PROJECT_ID'; 
 // const location = 'YOUR_PROJECT_LOCATION'; 
 // Imports the Google Cloud Dataset Service Client library 
 const 
  
 { 
 DatasetServiceClient 
 } 
  
 = 
  
 require 
 ( 
 ' @google-cloud/aiplatform 
' 
 ); 
 // Specifies the location of the api endpoint 
 const 
  
 clientOptions 
  
 = 
  
 { 
  
 apiEndpoint 
 : 
  
 'us-central1-aiplatform.googleapis.com' 
 , 
 }; 
 const 
  
 datasetServiceClient 
  
 = 
  
 new 
  
  DatasetServiceClient 
 
 ( 
 clientOptions 
 ); 
 async 
  
 function 
  
 importDataVideoClassification 
 () 
  
 { 
  
 const 
  
 name 
  
 = 
  
 datasetServiceClient 
 . 
 datasetPath 
 ( 
 project 
 , 
  
 location 
 , 
  
 datasetId 
 ); 
  
 // Here we use only one import config with one source 
  
 const 
  
 importConfigs 
  
 = 
  
 [ 
  
 { 
  
 gcsSource 
 : 
  
 { 
 uris 
 : 
  
 [ 
 gcsSourceUri 
 ]}, 
  
 importSchemaUri 
 : 
  
 'gs://google-cloud-aiplatform/schema/dataset/ioformat/video_classification_io_format_1.0.0.yaml' 
 , 
  
 }, 
  
 ]; 
  
 const 
  
 request 
  
 = 
  
 { 
  
 name 
 , 
  
 importConfigs 
 , 
  
 }; 
  
 // Create Import Data Request 
  
 const 
  
 [ 
 response 
 ] 
  
 = 
  
 await 
  
 datasetServiceClient 
 . 
 importData 
 ( 
 request 
 ); 
  
 console 
 . 
 log 
 ( 
 `Long running operation : 
 ${ 
 response 
 . 
 name 
 } 
 ` 
 ); 
  
 // Wait for operation to complete 
  
 await 
  
 response 
 . 
 promise 
 (); 
  
 console 
 . 
 log 
 ( 
  
 `Import data video classification response : \ 
  
 ${ 
 JSON 
 . 
 stringify 
 ( 
 response 
 . 
 result 
 ) 
 } 
 ` 
  
 ); 
 } 
 importDataVideoClassification 
 (); 
 

  from 
  
 google.cloud 
  
 import 
 aiplatform 
 def 
  
 import_data_video_classification_sample 
 ( 
 project 
 : 
 str 
 , 
 dataset_id 
 : 
 str 
 , 
 gcs_source_uri 
 : 
 str 
 , 
 location 
 : 
 str 
 = 
 "us-central1" 
 , 
 api_endpoint 
 : 
 str 
 = 
 "us-central1-aiplatform.googleapis.com" 
 , 
 timeout 
 : 
 int 
 = 
 1800 
 , 
 ): 
 # 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 
 . 
  DatasetServiceClient 
 
 ( 
 client_options 
 = 
 client_options 
 ) 
 import_configs 
 = 
 [ 
 { 
 "gcs_source" 
 : 
 { 
 "uris" 
 : 
 [ 
 gcs_source_uri 
 ]}, 
 "import_schema_uri" 
 : 
 "gs://google-cloud-aiplatform/schema/dataset/ioformat/video_classification_io_format_1.0.0.yaml" 
 , 
 } 
 ] 
 name 
 = 
 client 
 . 
  dataset_path 
 
 ( 
 project 
 = 
 project 
 , 
 location 
 = 
 location 
 , 
 dataset 
 = 
 dataset_id 
 ) 
 response 
 = 
 client 
 . 
  import_data 
 
 ( 
 name 
 = 
 name 
 , 
 import_configs 
 = 
 import_configs 
 ) 
 print 
 ( 
 "Long running operation:" 
 , 
 response 
 . 
 operation 
 . 
 name 
 ) 
 import_data_response 
 = 
 response 
 . 
 result 
 ( 
 timeout 
 = 
 timeout 
 ) 
 print 
 ( 
 "import_data_response:" 
 , 
 import_data_response 
 )