检索用于文本分类的数据集。
代码示例
Go
如需向 AutoML Natural Language 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为本地开发环境设置身份验证。
import (
"context"
"fmt"
"io"
automl "cloud.google.com/go/automl/apiv1"
"cloud.google.com/go/automl/apiv1/automlpb"
)
// getDataset gets a dataset.
func getDataset(w io.Writer, projectID string, location string, datasetID string) error {
// projectID := "my-project-id"
// location := "us-central1"
// datasetID := "TRL123456789..."
ctx := context.Background()
client, err := automl.NewClient(ctx)
if err != nil {
return fmt.Errorf("NewClient: %w", err)
}
defer client.Close()
req := &automlpb.GetDatasetRequest{
Name: fmt.Sprintf("projects/%s/locations/%s/datasets/%s", projectID, location, datasetID),
}
dataset, err := client.GetDataset(ctx, req)
if err != nil {
return fmt.Errorf("DeleteDataset: %w", err)
}
fmt.Fprintf(w, "Dataset name: %v\n", dataset.GetName())
fmt.Fprintf(w, "Dataset display name: %v\n", dataset.GetDisplayName())
fmt.Fprintf(w, "Dataset create time:\n")
fmt.Fprintf(w, "\tseconds: %v\n", dataset.GetCreateTime().GetSeconds())
fmt.Fprintf(w, "\tnanos: %v\n", dataset.GetCreateTime().GetNanos())
// Language text classification
if metadata := dataset.GetTextClassificationDatasetMetadata(); metadata != nil {
fmt.Fprintf(w, "Text classification dataset metadata: %v\n", metadata)
}
return nil
}
Java
如需向 AutoML Natural Language 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为本地开发环境设置身份验证。
import com.google.cloud.automl.v1.AutoMlClient;
import com.google.cloud.automl.v1.Dataset;
import com.google.cloud.automl.v1.DatasetName;
import java.io.IOException;
class GetDataset {
static void getDataset() throws IOException {
// TODO(developer): Replace these variables before running the sample.
String projectId = "YOUR_PROJECT_ID";
String datasetId = "YOUR_DATASET_ID";
getDataset(projectId, datasetId);
}
// Get a dataset
static void getDataset(String projectId, String datasetId) throws IOException {
// 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 (AutoMlClient client = AutoMlClient.create()) {
// Get the complete path of the dataset.
DatasetName datasetFullId = DatasetName.of(projectId, "us-central1", datasetId);
Dataset dataset = client.getDataset(datasetFullId);
// Display the dataset information
System.out.format("Dataset name: %s\n", dataset.getName());
// To get the dataset id, you have to parse it out of the `name` field. As dataset Ids are
// required for other methods.
// Name Form: `projects/{project_id}/locations/{location_id}/datasets/{dataset_id}`
String[] names = dataset.getName().split("/");
String retrievedDatasetId = names[names.length - 1];
System.out.format("Dataset id: %s\n", retrievedDatasetId);
System.out.format("Dataset display name: %s\n", dataset.getDisplayName());
System.out.println("Dataset create time:");
System.out.format("\tseconds: %s\n", dataset.getCreateTime().getSeconds());
System.out.format("\tnanos: %s\n", dataset.getCreateTime().getNanos());
System.out.format(
"Text classification dataset metadata: %s\n",
dataset.getTextClassificationDatasetMetadata());
}
}
}
Python
如需向 AutoML Natural Language 进行身份验证,请设置应用默认凭据。 如需了解详情,请参阅为本地开发环境设置身份验证。
from google.cloud import automl
# TODO(developer): Uncomment and set the following variables
# project_id = "YOUR_PROJECT_ID"
# dataset_id = "YOUR_DATASET_ID"
client = automl.AutoMlClient()
# Get the full path of the dataset
dataset_full_id = client.dataset_path(project_id, "us-central1", dataset_id)
dataset = client.get_dataset(name=dataset_full_id)
# Display the dataset information
print(f"Dataset name: {dataset.name}")
print("Dataset id: {}".format(dataset.name.split("/")[-1]))
print(f"Dataset display name: {dataset.display_name}")
print(f"Dataset create time: {dataset.create_time}")
print(
"Text classification dataset metadata: {}".format(
dataset.text_classification_dataset_metadata
)
)
后续步骤
如需搜索和过滤其他 Google Cloud 产品的代码示例,请参阅 Google Cloud 示例浏览器。