表格說明

使用 explain 方法取得表格的說明。

程式碼範例

Python

在試用這個範例之前，請先按照Python使用用戶端程式庫的 Vertex AI 快速入門中的操作說明進行設定。 詳情請參閱 Vertex AI Python API 參考說明文件。

如要向 Vertex AI 進行驗證，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

from typing import Dict

from google.cloud import aiplatform_v1beta1
from google.protobuf import json_format
from google.protobuf.struct_pb2 import Value


def explain_tabular_sample(
    project: str,
    endpoint_id: str,
    instance_dict: Dict,
    location: str = "us-central1",
    api_endpoint: str = "us-central1-aiplatform.googleapis.com",
):
    # 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_v1beta1.PredictionServiceClient(client_options=client_options)
    # The format of each instance should conform to the deployed model's prediction input schema.
    instance = json_format.ParseDict(instance_dict, Value())
    instances = [instance]
    # tabular models do not have additional parameters
    parameters_dict = {}
    parameters = json_format.ParseDict(parameters_dict, Value())
    endpoint = client.endpoint_path(
        project=project, location=location, endpoint=endpoint_id
    )
    response = client.explain(
        endpoint=endpoint, instances=instances, parameters=parameters
    )
    print("response")
    print(" deployed_model_id:", response.deployed_model_id)
    explanations = response.explanations
    for explanation in explanations:
        print(" explanation")
        # Feature attributions.
        attributions = explanation.attributions
        for attribution in attributions:
            print("  attribution")
            print("   baseline_output_value:", attribution.baseline_output_value)
            print("   instance_output_value:", attribution.instance_output_value)
            print("   output_display_name:", attribution.output_display_name)
            print("   approximation_error:", attribution.approximation_error)
            print("   output_name:", attribution.output_name)
            output_index = attribution.output_index
            for output_index in output_index:
                print("   output_index:", output_index)
    predictions = response.predictions
    for prediction in predictions:
        print(" prediction:", dict(prediction))

後續步驟

如要搜尋及篩選其他 Google Cloud 產品的程式碼範例，請參閱Google Cloud 範例瀏覽器。