설명 메서드를 사용하여 테이블 형식을 위한 설명을 가져옵니다.
코드 샘플
Python
Vertex AI용 클라이언트 라이브러리를 설치하고 사용하는 방법은 Vertex AI 클라이언트 라이브러리를 참조하세요. 자세한 내용은 Vertex AI Python API 참조 문서를 참조하세요.
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))
다음 단계
다른 Google Cloud 제품의 코드 샘플을 검색하고 필터링하려면 Google Cloud 샘플 브라우저를 참조하세요.