Membuat tugas prediksi batch untuk perkiraan tabulasi
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Membuat tugas prediksi batch untuk perkiraan tabulasi menggunakan metode create_batch_prediction_job.
Contoh kode
Kecuali dinyatakan lain, konten di halaman ini dilisensikan berdasarkan Lisensi Creative Commons Attribution 4.0, sedangkan contoh kode dilisensikan berdasarkan Lisensi Apache 2.0. Untuk mengetahui informasi selengkapnya, lihat Kebijakan Situs Google Developers. Java adalah merek dagang terdaftar dari Oracle dan/atau afiliasinya.
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Sulit dipahami","hardToUnderstand","thumb-down"],["Informasi atau kode contoh salah","incorrectInformationOrSampleCode","thumb-down"],["Informasi/contoh yang saya butuhkan tidak ada","missingTheInformationSamplesINeed","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Lainnya","otherDown","thumb-down"]],[],[],[],null,["# Create a batch prediction job for tabular forecasting\n\nCreates a batch prediction job for tabular forecasting using the create_batch_prediction_job method.\n\nCode sample\n-----------\n\n### Python\n\n\nBefore trying this sample, follow the Python setup instructions in the\n[Vertex AI quickstart using\nclient libraries](/vertex-ai/docs/start/client-libraries).\n\n\nFor more information, see the\n[Vertex AI Python API\nreference documentation](/python/docs/reference/aiplatform/latest).\n\n\nTo authenticate to Vertex AI, set up Application Default Credentials.\nFor more information, see\n\n[Set up authentication for a local development environment](/docs/authentication/set-up-adc-local-dev-environment).\n\n from google.cloud import aiplatform_v1beta1\n\n\n def create_batch_prediction_job_tabular_forecasting_sample(\n project: str,\n display_name: str,\n model_name: str,\n gcs_source_uri: str,\n gcs_destination_output_uri_prefix: str,\n predictions_format: str,\n location: str = \"us-central1\",\n api_endpoint: str = \"us-central1-aiplatform.googleapis.com\",\n ):\n # The AI Platform services require regional API endpoints.\n client_options = {\"api_endpoint\": api_endpoint}\n # Initialize client that will be used to create and send requests.\n # This client only needs to be created once, and can be reused for multiple requests.\n client = aiplatform_v1beta1.https://cloud.google.com/python/docs/reference/aiplatform/latest/google.cloud.aiplatform_v1beta1.services.job_service.JobServiceClient.html(client_options=client_options)\n batch_prediction_job = {\n \"display_name\": display_name,\n # Format: 'projects/{project}/locations/{location}/models/{model_id}'\n \"model\": model_name,\n \"input_config\": {\n \"instances_format\": predictions_format,\n \"gcs_source\": {\"uris\": [gcs_source_uri]},\n },\n \"output_config\": {\n \"predictions_format\": predictions_format,\n \"gcs_destination\": {\"output_uri_prefix\": gcs_destination_output_uri_prefix},\n },\n }\n parent = f\"projects/{project}/locations/{location}\"\n response = client.https://cloud.google.com/python/docs/reference/aiplatform/latest/google.cloud.aiplatform_v1beta1.services.job_service.JobServiceClient.html#google_cloud_aiplatform_v1beta1_services_job_service_JobServiceClient_create_batch_prediction_job(\n parent=parent, batch_prediction_job=batch_prediction_job\n )\n print(\"response:\", response)\n\nWhat's next\n-----------\n\n\nTo search and filter code samples for other Google Cloud products, see the\n[Google Cloud sample browser](/docs/samples?product=aiplatform)."]]