# frozen_string_literal: true
# Copyright 2022 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# Auto-generated by gapic-generator-ruby. DO NOT EDIT!
module Google
module Cloud
module AIPlatform
module V1
# A job that uses a
# {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#model Model} to produce
# predictions on multiple [input
# instances][google.cloud.aiplatform.v1.BatchPredictionJob.input_config]. If
# predictions for significant portion of the instances fail, the job may finish
# without attempting predictions for all remaining instances.
# @!attribute [r] name
# @return [::String]
# Output only. Resource name of the BatchPredictionJob.
# @!attribute [rw] display_name
# @return [::String]
# Required. The user-defined name of this BatchPredictionJob.
# @!attribute [rw] model
# @return [::String]
# The name of the Model resource that produces the predictions via this job,
# must share the same ancestor Location.
# Starting this job has no impact on any existing deployments of the Model
# and their resources.
# Exactly one of model and unmanaged_container_model must be set.
#
# The model resource name may contain version id or version alias to specify
# the version.
# Example: `projects/{project}/locations/{location}/models/{model}@2`
# or
# `projects/{project}/locations/{location}/models/{model}@golden`
# if no version is specified, the default version will be deployed.
#
# The model resource could also be a publisher model.
# Example: `publishers/{publisher}/models/{model}`
# or
# `projects/{project}/locations/{location}/publishers/{publisher}/models/{model}`
# @!attribute [r] model_version_id
# @return [::String]
# Output only. The version ID of the Model that produces the predictions via
# this job.
# @!attribute [rw] unmanaged_container_model
# @return [::Google::Cloud::AIPlatform::V1::UnmanagedContainerModel]
# Contains model information necessary to perform batch prediction without
# requiring uploading to model registry.
# Exactly one of model and unmanaged_container_model must be set.
# @!attribute [rw] input_config
# @return [::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InputConfig]
# Required. Input configuration of the instances on which predictions are
# performed. The schema of any single instance may be specified via the
# [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
# [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
# {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance_schema_uri}.
# @!attribute [rw] instance_config
# @return [::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig]
# Configuration for how to convert batch prediction input instances to the
# prediction instances that are sent to the Model.
# @!attribute [rw] model_parameters
# @return [::Google::Protobuf::Value]
# The parameters that govern the predictions. The schema of the parameters
# may be specified via the
# [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
# [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
# {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri parameters_schema_uri}.
# @!attribute [rw] output_config
# @return [::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig]
# Required. The Configuration specifying where output predictions should
# be written.
# The schema of any single prediction may be specified as a concatenation
# of [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
# [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
# {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance_schema_uri}
# and
# {::Google::Cloud::AIPlatform::V1::PredictSchemata#prediction_schema_uri prediction_schema_uri}.
# @!attribute [rw] dedicated_resources
# @return [::Google::Cloud::AIPlatform::V1::BatchDedicatedResources]
# The config of resources used by the Model during the batch prediction. If
# the Model
# {::Google::Cloud::AIPlatform::V1::Model#supported_deployment_resources_types supports}
# DEDICATED_RESOURCES this config may be provided (and the job will use these
# resources), if the Model doesn't support AUTOMATIC_RESOURCES, this config
# must be provided.
# @!attribute [rw] service_account
# @return [::String]
# The service account that the DeployedModel's container runs as. If not
# specified, a system generated one will be used, which
# has minimal permissions and the custom container, if used, may not have
# enough permission to access other Google Cloud resources.
#
# Users deploying the Model must have the `iam.serviceAccounts.actAs`
# permission on this service account.
# @!attribute [rw] manual_batch_tuning_parameters
# @return [::Google::Cloud::AIPlatform::V1::ManualBatchTuningParameters]
# Immutable. Parameters configuring the batch behavior. Currently only
# applicable when
# {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#dedicated_resources dedicated_resources}
# are used (in other cases Vertex AI does the tuning itself).
# @!attribute [rw] generate_explanation
# @return [::Boolean]
# Generate explanation with the batch prediction results.
#
# When set to `true`, the batch prediction output changes based on the
# `predictions_format` field of the
# {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config BatchPredictionJob.output_config}
# object:
#
# * `bigquery`: output includes a column named `explanation`. The value
# is a struct that conforms to the
# {::Google::Cloud::AIPlatform::V1::Explanation Explanation} object.
# * `jsonl`: The JSON objects on each line include an additional entry
# keyed `explanation`. The value of the entry is a JSON object that
# conforms to the {::Google::Cloud::AIPlatform::V1::Explanation Explanation}
# object.
# * `csv`: Generating explanations for CSV format is not supported.
#
# If this field is set to true, either the
# {::Google::Cloud::AIPlatform::V1::Model#explanation_spec Model.explanation_spec}
# or
# {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#explanation_spec explanation_spec}
# must be populated.
# @!attribute [rw] explanation_spec
# @return [::Google::Cloud::AIPlatform::V1::ExplanationSpec]
# Explanation configuration for this BatchPredictionJob. Can be
# specified only if
# {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#generate_explanation generate_explanation}
# is set to `true`.
#
# This value overrides the value of
# {::Google::Cloud::AIPlatform::V1::Model#explanation_spec Model.explanation_spec}.
# All fields of
# {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#explanation_spec explanation_spec}
# are optional in the request. If a field of the
# {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#explanation_spec explanation_spec}
# object is not populated, the corresponding field of the
# {::Google::Cloud::AIPlatform::V1::Model#explanation_spec Model.explanation_spec}
# object is inherited.
# @!attribute [r] output_info
# @return [::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputInfo]
# Output only. Information further describing the output of this job.
# @!attribute [r] state
# @return [::Google::Cloud::AIPlatform::V1::JobState]
# Output only. The detailed state of the job.
# @!attribute [r] error
# @return [::Google::Rpc::Status]
# Output only. Only populated when the job's state is JOB_STATE_FAILED or
# JOB_STATE_CANCELLED.
# @!attribute [r] partial_failures
# @return [::Array<::Google::Rpc::Status>]
# Output only. Partial failures encountered.
# For example, single files that can't be read.
# This field never exceeds 20 entries.
# Status details fields contain standard Google Cloud error details.
# @!attribute [r] resources_consumed
# @return [::Google::Cloud::AIPlatform::V1::ResourcesConsumed]
# Output only. Information about resources that had been consumed by this
# job. Provided in real time at best effort basis, as well as a final value
# once the job completes.
#
# Note: This field currently may be not populated for batch predictions that
# use AutoML Models.
# @!attribute [r] completion_stats
# @return [::Google::Cloud::AIPlatform::V1::CompletionStats]
# Output only. Statistics on completed and failed prediction instances.
# @!attribute [r] create_time
# @return [::Google::Protobuf::Timestamp]
# Output only. Time when the BatchPredictionJob was created.
# @!attribute [r] start_time
# @return [::Google::Protobuf::Timestamp]
# Output only. Time when the BatchPredictionJob for the first time entered
# the `JOB_STATE_RUNNING` state.
# @!attribute [r] end_time
# @return [::Google::Protobuf::Timestamp]
# Output only. Time when the BatchPredictionJob entered any of the following
# states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`.
# @!attribute [r] update_time
# @return [::Google::Protobuf::Timestamp]
# Output only. Time when the BatchPredictionJob was most recently updated.
# @!attribute [rw] labels
# @return [::Google::Protobuf::Map{::String => ::String}]
# The labels with user-defined metadata to organize BatchPredictionJobs.
#
# Label keys and values can be no longer than 64 characters
# (Unicode codepoints), can only contain lowercase letters, numeric
# characters, underscores and dashes. International characters are allowed.
#
# See https://goo.gl/xmQnxf for more information and examples of labels.
# @!attribute [rw] encryption_spec
# @return [::Google::Cloud::AIPlatform::V1::EncryptionSpec]
# Customer-managed encryption key options for a BatchPredictionJob. If this
# is set, then all resources created by the BatchPredictionJob will be
# encrypted with the provided encryption key.
# @!attribute [rw] disable_container_logging
# @return [::Boolean]
# For custom-trained Models and AutoML Tabular Models, the container of the
# DeployedModel instances will send `stderr` and `stdout` streams to
# Cloud Logging by default. Please note that the logs incur cost,
# which are subject to [Cloud Logging
# pricing](https://cloud.google.com/logging/pricing).
#
# User can disable container logging by setting this flag to true.
class BatchPredictionJob
include ::Google::Protobuf::MessageExts
extend ::Google::Protobuf::MessageExts::ClassMethods
# Configures the input to
# {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
# {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats Model.supported_input_storage_formats}
# for Model's supported input formats, and how instances should be expressed
# via any of them.
# @!attribute [rw] gcs_source
# @return [::Google::Cloud::AIPlatform::V1::GcsSource]
# The Cloud Storage location for the input instances.
# @!attribute [rw] bigquery_source
# @return [::Google::Cloud::AIPlatform::V1::BigQuerySource]
# The BigQuery location of the input table.
# The schema of the table should be in the format described by the given
# context OpenAPI Schema, if one is provided. The table may contain
# additional columns that are not described by the schema, and they will
# be ignored.
# @!attribute [rw] instances_format
# @return [::String]
# Required. The format in which instances are given, must be one of the
# [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
# {::Google::Cloud::AIPlatform::V1::Model#supported_input_storage_formats supported_input_storage_formats}.
class InputConfig
include ::Google::Protobuf::MessageExts
extend ::Google::Protobuf::MessageExts::ClassMethods
end
# Configuration defining how to transform batch prediction input instances to
# the instances that the Model accepts.
# @!attribute [rw] instance_type
# @return [::String]
# The format of the instance that the Model accepts. Vertex AI will
# convert compatible
# [batch prediction input instance
# formats][google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig.instances_format]
# to the specified format.
#
# Supported values are:
#
# * `object`: Each input is converted to JSON object format.
# * For `bigquery`, each row is converted to an object.
# * For `jsonl`, each line of the JSONL input must be an object.
# * Does not apply to `csv`, `file-list`, `tf-record`, or
# `tf-record-gzip`.
#
# * `array`: Each input is converted to JSON array format.
# * For `bigquery`, each row is converted to an array. The order
# of columns is determined by the BigQuery column order, unless
# {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
# is populated.
# {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
# must be populated for specifying field orders.
# * For `jsonl`, if each line of the JSONL input is an object,
# {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
# must be populated for specifying field orders.
# * Does not apply to `csv`, `file-list`, `tf-record`, or
# `tf-record-gzip`.
#
# If not specified, Vertex AI converts the batch prediction input as
# follows:
#
# * For `bigquery` and `csv`, the behavior is the same as `array`. The
# order of columns is the same as defined in the file or table, unless
# {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
# is populated.
# * For `jsonl`, the prediction instance format is determined by
# each line of the input.
# * For `tf-record`/`tf-record-gzip`, each record will be converted to
# an object in the format of `{"b64": <value>}`, where `<value>` is
# the Base64-encoded string of the content of the record.
# * For `file-list`, each file in the list will be converted to an
# object in the format of `{"b64": <value>}`, where `<value>` is
# the Base64-encoded string of the content of the file.
# @!attribute [rw] key_field
# @return [::String]
# The name of the field that is considered as a key.
#
# The values identified by the key field is not included in the transformed
# instances that is sent to the Model. This is similar to
# specifying this name of the field in
# {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}.
# In addition, the batch prediction output will not include the instances.
# Instead the output will only include the value of the key field, in a
# field named `key` in the output:
#
# * For `jsonl` output format, the output will have a `key` field
# instead of the `instance` field.
# * For `csv`/`bigquery` output format, the output will have have a `key`
# column instead of the instance feature columns.
#
# The input must be JSONL with objects at each line, CSV, BigQuery
# or TfRecord.
# @!attribute [rw] included_fields
# @return [::Array<::String>]
# Fields that will be included in the prediction instance that is
# sent to the Model.
#
# If
# {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#instance_type instance_type}
# is `array`, the order of field names in included_fields also determines
# the order of the values in the array.
#
# When included_fields is populated,
# {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#excluded_fields excluded_fields}
# must be empty.
#
# The input must be JSONL with objects at each line, CSV, BigQuery
# or TfRecord.
# @!attribute [rw] excluded_fields
# @return [::Array<::String>]
# Fields that will be excluded in the prediction instance that is
# sent to the Model.
#
# Excluded will be attached to the batch prediction output if
# {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#key_field key_field}
# is not specified.
#
# When excluded_fields is populated,
# {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::InstanceConfig#included_fields included_fields}
# must be empty.
#
# The input must be JSONL with objects at each line, CSV, BigQuery
# or TfRecord.
class InstanceConfig
include ::Google::Protobuf::MessageExts
extend ::Google::Protobuf::MessageExts::ClassMethods
end
# Configures the output of
# {::Google::Cloud::AIPlatform::V1::BatchPredictionJob BatchPredictionJob}. See
# {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats Model.supported_output_storage_formats}
# for supported output formats, and how predictions are expressed via any of
# them.
# @!attribute [rw] gcs_destination
# @return [::Google::Cloud::AIPlatform::V1::GcsDestination]
# The Cloud Storage location of the directory where the output is
# to be written to. In the given directory a new directory is created.
# Its name is `prediction-<model-display-name>-<job-create-time>`,
# where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format.
# Inside of it files `predictions_0001.<extension>`,
# `predictions_0002.<extension>`, ..., `predictions_N.<extension>`
# are created where `<extension>` depends on chosen
# {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format},
# and N may equal 0001 and depends on the total number of successfully
# predicted instances. If the Model has both
# {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
# and
# {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
# schemata defined then each such file contains predictions as per the
# {::Google::Cloud::AIPlatform::V1::BatchPredictionJob::OutputConfig#predictions_format predictions_format}.
# If prediction for any instance failed (partially or completely), then
# an additional `errors_0001.<extension>`, `errors_0002.<extension>`,...,
# `errors_N.<extension>` files are created (N depends on total number
# of failed predictions). These files contain the failed instances,
# as per their schema, followed by an additional `error` field which as
# value has {::Google::Rpc::Status google.rpc.Status}
# containing only `code` and `message` fields.
# @!attribute [rw] bigquery_destination
# @return [::Google::Cloud::AIPlatform::V1::BigQueryDestination]
# The BigQuery project or dataset location where the output is to be
# written to. If project is provided, a new dataset is created with name
# `prediction_<model-display-name>_<job-create-time>`
# where <model-display-name> is made
# BigQuery-dataset-name compatible (for example, most special characters
# become underscores), and timestamp is in
# YYYY_MM_DDThh_mm_ss_sssZ "based on ISO-8601" format. In the dataset
# two tables will be created, `predictions`, and `errors`.
# If the Model has both
# {::Google::Cloud::AIPlatform::V1::PredictSchemata#instance_schema_uri instance}
# and
# {::Google::Cloud::AIPlatform::V1::PredictSchemata#parameters_schema_uri prediction}
# schemata defined then the tables have columns as follows: The
# `predictions` table contains instances for which the prediction
# succeeded, it has columns as per a concatenation of the Model's
# instance and prediction schemata. The `errors` table contains rows for
# which the prediction has failed, it has instance columns, as per the
# instance schema, followed by a single "errors" column, which as values
# has {::Google::Rpc::Status google.rpc.Status}
# represented as a STRUCT, and containing only `code` and `message`.
# @!attribute [rw] predictions_format
# @return [::String]
# Required. The format in which Vertex AI gives the predictions, must be
# one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
# {::Google::Cloud::AIPlatform::V1::Model#supported_output_storage_formats supported_output_storage_formats}.
class OutputConfig
include ::Google::Protobuf::MessageExts
extend ::Google::Protobuf::MessageExts::ClassMethods
end
# Further describes this job's output.
# Supplements
# {::Google::Cloud::AIPlatform::V1::BatchPredictionJob#output_config output_config}.
# @!attribute [r] gcs_output_directory
# @return [::String]
# Output only. The full path of the Cloud Storage directory created, into
# which the prediction output is written.
# @!attribute [r] bigquery_output_dataset
# @return [::String]
# Output only. The path of the BigQuery dataset created, in
# `bq://projectId.bqDatasetId`
# format, into which the prediction output is written.
# @!attribute [r] bigquery_output_table
# @return [::String]
# Output only. The name of the BigQuery table created, in
# `predictions_<timestamp>`
# format, into which the prediction output is written.
# Can be used by UI to generate the BigQuery output path, for example.
class OutputInfo
include ::Google::Protobuf::MessageExts
extend ::Google::Protobuf::MessageExts::ClassMethods
end
# @!attribute [rw] key
# @return [::String]
# @!attribute [rw] value
# @return [::String]
class LabelsEntry
include ::Google::Protobuf::MessageExts
extend ::Google::Protobuf::MessageExts::ClassMethods
end
end
end
end
end
end