lib/google_api/machine_learning/v1/model/google_cloud_ml_v1__job.ex

# Copyright 2019 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
#
#     http://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.

# NOTE: This file is auto generated by the elixir code generator program.
# Do not edit this file manually.

defmodule GoogleApi.MachineLearning.V1.Model.GoogleCloudMlV1_Job do
  @moduledoc """
  Represents a training or prediction job.

  ## Attributes

  *   `createTime` (*type:* `DateTime.t`, *default:* `nil`) - Output only. When the job was created.
  *   `endTime` (*type:* `DateTime.t`, *default:* `nil`) - Output only. When the job processing was completed.
  *   `errorMessage` (*type:* `String.t`, *default:* `nil`) - Output only. The details of a failure or a cancellation.
  *   `etag` (*type:* `String.t`, *default:* `nil`) - `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a job from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform job updates in order to avoid race conditions: An `etag` is returned in the response to `GetJob`, and systems are expected to put that etag in the request to `UpdateJob` to ensure that their change will be applied to the same version of the job.
  *   `jobId` (*type:* `String.t`, *default:* `nil`) - Required. The user-specified id of the job.
  *   `jobPosition` (*type:* `String.t`, *default:* `nil`) - Output only. It's only effect when the job is in QUEUED state. If it's positive, it indicates the job's position in the job scheduler. It's 0 when the job is already scheduled.
  *   `labels` (*type:* `map()`, *default:* `nil`) - Optional. One or more labels that you can add, to organize your jobs. Each label is a key-value pair, where both the key and the value are arbitrary strings that you supply. For more information, see the documentation on using labels.
  *   `predictionInput` (*type:* `GoogleApi.MachineLearning.V1.Model.GoogleCloudMlV1_PredictionInput.t`, *default:* `nil`) - Input parameters to create a prediction job.
  *   `predictionOutput` (*type:* `GoogleApi.MachineLearning.V1.Model.GoogleCloudMlV1_PredictionOutput.t`, *default:* `nil`) - The current prediction job result.
  *   `startTime` (*type:* `DateTime.t`, *default:* `nil`) - Output only. When the job processing was started.
  *   `state` (*type:* `String.t`, *default:* `nil`) - Output only. The detailed state of a job.
  *   `trainingInput` (*type:* `GoogleApi.MachineLearning.V1.Model.GoogleCloudMlV1_TrainingInput.t`, *default:* `nil`) - Input parameters to create a training job.
  *   `trainingOutput` (*type:* `GoogleApi.MachineLearning.V1.Model.GoogleCloudMlV1_TrainingOutput.t`, *default:* `nil`) - The current training job result.
  """

  use GoogleApi.Gax.ModelBase

  @type t :: %__MODULE__{
          :createTime => DateTime.t() | nil,
          :endTime => DateTime.t() | nil,
          :errorMessage => String.t() | nil,
          :etag => String.t() | nil,
          :jobId => String.t() | nil,
          :jobPosition => String.t() | nil,
          :labels => map() | nil,
          :predictionInput =>
            GoogleApi.MachineLearning.V1.Model.GoogleCloudMlV1_PredictionInput.t() | nil,
          :predictionOutput =>
            GoogleApi.MachineLearning.V1.Model.GoogleCloudMlV1_PredictionOutput.t() | nil,
          :startTime => DateTime.t() | nil,
          :state => String.t() | nil,
          :trainingInput =>
            GoogleApi.MachineLearning.V1.Model.GoogleCloudMlV1_TrainingInput.t() | nil,
          :trainingOutput =>
            GoogleApi.MachineLearning.V1.Model.GoogleCloudMlV1_TrainingOutput.t() | nil
        }

  field(:createTime, as: DateTime)
  field(:endTime, as: DateTime)
  field(:errorMessage)
  field(:etag)
  field(:jobId)
  field(:jobPosition)
  field(:labels, type: :map)
  field(:predictionInput, as: GoogleApi.MachineLearning.V1.Model.GoogleCloudMlV1_PredictionInput)

  field(:predictionOutput, as: GoogleApi.MachineLearning.V1.Model.GoogleCloudMlV1_PredictionOutput)

  field(:startTime, as: DateTime)
  field(:state)
  field(:trainingInput, as: GoogleApi.MachineLearning.V1.Model.GoogleCloudMlV1_TrainingInput)
  field(:trainingOutput, as: GoogleApi.MachineLearning.V1.Model.GoogleCloudMlV1_TrainingOutput)
end

defimpl Poison.Decoder, for: GoogleApi.MachineLearning.V1.Model.GoogleCloudMlV1_Job do
  def decode(value, options) do
    GoogleApi.MachineLearning.V1.Model.GoogleCloudMlV1_Job.decode(value, options)
  end
end

defimpl Poison.Encoder, for: GoogleApi.MachineLearning.V1.Model.GoogleCloudMlV1_Job do
  def encode(value, options) do
    GoogleApi.Gax.ModelBase.encode(value, options)
  end
end