NAME
    gcloud alpha ai-platform jobs submit prediction - start an AI Platform
        batch prediction job

SYNOPSIS
    gcloud alpha ai-platform jobs submit prediction JOB
        --data-format=DATA_FORMAT --input-paths=INPUT_PATH,[INPUT_PATH,...]
        --output-path=OUTPUT_PATH --region=REGION
        (--model=MODEL | --model-dir=MODEL_DIR) [--batch-size=BATCH_SIZE]
        [--labels=[KEY=VALUE,...]] [--max-worker-count=MAX_WORKER_COUNT]
        [--runtime-version=RUNTIME_VERSION] [--signature-name=SIGNATURE_NAME]
        [--version=VERSION]
        [--accelerator-count=ACCELERATOR_COUNT
          --accelerator-type=ACCELERATOR_TYPE] [GCLOUD_WIDE_FLAG ...]

DESCRIPTION
    (ALPHA) Start an AI Platform batch prediction job.

POSITIONAL ARGUMENTS
     JOB
        Name of the batch prediction job.

REQUIRED FLAGS
     --data-format=DATA_FORMAT
        Data format of the input files. DATA_FORMAT must be one of:

         text
            Text and JSON files; for text files, see
            https://www.tensorflow.org/guide/datasets#consuming_text_data, for
            JSON files, see
            https://cloud.google.com/ai-platform/prediction/docs/overview#batch_prediction_input_data
         tf-record
            TFRecord files; see
            https://www.tensorflow.org/guide/datasets#consuming_tfrecord_data
         tf-record-gzip
            GZIP-compressed TFRecord files.

     --input-paths=INPUT_PATH,[INPUT_PATH,...]
        Cloud Storage paths to the instances to run prediction on.

        Wildcards (*) accepted at the end of a path. More than one path can be
        specified if multiple file patterns are needed. For example,

            gs://my-bucket/instances*,gs://my-bucket/other-instances1

        will match any objects whose names start with instances in my-bucket as
        well as the other-instances1 bucket, while

            gs://my-bucket/instance-dir/*

        will match any objects in the instance-dir "directory" (since
        directories aren't a first-class Cloud Storage concept) of my-bucket.

     --output-path=OUTPUT_PATH
        Cloud Storage path to which to save the output. Example:
        gs://my-bucket/output.

     --region=REGION
        The Compute Engine region to run the job in.

     Exactly one of these must be specified:

       --model=MODEL
          Name of the model to use for prediction.

       --model-dir=MODEL_DIR
          Cloud Storage location where the model files are located.

OPTIONAL FLAGS
     --batch-size=BATCH_SIZE
        The number of records per batch. The service will buffer batch_size
        number of records in memory before invoking TensorFlow. Defaults to 64
        if not specified.

     --labels=[KEY=VALUE,...]
        List of label KEY=VALUE pairs to add.

        Keys must start with a lowercase character and contain only hyphens
        (-), underscores (_), lowercase characters, and numbers. Values must
        contain only hyphens (-), underscores (_), lowercase characters, and
        numbers.

     --max-worker-count=MAX_WORKER_COUNT
        The maximum number of workers to be used for parallel processing.
        Defaults to 10 if not specified.

     --runtime-version=RUNTIME_VERSION
        AI Platform runtime version for this job. Must be specified unless
        --master-image-uri is specified instead. It is defined in documentation
        along with the list of supported versions:
        https://cloud.google.com/ai-platform/prediction/docs/runtime-version-list

     --signature-name=SIGNATURE_NAME
        Name of the signature defined in the SavedModel to use for this job.
        Defaults to DEFAULT_SERVING_SIGNATURE_DEF_KEY in
        https://www.tensorflow.org/api_docs/python/tf/compat/v1/saved_model/signature_constants,
        which is "serving_default". Only applies to TensorFlow models.

     --version=VERSION
        Model version to be used.

        This flag may only be given if --model is specified. If unspecified,
        the default version of the model will be used. To list versions for a
        model, run

            $ gcloud ai-platform versions list

     Accelerator Configuration.

     --accelerator-count=ACCELERATOR_COUNT
        The number of accelerators to attach to the machines. Must be >= 1.

        This flag argument must be specified if any of the other arguments in
        this group are specified.

     --accelerator-type=ACCELERATOR_TYPE
        The available types of accelerators. ACCELERATOR_TYPE must be one of:

         nvidia-tesla-k80
            NVIDIA Tesla K80 GPU
         nvidia-tesla-p100
            NVIDIA Tesla P100 GPU.

        This flag argument must be specified if any of the other arguments in
        this group are specified.

GCLOUD WIDE FLAGS
    These flags are available to all commands: --access-token-file, --account,
    --billing-project, --configuration, --flags-file, --flatten, --format,
    --help, --impersonate-service-account, --log-http, --project, --quiet,
    --trace-token, --user-output-enabled, --verbosity.

    Run $ gcloud help for details.

NOTES
    This command is currently in alpha and might change without notice. If this
    command fails with API permission errors despite specifying the correct
    project, you might be trying to access an API with an invitation-only early
    access allowlist. These variants are also available:

        $ gcloud ai-platform jobs submit prediction

        $ gcloud beta ai-platform jobs submit prediction

