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

gcloud beta ai-platform jobs submit predictionJOB--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][GCLOUD_WIDE_FLAG …]

JOB

Name of the batch prediction job.

--data-format=DATA_FORMAT

Data format of the input files.DATA_FORMAT must be oneof:

text

Text and JSON files; for text files, seehttps://www.tensorflow.org/guide/datasets#consuming_text_data, for JSON files,seehttps://cloud.google.com/ai-platform/prediction/docs/overview#batch_prediction_input_data

tf-record

TFRecord files; seehttps://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 theend of a path. More thanone 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 withinstances inmy-bucket as well as theother-instances1 bucket,while

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

will match any objects in theinstance-dir "directory" (sincedirectories aren't a first-class Cloud Storage concept) ofmy-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.

--batch-size=BATCH_SIZE

The number of records per batch. The service will buffer batch_size number ofrecords 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, andnumbers. 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 10if 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 alongwith 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 toDEFAULT_SERVING_SIGNATURE_DEF_KEY inhttps://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 defaultversion of the model will be used. To list versions for a model, run

gcloudai-platformversionslist

Run$gcloud help for details.