Struct google_ml1::GoogleCloudMlV1__PredictionInput

pub struct GoogleCloudMlV1__PredictionInput {
    pub model_name: Option<String>,
    pub signature_name: Option<String>,
    pub runtime_version: Option<String>,
    pub batch_size: Option<String>,
    pub max_worker_count: Option<String>,
    pub input_paths: Option<Vec<String>>,
    pub uri: Option<String>,
    pub output_path: Option<String>,
    pub data_format: Option<String>,
    pub version_name: Option<String>,
    pub region: Option<String>,
    pub output_data_format: Option<String>,
}

Represents input parameters for a prediction job.

This type is not used in any activity, and only used as part of another schema.

Fields

model_name: Option<String>

Use this field if you want to use the default version for the specified model. The string must use the following format:

"projects/YOUR_PROJECT/models/YOUR_MODEL"

signature_name: Option<String>

Optional. The name of the signature defined in the SavedModel to use for this job. Please refer to SavedModel for information about how to use signatures.

Defaults to DEFAULT_SERVING_SIGNATURE_DEF_KEY , which is "serving_default".

runtime_version: Option<String>

Optional. The AI Platform runtime version to use for this batch prediction. If not set, AI Platform will pick the runtime version used during the CreateVersion request for this model version, or choose the latest stable version when model version information is not available such as when the model is specified by uri.

batch_size: Option<String>

Optional. Number of records per batch, defaults to 64. The service will buffer batch_size number of records in memory before invoking one Tensorflow prediction call internally. So take the record size and memory available into consideration when setting this parameter.

max_worker_count: Option<String>

Optional. The maximum number of workers to be used for parallel processing. Defaults to 10 if not specified.

input_paths: Option<Vec<String>>

Required. The Cloud Storage location of the input data files. May contain wildcards.

uri: Option<String>

Use this field if you want to specify a Google Cloud Storage path for the model to use.

output_path: Option<String>

Required. The output Google Cloud Storage location.

data_format: Option<String>

Required. The format of the input data files.

version_name: Option<String>

Use this field if you want to specify a version of the model to use. The string is formatted the same way as model_version, with the addition of the version information:

"projects/YOUR_PROJECT/models/YOUR_MODEL/versions/YOUR_VERSION"

region: Option<String>

Required. The Google Compute Engine region to run the prediction job in. See the available regions for AI Platform services.

output_data_format: Option<String>

Optional. Format of the output data files, defaults to JSON.

Trait Implementations

impl Part for GoogleCloudMlV1__PredictionInput

impl Default for GoogleCloudMlV1__PredictionInput

fn default() -> GoogleCloudMlV1__PredictionInput

Returns the "default value" for a type.

impl Clone for GoogleCloudMlV1__PredictionInput

fn clone(&self) -> GoogleCloudMlV1__PredictionInput

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for GoogleCloudMlV1__PredictionInput

fn fmt(&self, f: &mut Formatter) -> Result

Formats the value using the given formatter.

impl Serialize for GoogleCloudMlV1__PredictionInput

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error> where
    __S: Serializer, 

Serialize this value into the given Serde serializer.

impl<'de> Deserialize<'de> for GoogleCloudMlV1__PredictionInput

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
    __D: Deserializer<'de>, 

Deserialize this value from the given Serde deserializer.