Struct google_ml1::api::GoogleCloudMlV1__PredictionInput

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

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.

data_format: Option<String>

Required. The format of the input data files.

input_paths: Option<Vec<String>>

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

max_worker_count: Option<String>

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

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"

output_data_format: Option<String>

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

output_path: Option<String>

Required. The output Google Cloud Storage location.

region: Option<String>

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

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.

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”.

uri: Option<String>

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

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"

Trait Implementations

impl Clone for GoogleCloudMlV1__PredictionInput

fn clone(&self) -> GoogleCloudMlV1__PredictionInput

Returns a copy of the value.

pub 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 Default for GoogleCloudMlV1__PredictionInput

fn default() -> GoogleCloudMlV1__PredictionInput

Returns the “default value” for a type.

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.

impl Part for GoogleCloudMlV1__PredictionInput

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.