Struct google_api_proto::google::cloud::aiplatform::v1::schema::trainingjob::definition::AutoMlImageClassificationInputs

pub struct AutoMlImageClassificationInputs {
    pub model_type: i32,
    pub base_model_id: String,
    pub budget_milli_node_hours: i64,
    pub disable_early_stopping: bool,
    pub multi_label: bool,
}

Fields

model_type: i32

base_model_id: String

The ID of the base model. If it is specified, the new model will be trained based on the base model. Otherwise, the new model will be trained from scratch. The base model must be in the same Project and Location as the new Model to train, and have the same modelType.

budget_milli_node_hours: i64

The training budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The actual metadata.costMilliNodeHours will be equal or less than this value. If further model training ceases to provide any improvements, it will stop without using the full budget and the metadata.successfulStopReason will be model-converged. Note, node_hour = actual_hour * number_of_nodes_involved. For modelType cloud(default), the budget must be between 8,000 and 800,000 milli node hours, inclusive. The default value is 192,000 which represents one day in wall time, considering 8 nodes are used. For model types mobile-tf-low-latency-1, mobile-tf-versatile-1, mobile-tf-high-accuracy-1, the training budget must be between 1,000 and 100,000 milli node hours, inclusive. The default value is 24,000 which represents one day in wall time on a single node that is used.

disable_early_stopping: bool

Use the entire training budget. This disables the early stopping feature. When false the early stopping feature is enabled, which means that AutoML Image Classification might stop training before the entire training budget has been used.

multi_label: bool

If false, a single-label (multi-class) Model will be trained (i.e. assuming that for each image just up to one annotation may be applicable). If true, a multi-label Model will be trained (i.e. assuming that for each image multiple annotations may be applicable).

Implementations

impl AutoMlImageClassificationInputs

pub fn model_type(&self) -> ModelType

Returns the enum value of model_type, or the default if the field is set to an invalid enum value.

pub fn set_model_type(&mut self, value: ModelType)

Sets model_type to the provided enum value.

Trait Implementations

impl Clone for AutoMlImageClassificationInputs

fn clone(&self) -> AutoMlImageClassificationInputs

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for AutoMlImageClassificationInputs

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

Formats the value using the given formatter.

impl Default for AutoMlImageClassificationInputs

fn default() -> Self

Returns the “default value” for a type.

impl Message for AutoMlImageClassificationInputs

fn encoded_len(&self) -> usize

Returns the encoded length of the message without a length delimiter.

fn clear(&mut self)

Clears the message, resetting all fields to their default.

fn encode(&self, buf: &mut impl BufMut) -> Result<(), EncodeError>

where Self: Sized,

Encodes the message to a buffer.

fn encode_to_vec(&self) -> Vec<u8>

where Self: Sized,

Encodes the message to a newly allocated buffer.

fn encode_length_delimited( &self, buf: &mut impl BufMut, ) -> Result<(), EncodeError>

where Self: Sized,

Encodes the message with a length-delimiter to a buffer.

fn encode_length_delimited_to_vec(&self) -> Vec<u8>

where Self: Sized,

Encodes the message with a length-delimiter to a newly allocated buffer.

fn decode(buf: impl Buf) -> Result<Self, DecodeError>

where Self: Default,

Decodes an instance of the message from a buffer.

fn decode_length_delimited(buf: impl Buf) -> Result<Self, DecodeError>

where Self: Default,

Decodes a length-delimited instance of the message from the buffer.

fn merge(&mut self, buf: impl Buf) -> Result<(), DecodeError>

where Self: Sized,

Decodes an instance of the message from a buffer, and merges it into self.

fn merge_length_delimited(&mut self, buf: impl Buf) -> Result<(), DecodeError>

where Self: Sized,

Decodes a length-delimited instance of the message from buffer, and merges it into self.

impl PartialEq for AutoMlImageClassificationInputs

fn eq(&self, other: &AutoMlImageClassificationInputs) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

This method tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for AutoMlImageClassificationInputs