use crate::ml;
use serde::{Deserialize, Serialize};
#[derive(Clone, Default, Debug, PartialEq, Serialize, Deserialize)]
pub struct TrainPredict {
#[serde(
rename = "input_query",
default,
skip_serializing_if = "Option::is_none"
)]
pub input_query: Option<ml::InputQuery>,
#[serde(
rename = "parameters",
default,
skip_serializing_if = "Option::is_none"
)]
pub parameters: Option<ml::TrainParameters>,
#[serde(
rename = "input_data",
default,
skip_serializing_if = "Option::is_none"
)]
pub input_data: Option<ml::PredictionResult>,
#[serde(
rename = "input_index",
default,
skip_serializing_if = "Option::is_none"
)]
pub input_index: Option<Vec<String>>,
}
impl TrainPredict {
pub fn new() -> TrainPredict {
TrainPredict {
input_query: None,
parameters: None,
input_data: None,
input_index: None,
}
}
}