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,
}
}
}