async fn create_trial(
        &self,
        input: CreateTrialRequest,
    ) -> Result<CreateTrialResponse, RusotoError<CreateTrialError>> {
        let mut request = self.new_signed_request("POST", "/");
        request.add_header("x-amz-target", "SageMaker.CreateTrial");
        let encoded = serde_json::to_string(&input).unwrap();
        request.set_payload(Some(encoded));

        let response = self
            .sign_and_dispatch(request, CreateTrialError::from_response)
            .await?;
        let mut response = response;
        let response = response.buffer().await.map_err(RusotoError::HttpDispatch)?;
        proto::json::ResponsePayload::new(&response).deserialize::<CreateTrialResponse, _>()
    }
<p>Creates an SageMaker <i>trial</i>. A trial is a set of steps called <i>trial components</i> that produce a machine learning model. A trial is part of a single SageMaker <i>experiment</i>.</p> <p>When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the AWS SDK for Python (Boto), you must use the logging APIs provided by the SDK.</p> <p>You can add tags to a trial and then use the <a>Search</a> API to search for the tags.</p> <p>To get a list of all your trials, call the <a>ListTrials</a> API. To view a trial's properties, call the <a>DescribeTrial</a> API. To create a trial component, call the <a>CreateTrialComponent</a> API.</p>
rusoto/services/sagemaker/src/generated.rs