gpu-workload/triton/loadgenerator/locustfile.py

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from locust import FastHttpUser, task, between
from locust import LoadTestShape
import json
import os


class ProfileLoad(LoadTestShape):
    '''
    This load profile starts at 0 and steps up by step_users
    increments every tick, up to target_users. After reaching
    target_user level, load will stay at target_user level
    until time_limit is reached.
    '''

    target_users = 1000
    step_users = 50  # ramp users each step
    time_limit = 3600  # seconds

    def tick(self):
        num_steps = self.target_users / self.step_users
        run_time = round(self.get_run_time())

        if run_time < self.time_limit:
            if num_steps < run_time:
                user_count = num_steps * self.step_users
            else:
                user_count = self.target_users
            return (user_count, self.step_users)
        else:
            return None


class TritonUser(FastHttpUser):
    wait_time = between(0.2, 0.2)

    @task()
    def bert(self):
        with self.client.post(self.infer_url,
                              catch_response=True, data=json.dumps(self.data)
                              ) as response:
            if response.status_code == 200:
                response.success()
            else:
                response.failure(f'{response.status_code} {response.reason}')

    def on_start(self):
        with open('request.json') as f:
            self.data = json.load(f)

        model_name = os.getenv('MODEL_NAME', 'bert_tf')

        self.infer_url = f'{self.environment.host}/v2/models/{model_name}/infer'