code: def __init__(
      self, model, input_tensors, device, n_warmup=50, n_runs=1000
  ):
      self.model = model
      self.input_tensors = input_tensors
      self.device = device
      self.n_warmup = n_warmup
      self.n_runs = n_runs
  
imports: import time
  from abc import abstractmethod, ABC
  from typing import Any, Dict, Type
  import numpy
  from loguru import logger
  from tqdm import tqdm
  from nebullvm.core.models import DeepLearningFramework, ModelParams, DeviceType
  from nebullvm.operations.inference_learners.base import BaseInferenceLearner
  from nebullvm.optional_modules.tensorflow import tensorflow
  from nebullvm.optional_modules.torch import torch, DataLoader
  from nebullvm.tools.data import DataManager
  from nebullvm.tools.onnx import create_model_inputs_onnx
  from nebullvm.tools.pytorch import create_model_inputs_torch
  from nebullvm.tools.tf import create_model_inputs_tf
  from nebullvm.tools.utils import check_input_data, extract_info_from_data, is_data_subscriptable, check_device
label_desc: Use image node_id 1 to create a new BaseBenchmark object from inherited base classes: ABC with example: obj = BaseBenchmark(model, input_tensors, device, n_warmup, n_runs)