class_docstr: Benchmarks runtime and error of crypten functions against PyTorch
  
  Args:
      tensor_size (int or tuple): size of tensor for benchmarking runtimes
class_docstr_tok: ["Benchmarks","runtime","and","error","of","crypten","functions","against","PyTorch","Args",":","tensor_size","(","int","or","tuple",")",":","size","of","tensor","for","benchmarking","runtimes"]
code: def __init__(self, tensor_size=(100, 100), device="cpu"):
      self.device = torch.device(device)
      self.tensor_size = tensor_size
  
      # dataframe for benchmarks
      self.df = None
  
imports: import argparse
  import functools
  import os
  import timeit
  from collections import namedtuple
  import crypten
  import crypten.communicator
  import numpy
  import pandas
  import torch
  from examples import multiprocess_launcher
label_desc: Use image node_id 1 to create a new FuncBenchmarks object  with example: obj = FuncBenchmarks(tensor_size, device)